Multi-objective optimization to predict muscle tensions in a pinch function using genetic algorithm

NASA Astrophysics Data System (ADS)

Bensghaier, Amani; Romdhane, Lotfi; Benouezdou, Fethi

2012-03-01

This work is focused on the determination of the thumb and the index finger muscle tensions in a tip pinch task. A biomechanical model of the musculoskeletal system of the thumb and the index finger is developed. Due to the assumptions made in carrying out the biomechanical model, the formulated force analysis problem is indeterminate leading to an infinite number of solutions. Thus, constrained single and multi-objective optimization methodologies are used in order to explore the muscular redundancy and to predict optimal muscle tension distributions. Various models are investigated using the optimization process. The basic criteria to minimize are the sum of the muscle stresses, the sum of individual muscle tensions and the maximum muscle stress. The multi-objective optimization is solved using a Pareto genetic algorithm to obtain non-dominated solutions, defined as the set of optimal distributions of muscle tensions. The results show the advantage of the multi-objective formulation over the single objective one. The obtained solutions are compared to those available in the literature demonstrating the effectiveness of our approach in the analysis of the fingers musculoskeletal systems when predicting muscle tensions.

Exploring the Pareto frontier using multisexual evolutionary algorithms: an application to a flexible manufacturing problem

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.; Subbu, Raj

2002-12-01

In multi-objective optimization (MOO) problems we need to optimize many possibly conflicting objectives. For instance, in manufacturing planning we might want to minimize the cost and production time while maximizing the product's quality. We propose the use of evolutionary algorithms (EAs) to solve these problems. Solutions are represented as individuals in a population and are assigned scores according to a fitness function that determines their relative quality. Strong solutions are selected for reproduction, and pass their genetic material to the next generation. Weak solutions are removed from the population. The fitness function evaluates each solution and returns a related score. In MOO problems, this fitness function is vector-valued, i.e. it returns a value for each objective. Therefore, instead of a global optimum, we try to find the Pareto-optimal or non-dominated frontier. We use multi-sexual EAs with as many genders as optimization criteria. We have created new crossover and gender assignment functions, and experimented with various parameters to determine the best setting (yielding the highest number of non-dominated solutions.) These experiments are conducted using a variety of fitness functions, and the algorithms are later evaluated on a flexible manufacturing problem with total cost and time minimization objectives.

A multi-criteria approach to camera motion design for volume data animation.

PubMed

Hsu, Wei-Hsien; Zhang, Yubo; Ma, Kwan-Liu

2013-12-01

We present an integrated camera motion design and path generation system for building volume data animations. Creating animations is an essential task in presenting complex scientific visualizations. Existing visualization systems use an established animation function based on keyframes selected by the user. This approach is limited in providing the optimal in-between views of the data. Alternatively, computer graphics and virtual reality camera motion planning is frequently focused on collision free movement in a virtual walkthrough. For semi-transparent, fuzzy, or blobby volume data the collision free objective becomes insufficient. Here, we provide a set of essential criteria focused on computing camera paths to establish effective animations of volume data. Our dynamic multi-criteria solver coupled with a force-directed routing algorithm enables rapid generation of camera paths. Once users review the resulting animation and evaluate the camera motion, they are able to determine how each criterion impacts path generation. In this paper, we demonstrate how incorporating this animation approach with an interactive volume visualization system reduces the effort in creating context-aware and coherent animations. This frees the user to focus on visualization tasks with the objective of gaining additional insight from the volume data.

Negotiating designs of multi-purpose reservoir systems in international basins

NASA Astrophysics Data System (ADS)

Geressu, Robel; Harou, Julien

2016-04-01

Given increasing agricultural and energy demands, coordinated management of multi-reservoir systems could help increase production without further stressing available water resources. However, regional or international disputes about water-use rights pose a challenge to efficient expansion and management of many large reservoir systems. Even when projects are likely to benefit all stakeholders, agreeing on the design, operation, financing, and benefit sharing can be challenging. This is due to the difficulty of considering multiple stakeholder interests in the design of projects and understanding the benefit trade-offs that designs imply. Incommensurate performance metrics, incomplete knowledge on system requirements, lack of objectivity in managing conflict and difficulty to communicate complex issue exacerbate the problem. This work proposes a multi-step hybrid multi-objective optimization and multi-criteria ranking approach for supporting negotiation in water resource systems. The approach uses many-objective optimization to generate alternative efficient designs and reveal the trade-offs between conflicting objectives. This enables informed elicitation of criteria weights for further multi-criteria ranking of alternatives. An ideal design would be ranked as best by all stakeholders. Resource-sharing mechanisms such as power-trade and/or cost sharing may help competing stakeholders arrive at designs acceptable to all. Many-objective optimization helps suggests efficient designs (reservoir site, its storage size and operating rule) and coordination levels considering the perspectives of multiple stakeholders simultaneously. We apply the proposed approach to a proof-of-concept study of the expansion of the Blue Nile transboundary reservoir system.

Multi-criteria evaluation of wastewater treatment plant control strategies under uncertainty.

PubMed

Flores-Alsina, Xavier; Rodríguez-Roda, Ignasi; Sin, Gürkan; Gernaey, Krist V

2008-11-01

The evaluation of activated sludge control strategies in wastewater treatment plants (WWTP) via mathematical modelling is a complex activity because several objectives; e.g. economic, environmental, technical and legal; must be taken into account at the same time, i.e. the evaluation of the alternatives is a multi-criteria problem. Activated sludge models are not well characterized and some of the parameters can present uncertainty, e.g. the influent fractions arriving to the facility and the effect of either temperature or toxic compounds on the kinetic parameters, having a strong influence in the model predictions used during the evaluation of the alternatives and affecting the resulting rank of preferences. Using a simplified version of the IWA Benchmark Simulation Model No. 2 as a case study, this article shows the variations in the decision making when the uncertainty in activated sludge model (ASM) parameters is either included or not during the evaluation of WWTP control strategies. This paper comprises two main sections. Firstly, there is the evaluation of six WWTP control strategies using multi-criteria decision analysis setting the ASM parameters at their default value. In the following section, the uncertainty is introduced, i.e. input uncertainty, which is characterized by probability distribution functions based on the available process knowledge. Next, Monte Carlo simulations are run to propagate input through the model and affect the different outcomes. Thus (i) the variation in the overall degree of satisfaction of the control objectives for the generated WWTP control strategies is quantified, (ii) the contributions of environmental, legal, technical and economic objectives to the existing variance are identified and finally (iii) the influence of the relative importance of the control objectives during the selection of alternatives is analyzed. The results show that the control strategies with an external carbon source reduce the output uncertainty in the criteria used to quantify the degree of satisfaction of environmental, technical and legal objectives, but increasing the economical costs and their variability as a trade-off. Also, it is shown how a preliminary selected alternative with cascade ammonium controller becomes less desirable when input uncertainty is included, having simpler alternatives more chance of success.

IFSM fractal image compression with entropy and sparsity constraints: A sequential quadratic programming approach

NASA Astrophysics Data System (ADS)

Kunze, Herb; La Torre, Davide; Lin, Jianyi

2017-01-01

We consider the inverse problem associated with IFSM: Given a target function f , find an IFSM, such that its fixed point f ¯ is sufficiently close to f in the Lp distance. Forte and Vrscay [1] showed how to reduce this problem to a quadratic optimization model. In this paper, we extend the collage-based method developed by Kunze, La Torre and Vrscay ([2][3][4]), by proposing the minimization of the 1-norm instead of the 0-norm. In fact, optimization problems involving the 0-norm are combinatorial in nature, and hence in general NP-hard. To overcome these difficulties, we introduce the 1-norm and propose a Sequential Quadratic Programming algorithm to solve the corresponding inverse problem. As in Kunze, La Torre and Vrscay [3] in our formulation, the minimization of collage error is treated as a multi-criteria problem that includes three different and conflicting criteria i.e., collage error, entropy and sparsity. This multi-criteria program is solved by means of a scalarization technique which reduces the model to a single-criterion program by combining all objective functions with different trade-off weights. The results of some numerical computations are presented.

Multi-criteria decision making development of ion chromatographic method for determination of inorganic anions in oilfield waters based on artificial neural networks retention model.

PubMed

Stefanović, Stefica Cerjan; Bolanča, Tomislav; Luša, Melita; Ukić, Sime; Rogošić, Marko

2012-02-24

This paper describes the development of ad hoc methodology for determination of inorganic anions in oilfield water, since their composition often significantly differs from the average (concentration of components and/or matrix). Therefore, fast and reliable method development has to be performed in order to ensure the monitoring of desired properties under new conditions. The method development was based on computer assisted multi-criteria decision making strategy. The used criteria were: maximal value of objective functions used, maximal robustness of the separation method, minimal analysis time, and maximal retention distance between two nearest components. Artificial neural networks were used for modeling of anion retention. The reliability of developed method was extensively tested by the validation of performance characteristics. Based on validation results, the developed method shows satisfactory performance characteristics, proving the successful application of computer assisted methodology in the described case study. Copyright © 2011 Elsevier B.V. All rights reserved.

A Multi-Objective Decision Making Approach for Solving the Image Segmentation Fusion Problem.

PubMed

Khelifi, Lazhar; Mignotte, Max

2017-08-01

Image segmentation fusion is defined as the set of methods which aim at merging several image segmentations, in a manner that takes full advantage of the complementarity of each one. Previous relevant researches in this field have been impeded by the difficulty in identifying an appropriate single segmentation fusion criterion, providing the best possible, i.e., the more informative, result of fusion. In this paper, we propose a new model of image segmentation fusion based on multi-objective optimization which can mitigate this problem, to obtain a final improved result of segmentation. Our fusion framework incorporates the dominance concept in order to efficiently combine and optimize two complementary segmentation criteria, namely, the global consistency error and the F-measure (precision-recall) criterion. To this end, we present a hierarchical and efficient way to optimize the multi-objective consensus energy function related to this fusion model, which exploits a simple and deterministic iterative relaxation strategy combining the different image segments. This step is followed by a decision making task based on the so-called "technique for order performance by similarity to ideal solution". Results obtained on two publicly available databases with manual ground truth segmentations clearly show that our multi-objective energy-based model gives better results than the classical mono-objective one.

Near-Earth object hazardous impact: A Multi-Criteria Decision Making approach.

PubMed

Sánchez-Lozano, J M; Fernández-Martínez, M

2016-11-16

The impact of a near-Earth object (NEO) may release large amounts of energy and cause serious damage. Several NEO hazard studies conducted over the past few years provide forecasts, impact probabilities and assessment ratings, such as the Torino and Palermo scales. These high-risk NEO assessments involve several criteria, including impact energy, mass, and absolute magnitude. The main objective of this paper is to provide the first Multi-Criteria Decision Making (MCDM) approach to classify hazardous NEOs. Our approach applies a combination of two methods from a widely utilized decision making theory. Specifically, the Analytic Hierarchy Process (AHP) methodology is employed to determine the criteria weights, which influence the decision making, and the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is used to obtain a ranking of alternatives (potentially hazardous NEOs). In addition, NEO datasets provided by the NASA Near-Earth Object Program are utilized. This approach allows the classification of NEOs by descending order of their TOPSIS ratio, a single quantity that contains all of the relevant information for each object.

The prioritisation of invasive alien plant control projects using a multi-criteria decision model informed by stakeholder input and spatial data.

PubMed

Forsyth, G G; Le Maitre, D C; O'Farrell, P J; van Wilgen, B W

2012-07-30

Invasions by alien plants are a significant threat to the biodiversity and functioning of ecosystems and the services they provide. The South African Working for Water program was established to address this problem. It needs to formulate objective and transparent priorities for clearing in the face of multiple and sometimes conflicting demands. This study used the analytic hierarchy process (a multi-criteria decision support technique) to develop and rank criteria for prioritising alien plant control operations in the Western Cape, South Africa. Stakeholder workshops were held to identify a goal and criteria and to conduct pair-wise comparisons to weight the criteria with respect to invasive alien plant control. The combination of stakeholder input (to develop decision models) with data-driven model solutions enabled us to include many alternatives (water catchments), that would otherwise not have been feasible. The most important criteria included the capacity to maintain gains made through control operations, the potential to enhance water resources and conserve biodiversity, and threats from priority invasive alien plant species. We selected spatial datasets and used them to generate weights that could be used to objectively compare alternatives with respect to agreed criteria. The analysis showed that there are many high priority catchments which are not receiving any funding and low priority catchments which are receiving substantial allocations. Clearly, there is a need for realigning priorities, including directing sufficient funds to the highest priority catchments to provide effective control. This approach provided a tractable, consensus-based solution that can be used to direct clearing operations. Copyright © 2012 Elsevier Ltd. All rights reserved.

Controller design for wind turbine load reduction via multiobjective parameter synthesis

NASA Astrophysics Data System (ADS)

Hoffmann, A. F.; Weiβ, F. A.

2016-09-01

During the design process for a wind turbine load reduction controller many different, sometimes conflicting requirements must be fulfilled simultaneously. If the requirements can be expressed as mathematical criteria, such a design problem can be solved by a criterion-vector and multi-objective design optimization. The software environment MOPS (Multi-Objective Parameter Synthesis) supports the engineer for such a design optimization. In this paper MOPS is applied to design a multi-objective load reduction controller for the well-known DTU 10 MW reference wind turbine. A significant reduction in the fatigue criteria especially the blade damage can be reached by the use of an additional Individual Pitch Controller (IPC) and an additional tower damper. This reduction is reached as a trade-off with an increase of actuator load.

A Multi Criteria Group Decision-Making Model for Teacher Evaluation in Higher Education Based on Cloud Model and Decision Tree

ERIC Educational Resources Information Center

Chang, Ting-Cheng; Wang, Hui

2016-01-01

This paper proposes a cloud multi-criteria group decision-making model for teacher evaluation in higher education which is involving subjectivity, imprecision and fuzziness. First, selecting the appropriate evaluation index depending on the evaluation objectives, indicating a clear structural relationship between the evaluation index and…

Design review of fluid film bearing testers

NASA Technical Reports Server (NTRS)

Scharrer, Joseph K.

1993-01-01

The designs of three existing testers (Hybrid Bearing Tester, OTV Bearing Tester, and Long Life Bearing Tester) owned by NASA were reviewed for their capability to serve as a multi-purpose cryogenic fluid film bearing tester. The primary tester function is the validation of analytical predictions for fluid film bearing steady state and dynamic performance. Evaluation criteria were established for test bearing configurations, test fluids, instrumentation, and test objectives. Each tester was evaluated with respect to these criteria. A determination was made of design improvements which would allow the testers to meet the stated criteria. The cost and time required to make the design changes were estimated. A recommendation based on the results of this study was made to proceed with the Hybrid Bearing Tester.

Multi-criteria Integrated Resource Assessment (MIRA)

EPA Pesticide Factsheets

MIRA is an approach that facilitates stakeholder engagement for collaborative multi-objective decision making. MIRA is designed to facilitate and support an inclusive, explicit, transparent, iterative learning-based decision process.

Multi-criteria analysis for PM10 planning

NASA Astrophysics Data System (ADS)

Pisoni, Enrico; Carnevale, Claudio; Volta, Marialuisa

To implement sound air quality policies, Regulatory Agencies require tools to evaluate outcomes and costs associated to different emission reduction strategies. These tools are even more useful when considering atmospheric PM10 concentrations due to the complex nonlinear processes that affect production and accumulation of the secondary fraction of this pollutant. The approaches presented in the literature (Integrated Assessment Modeling) are mainly cost-benefit and cost-effective analysis. In this work, the formulation of a multi-objective problem to control particulate matter is proposed. The methodology defines: (a) the control objectives (the air quality indicator and the emission reduction cost functions); (b) the decision variables (precursor emission reductions); (c) the problem constraints (maximum feasible technology reductions). The cause-effect relations between air quality indicators and decision variables are identified tuning nonlinear source-receptor models. The multi-objective problem solution provides to the decision maker a set of not-dominated scenarios representing the efficient trade-off between the air quality benefit and the internal costs (emission reduction technology costs). The methodology has been implemented for Northern Italy, often affected by high long-term exposure to PM10. The source-receptor models used in the multi-objective analysis are identified processing long-term simulations of GAMES multiphase modeling system, performed in the framework of CAFE-Citydelta project.

Multi objective decision making in hybrid energy system design

NASA Astrophysics Data System (ADS)

Merino, Gabriel Guillermo

The design of grid-connected photovoltaic wind generator system supplying a farmstead in Nebraska has been undertaken in this dissertation. The design process took into account competing criteria that motivate the use of different sources of energy for electric generation. The criteria considered were 'Financial', 'Environmental', and 'User/System compatibility'. A distance based multi-objective decision making methodology was developed to rank design alternatives. The method is based upon a precedence order imposed upon the design objectives and a distance metric describing the performance of each alternative. This methodology advances previous work by combining ambiguous information about the alternatives with a decision-maker imposed precedence order in the objectives. Design alternatives, defined by the photovoltaic array and wind generator installed capacities, were analyzed using the multi-objective decision making approach. The performance of the design alternatives was determined by simulating the system using hourly data for an electric load for a farmstead and hourly averages of solar irradiation, temperature and wind speed from eight wind-solar energy monitoring sites in Nebraska. The spatial variability of the solar energy resource within the region was assessed by determining semivariogram models to krige hourly and daily solar radiation data. No significant difference was found in the predicted performance of the system when using kriged solar radiation data, with the models generated vs. using actual data. The spatial variability of the combined wind and solar energy resources was included in the design analysis by using fuzzy numbers and arithmetic. The best alternative was dependent upon the precedence order assumed for the main criteria. Alternatives with no PV array or wind generator dominated when the 'Financial' criteria preceded the others. In contrast, alternatives with a nil component of PV array but a high wind generator component, dominated when the 'Environment' objective or the 'User/System compatibility' objectives were more important than the 'Financial' objectives and they also dominated when the three criteria were considered equally important.

Incorporating ecosystem function concept in environmental planning and decision making by means of multi-criteria evaluation: the case-study of Kalloni, Lesbos, Greece.

PubMed

Oikonomou, Vera; Dimitrakopoulos, Panayiotis G; Troumbis, Andreas Y

2011-01-01

Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.

Incorporating Ecosystem Function Concept in Environmental Planning and Decision Making by Means of Multi-Criteria Evaluation: The Case-Study of Kalloni, Lesbos, Greece

NASA Astrophysics Data System (ADS)

Oikonomou, Vera; Dimitrakopoulos, Panayiotis G.; Troumbis, Andreas Y.

2011-01-01

Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.

Green supplier selection: a new genetic/immune strategy with industrial application

NASA Astrophysics Data System (ADS)

Kumar, Amit; Jain, Vipul; Kumar, Sameer; Chandra, Charu

2016-10-01

With the onset of the 'climate change movement', organisations are striving to include environmental criteria into the supplier selection process. This article hybridises a Green Data Envelopment Analysis (GDEA)-based approach with a new Genetic/Immune Strategy for Data Envelopment Analysis (GIS-DEA). A GIS-DEA approach provides a different view to solving multi-criteria decision making problems using data envelopment analysis (DEA) by considering DEA as a multi-objective optimisation problem with efficiency as one objective and proximity of solution to decision makers' preferences as the other objective. The hybrid approach called GIS-GDEA is applied here to a well-known automobile spare parts manufacturer in India and the results presented. User validation developed based on specific set of criteria suggests that the supplier selection process with GIS-GDEA is more practical than other approaches in a current industrial scenario with multiple decision makers.

Multiple utility constrained multi-objective programs using Bayesian theory

NASA Astrophysics Data System (ADS)

Abbasian, Pooneh; Mahdavi-Amiri, Nezam; Fazlollahtabar, Hamed

2018-03-01

A utility function is an important tool for representing a DM's preference. We adjoin utility functions to multi-objective optimization problems. In current studies, usually one utility function is used for each objective function. Situations may arise for a goal to have multiple utility functions. Here, we consider a constrained multi-objective problem with each objective having multiple utility functions. We induce the probability of the utilities for each objective function using Bayesian theory. Illustrative examples considering dependence and independence of variables are worked through to demonstrate the usefulness of the proposed model.

A Tool for the Automated Design and Evaluation of Habitat Interior Layouts

NASA Technical Reports Server (NTRS)

Simon, Matthew A.; Wilhite, Alan W.

2013-01-01

The objective of space habitat design is to minimize mass and system size while providing adequate space for all necessary equipment and a functional layout that supports crew health and productivity. Unfortunately, development and evaluation of interior layouts is often ignored during conceptual design because of the subjectivity and long times required using current evaluation methods (e.g., human-in-the-loop mockup tests and in-depth CAD evaluations). Early, more objective assessment could prevent expensive design changes that may increase vehicle mass and compromise functionality. This paper describes a new interior design evaluation method to enable early, structured consideration of habitat interior layouts. This interior layout evaluation method features a comprehensive list of quantifiable habitat layout evaluation criteria, automatic methods to measure these criteria from a geometry model, and application of systems engineering tools and numerical methods to construct a multi-objective value function measuring the overall habitat layout performance. In addition to a detailed description of this method, a C++/OpenGL software tool which has been developed to implement this method is also discussed. This tool leverages geometry modeling coupled with collision detection techniques to identify favorable layouts subject to multiple constraints and objectives (e.g., minimize mass, maximize contiguous habitable volume, maximize task performance, and minimize crew safety risks). Finally, a few habitat layout evaluation examples are described to demonstrate the effectiveness of this method and tool to influence habitat design.

Multi-criteria decision making--an approach to setting priorities in health care.

PubMed

Nobre, F F; Trotta, L T; Gomes, L F

1999-12-15

The objective of this paper is to present a multi-criteria decision making (MCDM) approach to support public health decision making that takes into consideration the fuzziness of the decision goals and the behavioural aspect of the decision maker. The approach is used to analyse the process of health technology procurement in a University Hospital in Rio de Janeiro, Brazil. The method, known as TODIM, relies on evaluating alternatives with a set of decision criteria assessed using an ordinal scale. Fuzziness in generating criteria scores and weights or conflicts caused by dealing with different viewpoints of a group of decision makers (DMs) are solved using fuzzy set aggregation rules. The results suggested that MCDM models, incorporating fuzzy set approaches, should form a set of tools for public health decision making analysis, particularly when there are polarized opinions and conflicting objectives from the DM group. Copyright 1999 John Wiley & Sons, Ltd.

Multi-objective optimization of a continuous bio-dissimilation process of glycerol to 1, 3-propanediol.

PubMed

Xu, Gongxian; Liu, Ying; Gao, Qunwang

2016-02-10

This paper deals with multi-objective optimization of continuous bio-dissimilation process of glycerol to 1, 3-propanediol. In order to maximize the production rate of 1, 3-propanediol, maximize the conversion rate of glycerol to 1, 3-propanediol, maximize the conversion rate of glycerol, and minimize the concentration of by-product ethanol, we first propose six new multi-objective optimization models that can simultaneously optimize any two of the four objectives above. Then these multi-objective optimization problems are solved by using the weighted-sum and normal-boundary intersection methods respectively. Both the Pareto filter algorithm and removal criteria are used to remove those non-Pareto optimal points obtained by the normal-boundary intersection method. The results show that the normal-boundary intersection method can successfully obtain the approximate Pareto optimal sets of all the proposed multi-objective optimization problems, while the weighted-sum approach cannot achieve the overall Pareto optimal solutions of some multi-objective problems. Copyright © 2015 Elsevier B.V. All rights reserved.

MANCaLog: A Logic for Multi-Attribute Network Cascades

DTIC Science & Technology

2013-01-01

influence function , whose precise effects will be described later on when we discuss the semantics. As a result, a rule consists of four major parts...i) an influence function , (ii) neighbor criteria, (iii) target criteria, and (iv) a target. Intuitively, (i) specifies how the neighbors influence the...in terms of these elements. First, we define influence functions and neighbor criteria. Definition 2.6 ( Influence Function ). An influence function is a

A multi-objective framework to predict flows of ungauged rivers within regions of sparse hydrometeorologic observation

NASA Astrophysics Data System (ADS)

Alipour, M.; Kibler, K. M.

2017-12-01

Despite advances in flow prediction, managers of ungauged rivers located within broad regions of sparse hydrometeorologic observation still lack prescriptive methods robust to the data challenges of such regions. We propose a multi-objective streamflow prediction framework for regions of minimum observation to select models that balance runoff efficiency with choice of accurate parameter values. We supplement sparse observed data with uncertain or low-resolution information incorporated as `soft' a priori parameter estimates. The performance of the proposed framework is tested against traditional single-objective and constrained single-objective calibrations in two catchments in a remote area of southwestern China. We find that the multi-objective approach performs well with respect to runoff efficiency in both catchments (NSE = 0.74 and 0.72), within the range of efficiencies returned by other models (NSE = 0.67 - 0.78). However, soil moisture capacity estimated by the multi-objective model resonates with a priori estimates (parameter residuals of 61 cm versus 289 and 518 cm for maximum soil moisture capacity in one catchment, and 20 cm versus 246 and 475 cm in the other; parameter residuals of 0.48 versus 0.65 and 0.7 for soil moisture distribution shape factor in one catchment, and 0.91 versus 0.79 and 1.24 in the other). Thus, optimization to a multi-criteria objective function led to very different representations of soil moisture capacity as compared to models selected by single-objective calibration, without compromising runoff efficiency. These different soil moisture representations may translate into considerably different hydrological behaviors. The proposed approach thus offers a preliminary step towards greater process understanding in regions of severe data limitations. For instance, the multi-objective framework may be an adept tool to discern between models of similar efficiency to select models that provide the "right answers for the right reasons". Managers may feel more confident to utilize such models to predict flows in fully ungauged areas.

Multi-criteria objective based climate change impact assessment for multi-purpose multi-reservoir systems

NASA Astrophysics Data System (ADS)

Müller, Ruben; Schütze, Niels

2014-05-01

Water resources systems with reservoirs are expected to be sensitive to climate change. Assessment studies that analyze the impact of climate change on the performance of reservoirs can be divided in two groups: (1) Studies that simulate the operation under projected inflows with the current set of operational rules. Due to non adapted operational rules the future performance of these reservoirs can be underestimated and the impact overestimated. (2) Studies that optimize the operational rules for best adaption of the system to the projected conditions before the assessment of the impact. The latter allows for estimating more realistically future performance and adaption strategies based on new operation rules are available if required. Multi-purpose reservoirs serve various, often conflicting functions. If all functions cannot be served simultaneously at a maximum level, an effective compromise between multiple objectives of the reservoir operation has to be provided. Yet under climate change the historically preferenced compromise may no longer be the most suitable compromise in the future. Therefore a multi-objective based climate change impact assessment approach for multi-purpose multi-reservoir systems is proposed in the study. Projected inflows are provided in a first step using a physically based rainfall-runoff model. In a second step, a time series model is applied to generate long-term inflow time series. Finally, the long-term inflow series are used as driving variables for a simulation-based multi-objective optimization of the reservoir system in order to derive optimal operation rules. As a result, the adapted Pareto-optimal set of diverse best compromise solutions can be presented to the decision maker in order to assist him in assessing climate change adaption measures with respect to the future performance of the multi-purpose reservoir system. The approach is tested on a multi-purpose multi-reservoir system in a mountainous catchment in Germany. A climate change assessment is performed for climate change scenarios based on the SRES emission scenarios A1B, B1 and A2 for a set of statistically downscaled meteorological data. The future performance of the multi-purpose multi-reservoir system is quantified and possible intensifications of trade-offs between management goals or reservoir utilizations are shown.

Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

ERIC Educational Resources Information Center

Manouselis, Nikos; Sampson, Demetrios

This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…

A comparison of representations for discrete multi-criteria decision problems☆

PubMed Central

Gettinger, Johannes; Kiesling, Elmar; Stummer, Christian; Vetschera, Rudolf

2013-01-01

Discrete multi-criteria decision problems with numerous Pareto-efficient solution candidates place a significant cognitive burden on the decision maker. An interactive, aspiration-based search process that iteratively progresses toward the most preferred solution can alleviate this task. In this paper, we study three ways of representing such problems in a DSS, and compare them in a laboratory experiment using subjective and objective measures of the decision process as well as solution quality and problem understanding. In addition to an immediate user evaluation, we performed a re-evaluation several weeks later. Furthermore, we consider several levels of problem complexity and user characteristics. Results indicate that different problem representations have a considerable influence on search behavior, although long-term consistency appears to remain unaffected. We also found interesting discrepancies between subjective evaluations and objective measures. Conclusions from our experiments can help designers of DSS for large multi-criteria decision problems to fit problem representations to the goals of their system and the specific task at hand. PMID:24882912

Sleep and its associations with perceived and objective cognitive impairment in individuals with multiple sclerosis.

PubMed

Hughes, Abbey J; Parmenter, Brett A; Haselkorn, Jodie K; Lovera, Jesus F; Bourdette, Dennis; Boudreau, Eilis; Cameron, Michelle H; Turner, Aaron P

2017-08-01

Problems with sleep and cognitive impairment are common among people with multiple sclerosis (MS). The present study examined the relationship between self-reported sleep and both objective and perceived cognitive impairment in MS. Data were obtained from the baseline assessment of a multi-centre intervention trial (NCT00841321). Participants were 121 individuals with MS. Nearly half (49%) of participants met the criteria for objective cognitive impairment; however, cognitively impaired and unimpaired participants did not differ on any self-reported sleep measures. Nearly two-thirds (65%) of participants met the criteria for 'poor' sleep, and poorer sleep was significantly associated with greater levels of perceived cognitive impairment. Moreover, the relationships between self-reported sleep and perceived cognitive impairment were significant beyond the influence of clinical and demographic factors known to influence sleep and cognitive functioning (e.g. age, sex, education level, disability severity, type of MS, disease duration, depression and fatigue). However, self-reported sleep was not associated with any measures of objective cognitive impairment. Among different types of perceived cognitive impairment, poor self-reported sleep was most commonly related to worse perceived executive function (e.g. planning/organization) and prospective memory. Results from the present study emphasize that self-reported sleep is significantly and independently related to perceived cognitive impairment in MS. In terms of clinical implications, interventions focused on improving sleep may help improve perceived cognitive function and quality of life in this population; however, the impact of improved sleep on objective cognitive function requires further investigation. © 2017 European Sleep Research Society.

New Insights on the White Dwarf Luminosity and Mass Functions from the LSS-GAC Survey

NASA Astrophysics Data System (ADS)

Rebassa-Mansergas, Alberto; Liu, Xiaowei; Cojocaru, Ruxandra; Torres, Santiago; García–Berro, Enrique; Yuan, Haibo; Huang, Yang; Xiang, Maosheng

2015-06-01

The white dwarf (WD) population observed in magnitude-limited surveys can be used to derive the luminosity function (LF) and mass function (MF), once the corresponding volume corrections are employed. However, the WD samples from which the observational LFs and MFs are built are the result of complicated target selection algorithms. Thus, it is difficult to quantify the effects of the observational biases on the observed functions. The LAMOST (Large sky Area Multi-Object fiber Spectroscopic Telescope) spectroscopic survey of the Galactic anti-center (LSS-GAC) has well-defined selection criteria. This is a noticeable advantage over previous surveys. Here we derive the WD LF and MF of the LSS-GAC, and use a Monte Carlo code to simulate the WD population in the Galactic anti-center. We apply the well-defined LSS-GAC selection criteria to the simulated populations, taking into account all observational biases, and perform the first meaningful comparison between the simulated WD LFs and MFs and the observed ones.

Measuring the sustainability of a natural system by using multi-criteria distance function methods: Some critical issues.

PubMed

Diaz-Balteiro, L; Belavenutti, P; Ezquerro, M; González-Pachón, J; Ribeiro Nobre, S; Romero, C

2018-05-15

There is an important body of literature using multi-criteria distance function methods for the aggregation of a battery of sustainability indicators in order to obtain a composite index. This index is considered to be a proxy of the sustainability goodness of a natural system. Although this approach has been profusely used in the literature, it is not exempt from difficulties and potential pitfalls. Thus, in this paper, a significant number of critical issues have been identified showing different procedures capable of avoiding, or at least of mitigating, the inherent potential pitfalls associated with each one. The recommendations made in the paper could increase the theoretical soundness of the multi-criteria distance function methods when this type of approach is applied in the sustainability field, thus increasing the accuracy and realism of the sustainability measurements obtained. Copyright © 2018 Elsevier Ltd. All rights reserved.

Technology selection for ballast water treatment by multi-stakeholders: A multi-attribute decision analysis approach based on the combined weights and extension theory.

PubMed

Ren, Jingzheng

2018-01-01

This objective of this study is to develop a generic multi-attribute decision analysis framework for ranking the technologies for ballast water treatment and determine their grades. An evaluation criteria system consisting of eight criteria in four categories was used to evaluate the technologies for ballast water treatment. The Best-Worst method, which is a subjective weighting method and Criteria importance through inter-criteria correlation method, which is an objective weighting method, were combined to determine the weights of the evaluation criteria. The extension theory was employed to prioritize the technologies for ballast water treatment and determine their grades. An illustrative case including four technologies for ballast water treatment, i.e. Alfa Laval (T 1 ), Hyde (T 2 ), Unitor (T 3 ), and NaOH (T 4 ), were studied by the proposed method, and the Hyde (T 2 ) was recognized as the best technology. Sensitivity analysis was also carried to investigate the effects of the combined coefficients and the weights of the evaluation criteria on the final priority order of the four technologies for ballast water treatment. The sum weighted method and the TOPSIS was also employed to rank the four technologies, and the results determined by these two methods are consistent to that determined by the proposed method in this study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visualising Pareto-optimal trade-offs helps move beyond monetary-only criteria for water management decisions

NASA Astrophysics Data System (ADS)

Hurford, Anthony; Harou, Julien

2014-05-01

Water related eco-system services are important to the livelihoods of the poorest sectors of society in developing countries. Degradation or loss of these services can increase the vulnerability of people decreasing their capacity to support themselves. New approaches to help guide water resources management decisions are needed which account for the non-market value of ecosystem goods and services. In case studies from Brazil and Kenya we demonstrate the capability of many objective Pareto-optimal trade-off analysis to help decision makers balance economic and non-market benefits from the management of existing multi-reservoir systems. A multi-criteria search algorithm is coupled to a water resources management simulator of each basin to generate a set of Pareto-approximate trade-offs representing the best case management decisions. In both cases, volume dependent reservoir release rules are the management decisions being optimised. In the Kenyan case we further assess the impacts of proposed irrigation investments, and how the possibility of new investments impacts the system's trade-offs. During the multi-criteria search (optimisation), performance of different sets of management decisions (policies) is assessed against case-specific objective functions representing provision of water supply and irrigation, hydropower generation and maintenance of ecosystem services. Results are visualised as trade-off surfaces to help decision makers understand the impacts of different policies on a broad range of stakeholders and to assist in decision-making. These case studies show how the approach can reveal unexpected opportunities for win-win solutions, and quantify the trade-offs between investing to increase agricultural revenue and negative impacts on protected ecosystems which support rural livelihoods.

Reliability- and performance-based robust design optimization of MEMS structures considering technological uncertainties

NASA Astrophysics Data System (ADS)

Martowicz, Adam; Uhl, Tadeusz

2012-10-01

The paper discusses the applicability of a reliability- and performance-based multi-criteria robust design optimization technique for micro-electromechanical systems, considering their technological uncertainties. Nowadays, micro-devices are commonly applied systems, especially in the automotive industry, taking advantage of utilizing both the mechanical structure and electronic control circuit on one board. Their frequent use motivates the elaboration of virtual prototyping tools that can be applied in design optimization with the introduction of technological uncertainties and reliability. The authors present a procedure for the optimization of micro-devices, which is based on the theory of reliability-based robust design optimization. This takes into consideration the performance of a micro-device and its reliability assessed by means of uncertainty analysis. The procedure assumes that, for each checked design configuration, the assessment of uncertainty propagation is performed with the meta-modeling technique. The described procedure is illustrated with an example of the optimization carried out for a finite element model of a micro-mirror. The multi-physics approach allowed the introduction of several physical phenomena to correctly model the electrostatic actuation and the squeezing effect present between electrodes. The optimization was preceded by sensitivity analysis to establish the design and uncertain domains. The genetic algorithms fulfilled the defined optimization task effectively. The best discovered individuals are characterized by a minimized value of the multi-criteria objective function, simultaneously satisfying the constraint on material strength. The restriction of the maximum equivalent stresses was introduced with the conditionally formulated objective function with a penalty component. The yielded results were successfully verified with a global uniform search through the input design domain.

Definition and sensitivity of the conceptual MORDOR rainfall-runoff model parameters using different multi-criteria calibration strategies

NASA Astrophysics Data System (ADS)

Garavaglia, F.; Seyve, E.; Gottardi, F.; Le Lay, M.; Gailhard, J.; Garçon, R.

2014-12-01

MORDOR is a conceptual hydrological model extensively used in Électricité de France (EDF, French electric utility company) operational applications: (i) hydrological forecasting, (ii) flood risk assessment, (iii) water balance and (iv) climate change studies. MORDOR is a lumped, reservoir, elevation based model with hourly or daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt and routing. The model has been intensively used at EDF for more than 20 years, in particular for modeling French mountainous watersheds. In the matter of parameters calibration we propose and test alternative multi-criteria techniques based on two specific approaches: automatic calibration using single-objective functions and a priori parameter calibration founded on hydrological watershed features. The automatic calibration approach uses single-objective functions, based on Kling-Gupta efficiency, to quantify the good agreement between the simulated and observed runoff focusing on four different runoff samples: (i) time-series sample, (I) annual hydrological regime, (iii) monthly cumulative distribution functions and (iv) recession sequences.The primary purpose of this study is to analyze the definition and sensitivity of MORDOR parameters testing different calibration techniques in order to: (i) simplify the model structure, (ii) increase the calibration-validation performance of the model and (iii) reduce the equifinality problem of calibration process. We propose an alternative calibration strategy that reaches these goals. The analysis is illustrated by calibrating MORDOR model to daily data for 50 watersheds located in French mountainous regions.

Multi-focus image fusion based on window empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Zheng, Jiaoyue; Hu, Gang; Wang, Jiao

2017-09-01

In order to improve multi-focus image fusion quality, a novel fusion algorithm based on window empirical mode decomposition (WEMD) is proposed. This WEMD is an improved form of bidimensional empirical mode decomposition (BEMD), due to its decomposition process using the adding window principle, effectively resolving the signal concealment problem. We used WEMD for multi-focus image fusion, and formulated different fusion rules for bidimensional intrinsic mode function (BIMF) components and the residue component. For fusion of the BIMF components, the concept of the Sum-modified-Laplacian was used and a scheme based on the visual feature contrast adopted; when choosing the residue coefficients, a pixel value based on the local visibility was selected. We carried out four groups of multi-focus image fusion experiments and compared objective evaluation criteria with other three fusion methods. The experimental results show that the proposed fusion approach is effective and performs better at fusing multi-focus images than some traditional methods.

Scaling issues in multi-criteria evaluation of combinations of measures for integrated river basin management

NASA Astrophysics Data System (ADS)

Dietrich, Jörg

2016-05-01

In integrated river basin management, measures for reaching the environmental objectives can be evaluated at different scales, and according to multiple criteria of different nature (e.g. ecological, economic, social). Decision makers, including responsible authorities and stakeholders, follow different interests regarding criteria and scales. With a bottom up approach, the multi criteria assessment could produce a different outcome than with a top down approach. The first assigns more power to the local community, which is a common principle of IWRM. On the other hand, the development of an overall catchment strategy could potentially make use of synergetic effects of the measures, which fulfils the cost efficiency requirement at the basin scale but compromises local interests. Within a joint research project for the 5500 km2 Werra river basin in central Germany, measures have been planned to reach environmental objectives of the European Water Framework directive (WFD) regarding ecological continuity and nutrient loads. The main criteria for the evaluation of the measures were costs of implementation, reduction of nutrients, ecological benefit and social acceptance. The multi-criteria evaluation of the catchment strategies showed compensation between positive and negative performance of criteria within the catchment, which in the end reduced the discriminative power of the different strategies. Furthermore, benefit criteria are partially computed for the whole basin only. Both ecological continuity and nutrient load show upstream-downstream effects in opposite direction. The principles of "polluter pays" and "overall cost efficiency" can be followed for the reduction of nutrient losses when financial compensations between upstream and downstream users are made, similar to concepts of emission trading.

Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation

NASA Astrophysics Data System (ADS)

Sakamoto, M.; Honda, Y.; Kondo, A.

2016-06-01

From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.

Determination of criteria weights in solving multi-criteria problems

NASA Astrophysics Data System (ADS)

Kasim, Maznah Mat

2014-12-01

A multi-criteria (MC) problem comprises of units to be analyzed under a set of evaluation criteria. Solving a MC problem is basically the process of finding the overall performance or overall quality of the units of analysis by using certain aggregation method. Based on these overall measures of each unit, a decision can be made whether to sort them, to select the best or to group them according to certain ranges. Prior to solving the MC problems, the weights of the related criteria have to be determined with the assumption that the weights represent the degree of importance or the degree of contribution towards the overall performance of the units. This paper presents two main approaches which are called as subjective and objective approaches, where the first one involves evaluator(s) while the latter approach depends on the intrinsic information contained in each criterion. The subjective and objective weights are defined if the criteria are assumed to be independent with each other, but if they are dependent, there is another type of weight, which is called as monotone measure weight or compound weights which represent degree of interaction among the criteria. The measure of individual weights or compound weights must be addressed in solving multi-criteria problems so that the solutions are more reliable since in the real world, evaluation criteria always come with different degree of importance or are dependent with each other. As the real MC problems have their own uniqueness, it is up to the decision maker(s) to decide which type of weights and which method are the most applicable ones for the problem under study.

A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Lund, Jay R.

2011-05-01

Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average.

PubMed

Gorsevski, Pece V; Donevska, Katerina R; Mitrovski, Cvetko D; Frizado, Joseph P

2012-02-01

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Solving multi-objective optimization problems in conservation with the reference point method

PubMed Central

Dujardin, Yann; Chadès, Iadine

2018-01-01

Managing the biodiversity extinction crisis requires wise decision-making processes able to account for the limited resources available. In most decision problems in conservation biology, several conflicting objectives have to be taken into account. Most methods used in conservation either provide suboptimal solutions or use strong assumptions about the decision-maker’s preferences. Our paper reviews some of the existing approaches to solve multi-objective decision problems and presents new multi-objective linear programming formulations of two multi-objective optimization problems in conservation, allowing the use of a reference point approach. Reference point approaches solve multi-objective optimization problems by interactively representing the preferences of the decision-maker with a point in the criteria (objectives) space, called the reference point. We modelled and solved the following two problems in conservation: a dynamic multi-species management problem under uncertainty and a spatial allocation resource management problem. Results show that the reference point method outperforms classic methods while illustrating the use of an interactive methodology for solving combinatorial problems with multiple objectives. The method is general and can be adapted to a wide range of ecological combinatorial problems. PMID:29293650

Using MOEA with Redistribution and Consensus Branches to Infer Phylogenies.

PubMed

Min, Xiaoping; Zhang, Mouzhao; Yuan, Sisi; Ge, Shengxiang; Liu, Xiangrong; Zeng, Xiangxiang; Xia, Ningshao

2017-12-26

In recent years, to infer phylogenies, which are NP-hard problems, more and more research has focused on using metaheuristics. Maximum Parsimony and Maximum Likelihood are two effective ways to conduct inference. Based on these methods, which can also be considered as the optimal criteria for phylogenies, various kinds of multi-objective metaheuristics have been used to reconstruct phylogenies. However, combining these two time-consuming methods results in those multi-objective metaheuristics being slower than a single objective. Therefore, we propose a novel, multi-objective optimization algorithm, MOEA-RC, to accelerate the processes of rebuilding phylogenies using structural information of elites in current populations. We compare MOEA-RC with two representative multi-objective algorithms, MOEA/D and NAGA-II, and a non-consensus version of MOEA-RC on three real-world datasets. The result is, within a given number of iterations, MOEA-RC achieves better solutions than the other algorithms.

Digital fabrication of multi-material biomedical objects.

PubMed

Cheung, H H; Choi, S H

2009-12-01

This paper describes a multi-material virtual prototyping (MMVP) system for modelling and digital fabrication of discrete and functionally graded multi-material objects for biomedical applications. The MMVP system consists of a DMMVP module, an FGMVP module and a virtual reality (VR) simulation module. The DMMVP module is used to model discrete multi-material (DMM) objects, while the FGMVP module is for functionally graded multi-material (FGM) objects. The VR simulation module integrates these two modules to perform digital fabrication of multi-material objects, which can be subsequently visualized and analysed in a virtual environment to optimize MMLM processes for fabrication of product prototypes. Using the MMVP system, two biomedical objects, including a DMM human spine and an FGM intervertebral disc spacer are modelled and digitally fabricated for visualization and analysis in a VR environment. These studies show that the MMVP system is a practical tool for modelling, visualization, and subsequent fabrication of biomedical objects of discrete and functionally graded multi-materials for biomedical applications. The system may be adapted to control MMLM machines with appropriate hardware for physical fabrication of biomedical objects.

Optimizing a multi-product closed-loop supply chain using NSGA-II, MOSA, and MOPSO meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Babaveisi, Vahid; Paydar, Mohammad Mahdi; Safaei, Abdul Sattar

2018-07-01

This study aims to discuss the solution methodology for a closed-loop supply chain (CLSC) network that includes the collection of used products as well as distribution of the new products. This supply chain is presented on behalf of the problems that can be solved by the proposed meta-heuristic algorithms. A mathematical model is designed for a CLSC that involves three objective functions of maximizing the profit, minimizing the total risk and shortages of products. Since three objective functions are considered, a multi-objective solution methodology can be advantageous. Therefore, several approaches have been studied and an NSGA-II algorithm is first utilized, and then the results are validated using an MOSA and MOPSO algorithms. Priority-based encoding, which is used in all the algorithms, is the core of the solution computations. To compare the performance of the meta-heuristics, random numerical instances are evaluated by four criteria involving mean ideal distance, spread of non-dominance solution, the number of Pareto solutions, and CPU time. In order to enhance the performance of the algorithms, Taguchi method is used for parameter tuning. Finally, sensitivity analyses are performed and the computational results are presented based on the sensitivity analyses in parameter tuning.

Optimizing a multi-product closed-loop supply chain using NSGA-II, MOSA, and MOPSO meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Babaveisi, Vahid; Paydar, Mohammad Mahdi; Safaei, Abdul Sattar

2017-07-01

This study aims to discuss the solution methodology for a closed-loop supply chain (CLSC) network that includes the collection of used products as well as distribution of the new products. This supply chain is presented on behalf of the problems that can be solved by the proposed meta-heuristic algorithms. A mathematical model is designed for a CLSC that involves three objective functions of maximizing the profit, minimizing the total risk and shortages of products. Since three objective functions are considered, a multi-objective solution methodology can be advantageous. Therefore, several approaches have been studied and an NSGA-II algorithm is first utilized, and then the results are validated using an MOSA and MOPSO algorithms. Priority-based encoding, which is used in all the algorithms, is the core of the solution computations. To compare the performance of the meta-heuristics, random numerical instances are evaluated by four criteria involving mean ideal distance, spread of non-dominance solution, the number of Pareto solutions, and CPU time. In order to enhance the performance of the algorithms, Taguchi method is used for parameter tuning. Finally, sensitivity analyses are performed and the computational results are presented based on the sensitivity analyses in parameter tuning.

Defining how aging Pseudotsuga and Abies compensate for multiple stresses through multi-criteria assessment of a functional-structural model

Treesearch

Maureen C. Kennedy; E. David Ford; Thomas M. Hinckley

2009-01-01

Many hypotheses have been advanced about factors that control tree longevity. We use a simulation model with multi-criteria optimization and Pareto optimality to determine branch morphologies in the Pinaceae that minimize the effect of growth limitations due to water stress while simultaneously maximizing carbohydrate gain. Two distinct branch morphologies in the...

Multi criteria evaluation for universal soil loss equation based on geographic information system

NASA Astrophysics Data System (ADS)

Purwaamijaya, I. M.

2018-05-01

The purpose of this research were to produce(l) a conceptual, functional model designed and implementation for universal soil loss equation (usle), (2) standard operational procedure for multi criteria evaluation of universal soil loss equation (usle) using geographic information system, (3) overlay land cover, slope, soil and rain fall layers to gain universal soil loss equation (usle) using multi criteria evaluation, (4) thematic map of universal soil loss equation (usle) in watershed, (5) attribute table of universal soil loss equation (usle) in watershed. Descriptive and formal correlation methods are used for this research. Cikapundung Watershed, Bandung, West Java, Indonesia was study location. This research was conducted on January 2016 to May 2016. A spatial analysis is used to superimposed land cover, slope, soil and rain layers become universal soil loss equation (usle). Multi criteria evaluation for universal soil loss equation (usle) using geographic information system could be used for conservation program.

Multi-criteria assessment of community-based fluoride-removal technologies for rural Ethiopia.

PubMed

Osterwalder, Lars; Johnson, C Annette; Yang, Hong; Johnston, Richard B

2014-08-01

Elevated concentrations of naturally-occurring fluoride in groundwater pose a serious health risk to millions of people living in the Ethiopian Rift Valley. In the absence of low-fluoride water resources of sufficient capacity, fluoride removal from drinking water is the accepted mitigation option. To date, five different community-level fluoride-removal technologies have been implemented in Ethiopia, although only a few units have been found in a functional state in the field. Which technology should be promoted and up-scaled is the subject of controversial debate amongst key stakeholders. This paper describes a multi-criteria decision analysis exercise, which was conducted with the participation of stakeholders in Ethiopia during a one-day workshop, to assess in an objective and transparent manner the available technology options. Criteria for technology comparison were selected and weighted, thus enabling the participants to assess the advantages and disadvantages of the different technologies and hear the views of other stakeholders. It was shown that there is no single most-preferable, technical solution for fluoride removal in Ethiopia. Selection of the most suitable solution depends on location-specific parameters and on the relative importance given to different criteria by the stakeholders involved. The data presented in this paper can be used as reference values for Ethiopia. © 2013. Published by Elsevier B.V. All rights reserved.

A fuzzy MCDM model with objective and subjective weights for evaluating service quality in hotel industries

NASA Astrophysics Data System (ADS)

Zoraghi, Nima; Amiri, Maghsoud; Talebi, Golnaz; Zowghi, Mahdi

2013-12-01

This paper presents a fuzzy multi-criteria decision-making (FMCDM) model by integrating both subjective and objective weights for ranking and evaluating the service quality in hotels. The objective method selects weights of criteria through mathematical calculation, while the subjective method uses judgments of decision makers. In this paper, we use a combination of weights obtained by both approaches in evaluating service quality in hotel industries. A real case study that considered ranking five hotels is illustrated. Examples are shown to indicate capabilities of the proposed method.

Novel Approach to Facilitating Tradeoff Multi-Objective Grouping Optimization

ERIC Educational Resources Information Center

Lin, Yu-Shih; Chang, Yi-Chun; Chu, Chih-Ping

2016-01-01

The grouping problem is critical in collaborative learning (CL) because of the complexity and difficulty in adequate grouping, based on various grouping criteria and numerous learners. Previous studies have paid attention to certain research questions, and the consideration for a number of learner characteristics has arisen. Such a multi-objective…

Gender approaches to evolutionary multi-objective optimization using pre-selection of criteria

NASA Astrophysics Data System (ADS)

Kowalczuk, Zdzisław; Białaszewski, Tomasz

2018-01-01

A novel idea to perform evolutionary computations (ECs) for solving highly dimensional multi-objective optimization (MOO) problems is proposed. Following the general idea of evolution, it is proposed that information about gender is used to distinguish between various groups of objectives and identify the (aggregate) nature of optimality of individuals (solutions). This identification is drawn out of the fitness of individuals and applied during parental crossover in the processes of evolutionary multi-objective optimization (EMOO). The article introduces the principles of the genetic-gender approach (GGA) and virtual gender approach (VGA), which are not just evolutionary techniques, but constitute a completely new rule (philosophy) for use in solving MOO tasks. The proposed approaches are validated against principal representatives of the EMOO algorithms of the state of the art in solving benchmark problems in the light of recognized EC performance criteria. The research shows the superiority of the gender approach in terms of effectiveness, reliability, transparency, intelligibility and MOO problem simplification, resulting in the great usefulness and practicability of GGA and VGA. Moreover, an important feature of GGA and VGA is that they alleviate the 'curse' of dimensionality typical of many engineering designs.

The multi-criteria optimization for the formation of the multiple-valued logic model of a robotic agent

NASA Astrophysics Data System (ADS)

Bykovsky, A. Yu; Sherbakov, A. A.

2016-08-01

The C-valued Allen-Givone algebra is the attractive tool for modeling of a robotic agent, but it requires the consensus method of minimization for the simplification of logic expressions. This procedure substitutes some undefined states of the function for the maximal truth value, thus extending the initially given truth table. This further creates the problem of different formal representations for the same initially given function. The multi-criteria optimization is proposed for the deliberate choice of undefined states and model formation.

SU-G-BRC-02: A Novel Multi-Criteria Optimization Approach to Generate Deliverable Intensity-Modulated Radiation Therapy (IMRT) Treatment Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirlik, G; D’Souza, W; Zhang, H

2016-06-15

Purpose: To present a novel multi-criteria optimization (MCO) solution approach that generates treatment plans with deliverable apertures using column generation. Methods: We demonstrate our method with 10 locally advanced head-and-neck cancer cases retrospectively. In our MCO formulation, we defined an objective function for each structure in the treatment volume. This resulted in 9 objective functions, including 3 distinct objectives for primary target volume, high-risk and low-risk target volumes, 5 objectives for each of the organs-at-risk (OARs) (two parotid glands, spinal cord, brain stem and oral cavity), and one for the non-target non-OAR normal tissue. Conditional value-at-risk (CVaR) constraints were utilizedmore » to ensure at least certain fraction of the target volumes receiving the prescription doses. To directly generate deliverable plans, column generation algorithm was embedded within our MCO approach for aperture shape generation. Final dose distributions for all plans were generated using a Monte Carlo kernel-superposition dose calculation. We compared the MCO plans with the clinical plans, which were created by clinicians. Results: At least 95% target coverage was achieved by both MCO plans and clinical plans. However, the average conformity indices of clinical plans and the MCO plans were 1.95 and 1.35, respectively (31% reduction, p<0.01). Compared to the conventional clinical plan, the proposed MCO method achieved average reductions in left parotid mean dose of 5% (p=0.06), right parotid mean dose of 18% (p<0.01), oral cavity mean dose of 21% (p=0.03), spinal cord maximum dose of 20% (p<0.01), brain stem maximum dose of 61% (p<0.01), and normal tissue maximum dose of 5% (p<0.01), respectively. Conclusion: We demonstrated that the proposed MCO method was able to obtain deliverable IMRT treatment plans while achieving significant improvements in dosimetric plan quality.« less

Minimizing impacts of land use change on ecosystem services using multi-criteria heuristic analysis.

PubMed

Keller, Arturo A; Fournier, Eric; Fox, Jessica

2015-06-01

Development of natural landscapes to support human activities impacts the capacity of the landscape to provide ecosystem services. Typically, several ecosystem services are impacted at a single development site and various footprint scenarios are possible, thus a multi-criteria analysis is needed. Restoration potential should also be considered for the area surrounding the permanent impact site. The primary objective of this research was to develop a heuristic approach to analyze multiple criteria (e.g. impacts to various ecosystem services) in a spatial configuration with many potential development sites. The approach was to: (1) quantify the magnitude of terrestrial ecosystem service (biodiversity, carbon sequestration, nutrient and sediment retention, and pollination) impacts associated with a suite of land use change scenarios using the InVEST model; (2) normalize results across categories of ecosystem services to allow cross-service comparison; (3) apply the multi-criteria heuristic algorithm to select sites with the least impact to ecosystem services, including a spatial criterion (separation between sites). As a case study, the multi-criteria impact minimization algorithm was applied to InVEST output to select 25 potential development sites out of 204 possible locations (selected by other criteria) within a 24,000 ha property. This study advanced a generally applicable spatial multi-criteria approach for 1) considering many land use footprint scenarios, 2) balancing impact decisions across a suite of ecosystem services, and 3) determining the restoration potential of ecosystem services after impacts. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

PubMed Central

2010-01-01

Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters. PMID:21034451

Fuzzy Logic Approaches to Multi-Objective Decision-Making in Aerospace Applications

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1994-01-01

Fuzzy logic allows for the quantitative representation of multi-objective decision-making problems which have vague or fuzzy objectives and parameters. As such, fuzzy logic approaches are well-suited to situations where alternatives must be assessed by using criteria that are subjective and of unequal importance. This paper presents an overview of fuzzy logic and provides sample applications from the aerospace industry. Applications include an evaluation of vendor proposals, an analysis of future space vehicle options, and the selection of a future space propulsion system. On the basis of the results provided in this study, fuzzy logic provides a unique perspective on the decision-making process, allowing the evaluator to assess the degree to which each option meets the evaluation criteria. Future decision-making should take full advantage of fuzzy logic methods to complement existing approaches in the selection of alternatives.

Evaluation of purchase intention of customers in two wheeler automobile segment: AHP and TOPSIS

NASA Astrophysics Data System (ADS)

Sri Yogi, Kottala

2018-03-01

Winning heart of customers is preeminent main design of any business organization in global business environment. This paper explored customer’s priorities while purchasing a two wheeler automobile segment using Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as a multi criteria decision making tools to accomplish the research objectives. Study has been done to analyze different criteria to be considered during purchasing of two wheeler automobiles among respondents using structured questionnaire based on SAATY scale. Based on our previous work on empirical & fuzzy logic approach to product quality and purchase intention of customers in two wheeler- operational, performance, economic, brand value and maintenance aspects are considered as decision criteria of customers while purchasing a two wheeler. The study suggests high pick up during overtaking, petrol saving, reasonable spare parts price, unique in design and identity and easy to change gear as main criterion in purchasing process. We also found some leading two wheeler automobiles models available in Indian market using some objective function criterion in choosing some important characteristics like price, cylinder capacity, brake horse power and weight during purchasing process of two wheeler automobile in Indian market based on respondents perception.

Multi-objective shape optimization of plate structure under stress criteria based on sub-structured mixed FEM and genetic algorithms

NASA Astrophysics Data System (ADS)

Garambois, Pierre; Besset, Sebastien; Jézéquel, Louis

2015-07-01

This paper presents a methodology for the multi-objective (MO) shape optimization of plate structure under stress criteria, based on a mixed Finite Element Model (FEM) enhanced with a sub-structuring method. The optimization is performed with a classical Genetic Algorithm (GA) method based on Pareto-optimal solutions and considers thickness distributions parameters and antagonist objectives among them stress criteria. We implement a displacement-stress Dynamic Mixed FEM (DM-FEM) for plate structure vibrations analysis. Such a model gives a privileged access to the stress within the plate structure compared to primal classical FEM, and features a linear dependence to the thickness parameters. A sub-structuring reduction method is also computed in order to reduce the size of the mixed FEM and split the given structure into smaller ones with their own thickness parameters. Those methods combined enable a fast and stress-wise efficient structure analysis, and improve the performance of the repetitive GA. A few cases of minimizing the mass and the maximum Von Mises stress within a plate structure under a dynamic load put forward the relevance of our method with promising results. It is able to satisfy multiple damage criteria with different thickness distributions, and use a smaller FEM.

Development of a multi-criteria evaluation system to assess growing pig welfare.

PubMed

Martín, P; Traulsen, I; Buxadé, C; Krieter, J

2017-03-01

The aim of this paper was to present an alternative multi-criteria evaluation model to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. The WQ assessment protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first step of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion. The utility functions and the aggregation function were constructed in two separated steps. The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) method was used for utility function determination and the Choquet Integral (CI) was used as an aggregation operator. The WQ decision-makers' preferences were fitted in order to construct the utility functions and to determine the CI parameters. The methods were tested with generated data sets for farms of growing pigs. Using the MAUT, similar results were obtained to the ones obtained applying the WQ protocol aggregation methods. It can be concluded that due to the use of an interactive approach such as MACBETH, this alternative methodology is more transparent and more flexible than the methodology proposed by WQ, which allows the possibility to modify the model according, for instance, to new scientific knowledge.

Riparian rehabilitation planning in an urban-rural gradient: Integrating social needs and ecological conditions.

PubMed

Guida-Johnson, Bárbara; Zuleta, Gustavo A

2017-09-01

In the present context of global change and search for sustainability, we detected a gap between restoration and society: local communities are usually only considered as threats or disturbances when planning for restoration. To bridge this gap, we propose a landscape design framework for planning riparian rehabilitation in an urban-rural gradient. A spatial multi-criteria analysis was used to assess the priority of riversides by considering two rehabilitation objectives simultaneously-socio-environmental and ecological-and two sets of criteria were designed according to these objectives. The assessment made it possible to identify 17 priority sites for riparian rehabilitation that were associated with different conditions along the gradient. The double goal setting enabled a dual consideration of citizens, both as beneficiaries and potential impacts to rehabilitation, and the criteria selected incorporated the multi-dimensional nature of the environment. This approach can potentially be adapted and implemented in any other anthropic-natural interface throughout the world.

Proposed method to construct Boolean functions with maximum possible annihilator immunity

NASA Astrophysics Data System (ADS)

Goyal, Rajni; Panigrahi, Anupama; Bansal, Rohit

2017-07-01

Nonlinearity and Algebraic(annihilator) immunity are two core properties of a Boolean function because optimum values of Annihilator Immunity and nonlinearity are required to resist fast algebraic attack and differential cryptanalysis respectively. For a secure cypher system, Boolean function(S-Boxes) should resist maximum number of attacks. It is possible if a Boolean function has optimal trade-off among its properties. Before constructing Boolean functions, we fixed the criteria of our constructions based on its properties. In present work, our construction is based on annihilator immunity and nonlinearity. While keeping above facts in mind,, we have developed a multi-objective evolutionary approach based on NSGA-II and got the optimum value of annihilator immunity with good bound of nonlinearity. We have constructed balanced Boolean functions having the best trade-off among balancedness, Annihilator immunity and nonlinearity for 5, 6 and 7 variables by the proposed method.

Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis

NASA Astrophysics Data System (ADS)

Karlsson, Caroline S. J.; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve W.

2017-11-01

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis.

PubMed

Karlsson, Caroline S J; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve W

2017-11-01

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

Establishing politically feasible water markets: a multi-criteria approach.

PubMed

Ballestero, Enrique; Alarcón, Silverio; García-Bernabeu, Ana

2002-08-01

A multiple criteria decision-making (MCDM) model to simulate the establishment of water markets is developed. The environment is an irrigated area governed by a non-profit agency, which is responsible for water production, allocation, and pricing. There is a traditional situation of historical rights, average-cost pricing for water allocation, large quantities of water used, and inefficiency. A market-oriented policy could be implemented by accounting for ecological and political objectives such as saving groundwater and safeguarding historical rights while promoting economic efficiency. In this paper, a problem is solved by compromise programming, a multi-criteria technique based on the principles of Simonian logic. The model is theoretically developed and applied to the Lorca region in Spain near the Mediterranean Sea.

Carbon storage, timber production, and biodiversity: comparing ecosystem services with multi-criteria decision analysis

USGS Publications Warehouse

Schwenk, W. Scott; Donovan, Therese; Keeton, William S.; Nunery, Jared S.

2012-01-01

Increasingly, land managers seek ways to manage forests for multiple ecosystem services and functions, yet considerable challenges exist in comparing disparate services and balancing trade-offs among them. We applied multi-criteria decision analysis (MCDA) and forest simulation models to simultaneously consider three objectives: (1) storing carbon, (2) producing timber and wood products, and (3) sustaining biodiversity. We used the Forest Vegetation Simulator (FVS) applied to 42 northern hardwood sites to simulate forest development over 100 years and to estimate carbon storage and timber production. We estimated biodiversity implications with occupancy models for 51 terrestrial bird species that were linked to FVS outputs. We simulated four alternative management prescriptions that spanned a range of harvesting intensities and forest structure retention. We found that silvicultural approaches emphasizing less frequent harvesting and greater structural retention could be expected to achieve the greatest net carbon storage but also produce less timber. More intensive prescriptions would enhance biodiversity because positive responses of early successional species exceeded negative responses of late successional species within the heavily forested study area. The combinations of weights assigned to objectives had a large influence on which prescriptions were scored as optimal. Overall, we found that a diversity of silvicultural approaches is likely to be preferable to any single approach, emphasizing the need for landscape-scale management to provide a full range of ecosystem goods and services. Our analytical framework that combined MCDA with forest simulation modeling was a powerful tool in understanding trade-offs among management objectives and how they can be simultaneously accommodated.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Convex reformulation of biologically-based multi-criteria intensity-modulated radiation therapy optimization including fractionation effects

NASA Astrophysics Data System (ADS)

Hoffmann, Aswin L.; den Hertog, Dick; Siem, Alex Y. D.; Kaanders, Johannes H. A. M.; Huizenga, Henk

2008-11-01

Finding fluence maps for intensity-modulated radiation therapy (IMRT) can be formulated as a multi-criteria optimization problem for which Pareto optimal treatment plans exist. To account for the dose-per-fraction effect of fractionated IMRT, it is desirable to exploit radiobiological treatment plan evaluation criteria based on the linear-quadratic (LQ) cell survival model as a means to balance the radiation benefits and risks in terms of biologic response. Unfortunately, the LQ-model-based radiobiological criteria are nonconvex functions, which make the optimization problem hard to solve. We apply the framework proposed by Romeijn et al (2004 Phys. Med. Biol. 49 1991-2013) to find transformations of LQ-model-based radiobiological functions and establish conditions under which transformed functions result in equivalent convex criteria that do not change the set of Pareto optimal treatment plans. The functions analysed are: the LQ-Poisson-based model for tumour control probability (TCP) with and without inter-patient heterogeneity in radiation sensitivity, the LQ-Poisson-based relative seriality s-model for normal tissue complication probability (NTCP), the equivalent uniform dose (EUD) under the LQ-Poisson model and the fractionation-corrected Probit-based model for NTCP according to Lyman, Kutcher and Burman. These functions differ from those analysed before in that they cannot be decomposed into elementary EUD or generalized-EUD functions. In addition, we show that applying increasing and concave transformations to the convexified functions is beneficial for the piecewise approximation of the Pareto efficient frontier.

Evaluating the accuracy of self-report for the diagnosis of HIV-associated neurocognitive disorder (HAND): defining “symptomatic” versus “asymptomatic” HAND

PubMed Central

Obermeit, Lisa C.; Beltran, Jessica; Casaletto, Kaitlin B.; Franklin, Donald R.; Letendre, Scott; Ellis, Ronald; Fennema-Notestine, Christine; Vaida, Florin; Collier, Ann C.; Marra, Christina M.; Clifford, David; Gelman, Benjamin; Sacktor, Ned; Morgello, Susan; Simpson, David; McCutchan, J. Allen; Grant, Igor

2016-01-01

The criteria for differentiating symptomatic from asymptomatic HIV-associated neurocognitive disorder require evaluation of (1) cognitive impairment, (2) daily functioning declines, and (3) whether the functional declines are attributable to cognitive versus physical problems. Many providers rely only on self-report to evaluate these latter criteria. However, the accuracy of patient-provided information may be limited. This study evaluated the validity of self-assessment for HIV-associated neurocognitive disorder (HAND) diagnoses by comparing objective findings with self-report of criteria 2 and 3 above. Self-reports were used to stratify 277 cognitively impaired HIV+ individuals into functionally dependent (n = 159) and independent (n = 118) groups, followed by group comparisons of objective functional problems. The dependent group was then divided into those who self-attributed their functional dependence to only cognitive (n = 80) versus only physical (n = 79) causes, for further comparisons on objective findings. The functionally dependent group was significantly worse than the independent group on all objective disability characteristics except severity of cognitive impairment, while those who attributed their dependence to physical (versus cognitive) factors were similar on all objective physical, cognitive, and functioning variables. Of note, 28 % of physical attributors showed no physical abnormalities on neuromedical examinations. Results suggest that patient report is consistently associated with objective measures of functional loss; in contrast, patient identification of physical versus cognitive causes is poorly associated with objective criteria. These findings caution against relying solely on patient self-report to determine whether functional disability in cognitively impaired HIV+ individuals can be attributed to strictly physical causes. PMID:27557777

A Multi-criteria Decision Analysis System for Prioritizing Sites and Types of Low Impact Development Practices

NASA Astrophysics Data System (ADS)

Song, Jae Yeol; Chung, Eun-Sung

2017-04-01

This study developed a multi-criteria decision analysis framework to prioritize sites and types of low impact development (LID) practices. This framework was systemized as a web-based system coupled with the Storm Water Management Model (SWMM) from the Environmental Protection Agency (EPA). Using the technique for order of preference by similarity to ideal solution (TOPSIS), which is a type of multi-criteria decision-making (MCDM) method, multiple types and sites of designated LID practices are prioritized. This system is named the Water Management Prioritization Module (WMPM) and is an improved version of the Water Management Analysis Module (WMAM) that automatically generates and simulates multiple scenarios of LID design and planning parameters for a single LID type. WMPM can simultaneously determine the priority of multiple LID types and sites. In this study, an infiltration trench and permeable pavement were considered for multiple sub-catchments in South Korea to demonstrate the WMPM procedures. The TOPSIS method was manually incorporated to select the vulnerable target sub-catchments and to prioritize the LID planning scenarios for multiple types and sites considering socio-economic, hydrologic and physical-geometric factors. In this application, the Delphi method and entropy theory were used to determine the subjective and objective weights, respectively. Comparing the ranks derived by this system, two sub-catchments, S16 and S4, out of 18 were considered to be the most suitable places for installing an infiltration trench and porous pavement to reduce the peak and total flow, respectively, considering both socio-economic factors and hydrological effectiveness. WMPM can help policy-makers to objectively develop urban water plans for sustainable development. Keywords: Low Impact Development, Multi-Criteria Decision Analysis, SWMM, TOPSIS, Water Management Prioritization Module (WMPM)

THE MULTI-WAVELENGTH EXTREME STARBURST SAMPLE OF LUMINOUS GALAXIES. I. SAMPLE CHARACTERISTICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laag, Edward; Croft, Steve; Canalizo, Gabriela

2010-12-15

This paper introduces the Multi-wavelength Extreme Starburst Sample (MESS), a new catalog of 138 star-forming galaxies (0.1 < z < 0.3) optically selected from the Sloan Digital Sky Survey using emission line strength diagnostics to have a high absolute star formation rate (SFR; minimum 11 M{sub sun} yr{sup -1} with median SFR {approx} 61 M{sub sun} yr{sup -1} based on a Kroupa initial mass function). The MESS was designed to complement samples of nearby star-forming galaxies such as the luminous infrared galaxies (LIRGs) and ultraviolet luminous galaxies (UVLGs). Observations using the Multi-band Imaging Photometer (24, 70, and 160 {mu}m channels)more » on the Spitzer Space Telescope indicate that the MESS galaxies have IR luminosities similar to those of LIRGs, with an estimated median L{sub TIR} {approx} 3 x 10{sup 11} L{sub sun}. The selection criteria for the MESS objects suggest they may be less obscured than typical far-IR-selected galaxies with similar estimated SFRs. Twenty out of 70 of the MESS objects detected in the Galaxy Evolution Explorer FUV band also appear to be UVLGs. We estimate the SFRs based directly on luminosities to determine the agreement for these methods in the MESS. We compare these estimates to the emission line strength technique, since the effective measurement of dust attenuation plays a central role in these methods. We apply an image stacking technique to the Very Large Array FIRST survey radio data to retrieve 1.4 GHz luminosity information for 3/4 of the sample covered by FIRST including sources too faint, and at too high a redshift, to be detected in FIRST. We also discuss the relationship between the MESS objects and samples selected through alternative criteria. Morphologies will be the subject of a forthcoming paper.« less

Multi-Function Displays: A Guide for Human Factors Evaluation

DTIC Science & Technology

2013-11-01

mental workload in rotary wing aircraft . Ergonomics , 36, 1121 - 40. Smith, S., & Mosier, J. (1984). Design guidelines for the user interface for...Monterey Technologies, Inc., except one designated by (*), who is from CAMI. 16. Abstract This guide is designed to assist aircraft ...section. 17. Key Words 18. Distribution Statement Multi-Function Displays, Display Design , Avionics, Human Factors Criteria, Aircraft

Behavior analysis of video object in complicated background

NASA Astrophysics Data System (ADS)

Zhao, Wenting; Wang, Shigang; Liang, Chao; Wu, Wei; Lu, Yang

2016-10-01

This paper aims to achieve robust behavior recognition of video object in complicated background. Features of the video object are described and modeled according to the depth information of three-dimensional video. Multi-dimensional eigen vector are constructed and used to process high-dimensional data. Stable object tracing in complex scenes can be achieved with multi-feature based behavior analysis, so as to obtain the motion trail. Subsequently, effective behavior recognition of video object is obtained according to the decision criteria. What's more, the real-time of algorithms and accuracy of analysis are both improved greatly. The theory and method on the behavior analysis of video object in reality scenes put forward by this project have broad application prospect and important practical significance in the security, terrorism, military and many other fields.

Multi-Criteria Decision-Making Methods and Their Applications for Human Resources

NASA Astrophysics Data System (ADS)

D'Urso, M. G.; Masi, D.

2015-05-01

Both within the formation field and the labor market Multi-Criteria Decision Methods (MCDM) provide a significant support to the management of human resources in which the best choice among several alternatives can be very complex. This contribution addresses fuzzy logic in multi-criteria decision techniques since they have several applications in the management of human resources with the advantage of ruling out mistakes due to the subjectivity of the person in charge of making a choice. Evaluating educational achievements as well as the professional profile of a technician more suitable for a job in a firm, industry or a professional office are valuable examples of fuzzy logic. For all of the previous issues subjectivity is a fundamental aspect so that fuzzy logic, due to the very meaning of the word fuzzy, should be the preferred choice. However, this is not sufficient to justify its use; fuzzy technique has to make the system of evaluation and choice more effective and objective. The methodological structure of the multi-criteria fuzzy criterion is hierarchic and allows one to select the best alternatives in all those cases in which several alternatives are possible; thus, the optimal choice can be achieved by analyzing the different scopes of each criterion and sub-criterion as well as the relevant weights.

a Heuristic Approach for Multi Objective Distribution Feeder Reconfiguration: Using Fuzzy Sets in Normalization of Objective Functions

NASA Astrophysics Data System (ADS)

Milani, Armin Ebrahimi; Haghifam, Mahmood Reza

2008-10-01

The reconfiguration is an operation process used for optimization with specific objectives by means of changing the status of switches in a distribution network. In this paper each objectives is normalized with inspiration from fuzzy sets-to cause optimization more flexible- and formulized as a unique multi-objective function. The genetic algorithm is used for solving the suggested model, in which there is no risk of non-liner objective functions and constraints. The effectiveness of the proposed method is demonstrated through the examples.

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.

PubMed

Ceberio, Josu; Calvo, Borja; Mendiburu, Alexander; Lozano, Jose A

2018-02-15

In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. In this sense, a number of papers have proposed multi-objectivising single-objective problems in order to use multi-objective algorithms in their optimisation. In this article, we follow up this idea by presenting a methodology for multi-objectivising combinatorial optimisation problems based on elementary landscape decompositions of their objective function. Under this framework, each of the elementary landscapes obtained from the decomposition is considered as an independent objective function to optimise. In order to illustrate this general methodology, we consider four problems from different domains: the quadratic assignment problem and the linear ordering problem (permutation domain), the 0-1 unconstrained quadratic optimisation problem (binary domain), and the frequency assignment problem (integer domain). We implemented two widely known multi-objective algorithms, NSGA-II and SPEA2, and compared their performance with that of a single-objective GA. The experiments conducted on a large benchmark of instances of the four problems show that the multi-objective algorithms clearly outperform the single-objective approaches. Furthermore, a discussion on the results suggests that the multi-objective space generated by this decomposition enhances the exploration ability, thus permitting NSGA-II and SPEA2 to obtain better results in the majority of the tested instances.

Application of multi-objective nonlinear optimization technique for coordinated ramp-metering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haj Salem, Habib; Farhi, Nadir; Lebacque, Jean Patrick, E-mail: abib.haj-salem@ifsttar.fr, E-mail: nadir.frahi@ifsttar.fr, E-mail: jean-patrick.lebacque@ifsttar.fr

2015-03-10

This paper aims at developing a multi-objective nonlinear optimization algorithm applied to coordinated motorway ramp metering. The multi-objective function includes two components: traffic and safety. Off-line simulation studies were performed on A4 France Motorway including 4 on-ramps.

Possibility-induced simplified neutrosophic aggregation operators and their application to multi-criteria group decision-making

NASA Astrophysics Data System (ADS)

Şahin, Rıdvan; Liu, Peide

2017-07-01

Simplified neutrosophic set (SNS) is an appropriate tool used to express the incompleteness, indeterminacy and uncertainty of the evaluation objects in decision-making process. In this study, we define the concept of possibility SNS including two types of information such as the neutrosophic performance provided from the evaluation objects and its possibility degree using a value ranging from zero to one. Then by extending the existing neutrosophic information, aggregation models for SNSs that cannot be used effectively to fusion the two different information described above, we propose two novel neutrosophic aggregation operators considering possibility, which are named as a possibility-induced simplified neutrosophic weighted arithmetic averaging operator and possibility-induced simplified neutrosophic weighted geometric averaging operator, and discuss their properties. Moreover, we develop a useful method based on the proposed aggregation operators for solving a multi-criteria group decision-making problem with the possibility simplified neutrosophic information, in which the weights of decision-makers and decision criteria are calculated based on entropy measure. Finally, a practical example is utilised to show the practicality and effectiveness of the proposed method.

Multi-criteria analysis of potential recovery facilities in a reverse supply chain

NASA Astrophysics Data System (ADS)

Nukala, Satish; Gupta, Surendra M.

2005-11-01

Analytic Hierarchy Process (AHP) has been employed by researchers for solving multi-criteria analysis problems. However, AHP is often criticized for its unbalanced scale of judgments and failure to precisely handle the inherent uncertainty and vagueness in carrying out the pair-wise comparisons. With an objective to address these drawbacks, in this paper, we employ a fuzzy approach in selecting potential recovery facilities in the strategic planning of a reverse supply chain network that addresses the decision maker's level of confidence in the fuzzy assessments and his/her attitude towards risk. A numerical example is considered to illustrate the methodology.

Intelligent Support System of Steel Technical Preparation in an Arc Furnace: Functional Scheme of Interactive Builder of the Multi Objective Optimization Problem

NASA Astrophysics Data System (ADS)

Logunova, O. S.; Sibileva, N. S.

2017-12-01

The purpose of the study is to increase the efficiency of the steelmaking process in large capacity arc furnace on the basis of implementation a new decision-making system about the composition of charge materials. The authors proposed an interactive builder for the formation of the optimization problem, taking into account the requirements of the customer, normative documents and stocks of charge materials in the warehouse. To implement the interactive builder, the sets of deterministic and stochastic model components are developed, as well as a list of preferences of criteria and constraints.

A Mission Planning Approach for Precision Farming Systems Based on Multi-Objective Optimization.

PubMed

Zhai, Zhaoyu; Martínez Ortega, José-Fernán; Lucas Martínez, Néstor; Rodríguez-Molina, Jesús

2018-06-02

As the demand for food grows continuously, intelligent agriculture has drawn much attention due to its capability of producing great quantities of food efficiently. The main purpose of intelligent agriculture is to plan agricultural missions properly and use limited resources reasonably with minor human intervention. This paper proposes a Precision Farming System (PFS) as a Multi-Agent System (MAS). Components of PFS are treated as agents with different functionalities. These agents could form several coalitions to complete the complex agricultural missions cooperatively. In PFS, mission planning should consider several criteria, like expected benefit, energy consumption or equipment loss. Hence, mission planning could be treated as a Multi-objective Optimization Problem (MOP). In order to solve MOP, an improved algorithm, MP-PSOGA, is proposed, taking advantages of the Genetic Algorithms and Particle Swarm Optimization. A simulation, called precise pesticide spraying mission, is performed to verify the feasibility of the proposed approach. Simulation results illustrate that the proposed approach works properly. This approach enables the PFS to plan missions and allocate scarce resources efficiently. The theoretical analysis and simulation is a good foundation for the future study. Once the proposed approach is applied to a real scenario, it is expected to bring significant economic improvement.

Variance approach for multi-objective linear programming with fuzzy random of objective function coefficients

NASA Astrophysics Data System (ADS)

Indarsih, Indrati, Ch. Rini

2016-02-01

In this paper, we define variance of the fuzzy random variables through alpha level. We have a theorem that can be used to know that the variance of fuzzy random variables is a fuzzy number. We have a multi-objective linear programming (MOLP) with fuzzy random of objective function coefficients. We will solve the problem by variance approach. The approach transform the MOLP with fuzzy random of objective function coefficients into MOLP with fuzzy of objective function coefficients. By weighted methods, we have linear programming with fuzzy coefficients and we solve by simplex method for fuzzy linear programming.

Evaluation of stormwater harvesting sites using multi criteria decision methodology

NASA Astrophysics Data System (ADS)

Inamdar, P. M.; Sharma, A. K.; Cook, Stephen; Perera, B. J. C.

2018-07-01

Selection of suitable urban stormwater harvesting sites and associated project planning are often complex due to spatial, temporal, economic, environmental and social factors, and related various other variables. This paper is aimed at developing a comprehensive methodology framework for evaluating of stormwater harvesting sites in urban areas using Multi Criteria Decision Analysis (MCDA). At the first phase, framework selects potential stormwater harvesting (SWH) sites using spatial characteristics in a GIS environment. In second phase, MCDA methodology is used for evaluating and ranking of SWH sites in multi-objective and multi-stakeholder environment. The paper briefly describes first phase of framework and focuses chiefly on the second phase of framework. The application of the methodology is also demonstrated over a case study comprising of the local government area, City of Melbourne (CoM), Australia for the benefit of wider water professionals engaged in this area. Nine performance measures (PMs) were identified to characterise the objectives and system performance related to the eight alternative SWH sites for the demonstration of the application of developed methodology. To reflect the stakeholder interests in the current study, four stakeholder participant groups were identified, namely, water authorities (WA), academics (AC), consultants (CS), and councils (CL). The decision analysis methodology broadly consisted of deriving PROMETHEE II rankings of eight alternative SWH sites in the CoM case study, under two distinct group decision making scenarios. The major innovation of this work is the development and application of comprehensive methodology framework that assists in the selection of potential sites for SWH, and facilitates the ranking in multi-objective and multi-stakeholder environment. It is expected that the proposed methodology will assist the water professionals and managers with better knowledge that will reduce the subjectivity in the selection and evaluation of SWH sites.

Integrating LANDIS model and a multi-criteria decision-making approach to evaluate cumulative effects of forest management in the Missouri Ozarks, USA

Treesearch

Zong Bo Shang; Hong S. He; Weimin Xi; Stephen R. Shifley; Brian J. Palik

2012-01-01

Public forest management requires consideration of numerous objectives including protecting ecosystem health, sustaining habitats for native communities, providing sustainable forest products, and providing noncommodity ecosystem services. It is difficult to evaluate the long-term, cumulative effects and tradeoffs these and other associated management objectives. To...

Validation of a multi-criteria evaluation model for animal welfare.

PubMed

Martín, P; Czycholl, I; Buxadé, C; Krieter, J

2017-04-01

The aim of this paper was to validate an alternative multi-criteria evaluation system to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. This alternative methodology aimed to be more transparent for stakeholders and more flexible than the methodology proposed by WQ. The WQ assessment protocol for growing pigs was implemented to collect data in different farms in Schleswig-Holstein, Germany. In total, 44 observations were carried out. The aggregation system proposed in the WQ protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first two steps of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion and principle. The utility functions and the aggregation function were constructed in two separated steps. The MACBETH (Measuring Attractiveness by a Categorical-Based Evaluation Technique) method was used for utility function determination and the Choquet integral (CI) was used as an aggregation operator. The WQ decision-makers' preferences were fitted in order to construct the utility functions and to determine the CI parameters. The validation of the MAUT model was divided into two steps, first, the results of the model were compared with the results of the WQ project at criteria and principle level, and second, a sensitivity analysis of our model was carried out to demonstrate the relative importance of welfare measures in the different steps of the multi-criteria aggregation process. Using the MAUT, similar results were obtained to those obtained when applying the WQ protocol aggregation methods, both at criteria and principle level. Thus, this model could be implemented to produce an overall assessment of animal welfare in the context of the WQ protocol for growing pigs. Furthermore, this methodology could also be used as a framework in order to produce an overall assessment of welfare for other livestock species. Two main findings are obtained from the sensitivity analysis, first, a limited number of measures had a strong influence on improving or worsening the level of welfare at criteria level and second, the MAUT model was not very sensitive to an improvement in or a worsening of single welfare measures at principle level. The use of weighted sums and the conversion of disease measures into ordinal scores should be reconsidered.

Multi-criteria decision support framework for sustainable implementation of effective green supply chain management practices.

PubMed

Boutkhoum, Omar; Hanine, Mohamed; Boukhriss, Hicham; Agouti, Tarik; Tikniouine, Abdessadek

2016-01-01

At present, environmental issues become real critical barriers for many supply chain corporations concerning the sustainability of their businesses. In this context, several studies have been proposed from both academia and industry trying to develop new measurements related to green supply chain management (GSCM) practices to overcome these barriers, which will help create new environmental strategies, implementing those practices in their manufacturing processes. The objective of this study is to present the technical and analytical contribution that multi-criteria decision making analysis (MCDA) can bring to environmental decision making problems, and especially to GSCM field. For this reason, a multi-criteria decision-making methodology, combining fuzzy analytical hierarchy process and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS), is proposed to contribute to a better understanding of new sustainable strategies through the identification and evaluation of the most appropriate GSCM practices to be adopted by industrial organizations. The fuzzy AHP process is used to construct hierarchies of the influential criteria, and then identify the importance weights of the selected criteria, while the fuzzy TOPSIS process employs these weighted criteria as inputs to evaluate and measure the performance of each alternative. To illustrate the effectiveness and performance of our MCDA approach, we have applied it to a chemical industry corporation located in Safi, Morocco.

Comparative analysis of Pareto surfaces in multi-criteria IMRT planning

NASA Astrophysics Data System (ADS)

Teichert, K.; Süss, P.; Serna, J. I.; Monz, M.; Küfer, K. H.; Thieke, C.

2011-06-01

In the multi-criteria optimization approach to IMRT planning, a given dose distribution is evaluated by a number of convex objective functions that measure tumor coverage and sparing of the different organs at risk. Within this context optimizing the intensity profiles for any fixed set of beams yields a convex Pareto set in the objective space. However, if the number of beam directions and irradiation angles are included as free parameters in the formulation of the optimization problem, the resulting Pareto set becomes more intricate. In this work, a method is presented that allows for the comparison of two convex Pareto sets emerging from two distinct beam configuration choices. For the two competing beam settings, the non-dominated and the dominated points of the corresponding Pareto sets are identified and the distance between the two sets in the objective space is calculated and subsequently plotted. The obtained information enables the planner to decide if, for a given compromise, the current beam setup is optimal. He may then re-adjust his choice accordingly during navigation. The method is applied to an artificial case and two clinical head neck cases. In all cases no configuration is dominating its competitor over the whole Pareto set. For example, in one of the head neck cases a seven-beam configuration turns out to be superior to a nine-beam configuration if the highest priority is the sparing of the spinal cord. The presented method of comparing Pareto sets is not restricted to comparing different beam angle configurations, but will allow for more comprehensive comparisons of competing treatment techniques (e.g. photons versus protons) than with the classical method of comparing single treatment plans.

Combinatorial Optimization in Project Selection Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Dewi, Sari; Sawaluddin

2018-01-01

This paper discusses the problem of project selection in the presence of two objective functions that maximize profit and minimize cost and the existence of some limitations is limited resources availability and time available so that there is need allocation of resources in each project. These resources are human resources, machine resources, raw material resources. This is treated as a consideration to not exceed the budget that has been determined. So that can be formulated mathematics for objective function (multi-objective) with boundaries that fulfilled. To assist the project selection process, a multi-objective combinatorial optimization approach is used to obtain an optimal solution for the selection of the right project. It then described a multi-objective method of genetic algorithm as one method of multi-objective combinatorial optimization approach to simplify the project selection process in a large scope.

Improved multi-objective ant colony optimization algorithm and its application in complex reasoning

NASA Astrophysics Data System (ADS)

Wang, Xinqing; Zhao, Yang; Wang, Dong; Zhu, Huijie; Zhang, Qing

2013-09-01

The problem of fault reasoning has aroused great concern in scientific and engineering fields. However, fault investigation and reasoning of complex system is not a simple reasoning decision-making problem. It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints. So far, little research has been carried out in this field. This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes. Three optimization objectives are considered simultaneously: maximum probability of average fault, maximum average importance, and minimum average complexity of test. Under the constraints of both known symptoms and the causal relationship among different components, a multi-objective optimization mathematical model is set up, taking minimizing cost of fault reasoning as the target function. Since the problem is non-deterministic polynomial-hard(NP-hard), a modified multi-objective ant colony algorithm is proposed, in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives. At last, a Pareto optimal set is acquired. Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set, through which the final fault causes can be identified according to decision-making demands, thus realize fault reasoning of the multi-constraint and multi-objective complex system. Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model, which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.

GIS Based Multi-Criteria Decision Analysis For Cement Plant Site Selection For Cuddalore District

NASA Astrophysics Data System (ADS)

Chhabra, A.

2015-12-01

India's cement industry is a vital part of its economy, providing employment to more than a million people. On the back of growing demands, due to increased construction and infrastructural activities cement market in India is expected to grow at a compound annual growth rate (CAGR) of 8.96 percent during the period 2014-2019. In this study, GIS-based spatial Multi Criteria Decision Analysis (MCDA) is used to determine the optimum and alternative sites to setup a cement plant. This technique contains a set of evaluation criteria which are quantifiable indicators of the extent to which decision objectives are realized. In intersection with available GIS (Geographical Information System) and local ancillary data, the outputs of image analysis serves as input for the multi-criteria decision making system. Moreover, the following steps were performed so as to represent the criteria in GIS layers, which underwent the GIS analysis in order to get several potential sites. Satellite imagery from LANDSAT 8 and ASTER DEM were used for the analysis. Cuddalore District in Tamil Nadu was selected as the study site as limestone mining is already being carried out in that region which meets the criteria of raw material for cement production. Several other criteria considered were land use land cover (LULC) classification (built-up area, river, forest cover, wet land, barren land, harvest land and agriculture land), slope, proximity to road, railway and drainage networks.

Application fuzzy multi-attribute decision analysis method to prioritize project success criteria

NASA Astrophysics Data System (ADS)

Phong, Nguyen Thanh; Quyen, Nguyen Le Hoang Thuy To

2017-11-01

Project success is a foundation for project owner to manage and control not only for the current project but also for future potential projects in construction companies. However, identifying the key success criteria for evaluating a particular project in real practice is a challenging task. Normally, it depends on a lot of factors, such as the expectation of the project owner and stakeholders, triple constraints of the project (cost, time, quality), and company's mission, vision, and objectives. Traditional decision-making methods for measuring the project success are usually based on subjective opinions of panel experts, resulting in irrational and inappropriate decisions. Therefore, this paper introduces a multi-attribute decision analysis method (MADAM) for weighting project success criteria by using fuzzy Analytical Hierarchy Process approach. It is found that this method is useful when dealing with imprecise and uncertain human judgments in evaluating project success criteria. Moreover, this research also suggests that although cost, time, and quality are three project success criteria projects, the satisfaction of project owner and acceptance of project stakeholders with the completed project criteria is the most important criteria for project success evaluation in Vietnam.

Multi-objective, multiple participant decision support for water management in the Andarax catchment, Almeria

NASA Astrophysics Data System (ADS)

van Cauwenbergh, N.; Pinte, D.; Tilmant, A.; Frances, I.; Pulido-Bosch, A.; Vanclooster, M.

2008-04-01

Water management in the Andarax river basin (Almeria, Spain) is a multi-objective, multi-participant, long-term decision-making problem that faces several challenges. Adequate water allocation needs informed decisions to meet increasing socio-economic demands while respecting the environmental integrity of this basin. Key players in the Andarax water sector include the municipality of Almeria, the irrigators involved in the intensive greenhouse agricultural sector, and booming second residences. A decision support system (DSS) is developed to rank different sustainable planning and management alternatives according to their socio-economic and environmental performance. The DSS is intimately linked to sustainability indicators and is designed through a public participation process. Indicators are linked to criteria reflecting stakeholders concerns in the 2005 field survey, such as fulfilling water demand, water price, technical and economical efficiency, social and environmental impacts. Indicators can be partly quantified after simulating the operation of the groundwater reservoir over a 20-year planning period and partly through a parallel expert evaluation process. To predict the impact of future water demand in the catchment, several development scenarios are designed to be evaluated in the DSS. The successive multi-criteria analysis of the performance indicators permits the ranking of the different management alternatives according to the multiple objectives formulated by the different sectors/participants. This allows more informed and transparent decision-making processes for the Andarax river basin, recognizing both the socio-economic and environmental dimensions of water resources management.

Clinical assessment and determinants of chronic allograft nephropathy in maintenance renal transplant patients.

PubMed

Grinyo, Josep M; Saval, Nuria; Campistol, Josep M

2011-11-01

Current knowledge about the natural history, treatment and physicians' perception of chronic allograft nephropathy (CAN) is limited. The present study evaluated the prevalence and determinants of CAN in renal transplant patients. Epidemiological, cross-sectional multi-centre study conducted in Spain. A total of 872 renal transplant recipients with a functioning graft and at least 2 years of post-transplant data on renal function were consecutively included. CAN diagnosis was recorded based on physician's clinical criteria and on laboratory criteria (serum creatinine ≥ 2 mg/dL and/or glomerular filtration rate ≤ 50 mL/min). The mean time from transplantation until the time of this study was 8.2 years. CAN was diagnosed in 35% of patients (n = 305) according to the physician's criteria (31% of whom with histological assessment) and in 55.5% (n = 482) according to laboratory objective criteria. An older donor age, lack of induction therapy, cyclosporine use, lower tacrolimus levels at 1 year, acute rejection, hypertension and worse initial renal function were associated with CAN development. Time from transplant to biopsy was greater in patients with anti-proteinuric treatment. Immunosuppression was modified in 46.9% of patients with CAN diagnosis [calcineurin inhibitor (CNI) reduction alone in 18.9% of cases; CNI reduction and mycophenolate modification in 17.8% and CNI reduction or withdrawal with introduction of proliferation signal inhibitors in 12.9%). After ~8 years from renal transplantation, 55.5% of patients presented CAN, which was considerably underestimated by physicians. An older donor age and less initial immunosuppression seemed to be related to CAN development.

Robust Sensitivity Analysis for Multi-Attribute Deterministic Hierarchical Value Models

DTIC Science & Technology

2002-03-01

such as weighted sum method, weighted 5 product method, and the Analytic Hierarchy Process ( AHP ). This research focuses on only weighted sum...different groups. They can be termed as deterministic, stochastic, or fuzzy multi-objective decision methods if they are classified according to the...weighted product model (WPM), and analytic hierarchy process ( AHP ). His method attempts to identify the most important criteria weight and the most

Highlights from the 17th International Conference on Multi-Criteria Decision Making, Whistler, BC, August 6-11, 2004

DTIC Science & Technology

2005-04-01

related to one of the following areas: 1. Group Decision Support Methods; 2. Decision Support Methods; 3. AHP applications; 4. Multi...Objective Linear Programming (MOLP) algorithms; 5. Industrial engineering applications; 6. Behavioural considerations, and 7. Fuzzy MCDM. 3...making. This is especially important when using software like AHP or when constructing questionnaires for SME’s ( see [10] for many examples

Graph drawing using tabu search coupled with path relinking.

PubMed

Dib, Fadi K; Rodgers, Peter

2018-01-01

Graph drawing, or the automatic layout of graphs, is a challenging problem. There are several search based methods for graph drawing which are based on optimizing an objective function which is formed from a weighted sum of multiple criteria. In this paper, we propose a new neighbourhood search method which uses a tabu search coupled with path relinking to optimize such objective functions for general graph layouts with undirected straight lines. To our knowledge, before our work, neither of these methods have been previously used in general multi-criteria graph drawing. Tabu search uses a memory list to speed up searching by avoiding previously tested solutions, while the path relinking method generates new solutions by exploring paths that connect high quality solutions. We use path relinking periodically within the tabu search procedure to speed up the identification of good solutions. We have evaluated our new method against the commonly used neighbourhood search optimization techniques: hill climbing and simulated annealing. Our evaluation examines the quality of the graph layout (objective function's value) and the speed of layout in terms of the number of evaluated solutions required to draw a graph. We also examine the relative scalability of each method. Our experimental results were applied to both random graphs and a real-world dataset. We show that our method outperforms both hill climbing and simulated annealing by producing a better layout in a lower number of evaluated solutions. In addition, we demonstrate that our method has greater scalability as it can layout larger graphs than the state-of-the-art neighbourhood search methods. Finally, we show that similar results can be produced in a real world setting by testing our method against a standard public graph dataset.

A fuzzy cost-benefit function to select economical products for processing in a closed-loop supply chain

NASA Astrophysics Data System (ADS)

Pochampally, Kishore K.; Gupta, Surendra M.; Cullinane, Thomas P.

2004-02-01

The cost-benefit analysis of data associated with re-processing of used products often involves the uncertainty feature of cash-flow modeling. The data is not objective because of uncertainties in supply, quality and disassembly times of used products. Hence, decision-makers must rely on "fuzzy" data for analysis. The same parties that are involved in the forward supply chain often carry out the collection and re-processing of used products. It is therefore important that the cost-benefit analysis takes the data of both new products and used products into account. In this paper, a fuzzy cost-benefit function is proposed that is used to perform a multi-criteria economic analysis to select the most economical products to process in a closed-loop supply chain. Application of the function is detailed through an illustrative example.

A modified multi-objective particle swarm optimization approach and its application to the design of a deepwater composite riser

NASA Astrophysics Data System (ADS)

Zheng, Y.; Chen, J.

2017-09-01

A modified multi-objective particle swarm optimization method is proposed for obtaining Pareto-optimal solutions effectively. Different from traditional multi-objective particle swarm optimization methods, Kriging meta-models and the trapezoid index are introduced and integrated with the traditional one. Kriging meta-models are built to match expensive or black-box functions. By applying Kriging meta-models, function evaluation numbers are decreased and the boundary Pareto-optimal solutions are identified rapidly. For bi-objective optimization problems, the trapezoid index is calculated as the sum of the trapezoid's area formed by the Pareto-optimal solutions and one objective axis. It can serve as a measure whether the Pareto-optimal solutions converge to the Pareto front. Illustrative examples indicate that to obtain Pareto-optimal solutions, the method proposed needs fewer function evaluations than the traditional multi-objective particle swarm optimization method and the non-dominated sorting genetic algorithm II method, and both the accuracy and the computational efficiency are improved. The proposed method is also applied to the design of a deepwater composite riser example in which the structural performances are calculated by numerical analysis. The design aim was to enhance the tension strength and minimize the cost. Under the buckling constraint, the optimal trade-off of tensile strength and material volume is obtained. The results demonstrated that the proposed method can effectively deal with multi-objective optimizations with black-box functions.

Does technique matter; a pilot study exploring weighting techniques for a multi-criteria decision support framework.

PubMed

van Til, Janine; Groothuis-Oudshoorn, Catharina; Lieferink, Marijke; Dolan, James; Goetghebeur, Mireille

2014-01-01

There is an increased interest in the use of multi-criteria decision analysis (MCDA) to support regulatory and reimbursement decision making. The EVIDEM framework was developed to provide pragmatic multi-criteria decision support in health care, to estimate the value of healthcare interventions, and to aid in priority-setting. The objectives of this study were to test 1) the influence of different weighting techniques on the overall outcome of an MCDA exercise, 2) the discriminative power in weighting different criteria of such techniques, and 3) whether different techniques result in similar weights in weighting the criteria set proposed by the EVIDEM framework. A sample of 60 Dutch and Canadian students participated in the study. Each student used an online survey to provide weights for 14 criteria with two different techniques: a five-point rating scale and one of the following techniques selected randomly: ranking, point allocation, pairwise comparison and best worst scaling. The results of this study indicate that there is no effect of differences in weights on value estimates at the group level. On an individual level, considerable differences in criteria weights and rank order occur as a result of the weight elicitation method used, and the ability of different techniques to discriminate in criteria importance. Of the five techniques tested, the pair-wise comparison of criteria has the highest ability to discriminate in weights when fourteen criteria are compared. When weights are intended to support group decisions, the choice of elicitation technique has negligible impact on criteria weights and the overall value of an innovation. However, when weights are used to support individual decisions, the choice of elicitation technique influences outcome and studies that use dissimilar techniques cannot be easily compared. Weight elicitation through pairwise comparison of criteria is preferred when taking into account its superior ability to discriminate between criteria and respondents' preferences.

Evaluating Partnerships to Enhance Disaster Risk Management using Multi-Criteria Analysis: An Application at the Pan-European Level

NASA Astrophysics Data System (ADS)

Hochrainer-Stigler, Stefan; Lorant, Anna

2018-01-01

Disaster risk is increasingly recognized as a major development challenge. Recent calls emphasize the need to proactively engage in disaster risk reduction, as well as to establish new partnerships between private and public sector entities in order to decrease current and future risks. Very often such potential partnerships have to meet different objectives reflecting on the priorities of stakeholders involved. Consequently, potential partnerships need to be assessed on multiple criteria to determine weakest links and greatest threats in collaboration. This paper takes a supranational multi-sector partnership perspective, and considers possible ways to enhance disaster risk management in the European Union by better coordination between the European Union Solidarity Fund, risk reduction efforts, and insurance mechanisms. Based on flood risk estimates we employ a risk-layer approach to determine set of options for new partnerships and test them in a high-level workshop via a novel cardinal ranking based multi-criteria approach. Whilst transformative changes receive good overall scores, we also find that the incorporation of risk into budget planning is an essential condition for successful partnerships.

Valuing hydrological alteration in multi-objective water resources management

NASA Astrophysics Data System (ADS)

Bizzi, Simone; Pianosi, Francesca; Soncini-Sessa, Rodolfo

2012-11-01

SummaryThe management of water through the impoundment of rivers by dams and reservoirs is necessary to support key human activities such as hydropower production, agriculture and flood risk mitigation. Advances in multi-objective optimization techniques and ever growing computing power make it possible to design reservoir operating policies that represent Pareto-optimal tradeoffs between multiple interests. On the one hand, such optimization methods can enhance performances of commonly targeted objectives (such as hydropower production or water supply), on the other hand they risk strongly penalizing all the interests not directly (i.e. mathematically) included in the optimization algorithm. The alteration of the downstream hydrological regime is a well established cause of ecological degradation and its evaluation and rehabilitation is commonly required by recent legislation (as the Water Framework Directive in Europe). However, it is rarely embedded in reservoir optimization routines and, even when explicitly considered, the criteria adopted for its evaluation are doubted and not commonly trusted, undermining the possibility of real implementation of environmentally friendly policies. The main challenges in defining and assessing hydrological alterations are: how to define a reference state (referencing); how to define criteria upon which to build mathematical indicators of alteration (measuring); and finally how to aggregate the indicators in a single evaluation index (valuing) that can serve as objective function in the optimization problem. This paper aims to address these issues by: (i) discussing the benefits and constrains of different approaches to referencing, measuring and valuing hydrological alteration; (ii) testing two alternative indices of hydrological alteration, one based on the established framework of Indicators of Hydrological Alteration (Richter et al., 1996), and one satisfying the mathematical properties required by widely used optimization methods based on dynamic programming; (iii) demonstrating and discussing these indices by application River Ticino, in Italy; (iv) providing a framework to effectively include hydrological alteration within reservoir operation optimization.

Vector critical points and generalized quasi-efficient solutions in nonsmooth multi-objective programming.

PubMed

Wang, Zhen; Li, Ru; Yu, Guolin

2017-01-01

In this work, several extended approximately invex vector-valued functions of higher order involving a generalized Jacobian are introduced, and some examples are presented to illustrate their existences. The notions of higher-order (weak) quasi-efficiency with respect to a function are proposed for a multi-objective programming. Under the introduced generalization of higher-order approximate invexities assumptions, we prove that the solutions of generalized vector variational-like inequalities in terms of the generalized Jacobian are the generalized quasi-efficient solutions of nonsmooth multi-objective programming problems. Moreover, the equivalent conditions are presented, namely, a vector critical point is a weakly quasi-efficient solution of higher order with respect to a function.

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

PubMed Central

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having “very high susceptibility”, with the further 31% falling into zones classified as having “high susceptibility”. PMID:26089577

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping.

PubMed

Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

2014-12-01

Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

A Goal Oriented Approach for Modeling and Analyzing Security Trade-Offs

NASA Astrophysics Data System (ADS)

Elahi, Golnaz; Yu, Eric

In designing software systems, security is typically only one design objective among many. It may compete with other objectives such as functionality, usability, and performance. Too often, security mechanisms such as firewalls, access control, or encryption are adopted without explicit recognition of competing design objectives and their origins in stakeholder interests. Recently, there is increasing acknowledgement that security is ultimately about trade-offs. One can only aim for "good enough" security, given the competing demands from many parties. In this paper, we examine how conceptual modeling can provide explicit and systematic support for analyzing security trade-offs. After considering the desirable criteria for conceptual modeling methods, we examine several existing approaches for dealing with security trade-offs. From analyzing the limitations of existing methods, we propose an extension to the i* framework for security trade-off analysis, taking advantage of its multi-agent and goal orientation. The method was applied to several case studies used to exemplify existing approaches.

A multi-objective model for closed-loop supply chain optimization and efficient supplier selection in a competitive environment considering quantity discount policy

NASA Astrophysics Data System (ADS)

Jahangoshai Rezaee, Mustafa; Yousefi, Samuel; Hayati, Jamileh

2017-06-01

Supplier selection and allocation of optimal order quantity are two of the most important processes in closed-loop supply chain (CLSC) and reverse logistic (RL). So that providing high quality raw material is considered as a basic requirement for a manufacturer to produce popular products, as well as achieve more market shares. On the other hand, considering the existence of competitive environment, suppliers have to offer customers incentives like discounts and enhance the quality of their products in a competition with other manufacturers. Therefore, in this study, a model is presented for CLSC optimization, efficient supplier selection, as well as orders allocation considering quantity discount policy. It is modeled using multi-objective programming based on the integrated simultaneous data envelopment analysis-Nash bargaining game. In this study, maximizing profit and efficiency and minimizing defective and functions of delivery delay rate are taken into accounts. Beside supplier selection, the suggested model selects refurbishing sites, as well as determining the number of products and parts in each network's sector. The suggested model's solution is carried out using global criteria method. Furthermore, based on related studies, a numerical example is examined to validate it.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Szoka de Valladares, M.R.; Mack, S.

The DOE Hydrogen Program needs to develop criteria as part of a systematic evaluation process for proposal identification, evaluation and selection. The H Scan component of this process provides a framework in which a project proposer can fully describe their candidate technology system and its components. The H Scan complements traditional methods of capturing cost and technical information. It consists of a special set of survey forms designed to elicit information so expert reviewers can assess the proposal relative to DOE specified selection criteria. The Analytic Hierarchy Process (AHP) component of the decision process assembles the management defined evaluation andmore » selection criteria into a coherent multi-level decision construct by which projects can be evaluated in pair-wise comparisons. The AHP model will reflect management`s objectives and it will assist in the ranking of individual projects based on the extent to which each contributes to management`s objectives. This paper contains a detailed description of the products and activities associated with the planning and evaluation process: The objectives or criteria; the H Scan; and The Analytic Hierarchy Process (AHP).« less

Using multi-objective robust decision making to support seasonal water management in the Chao Phraya River basin, Thailand

NASA Astrophysics Data System (ADS)

Riegels, Niels; Jessen, Oluf; Madsen, Henrik

2016-04-01

A multi-objective robust decision making approach is demonstrated that supports seasonal water management in the Chao Phraya River basin in Thailand. The approach uses multi-objective optimization to identify a Pareto-optimal set of management alternatives. Ensemble simulation is used to evaluate how each member of the Pareto set performs under a range of uncertain future conditions, and a robustness criterion is used to select a preferred alternative. Data mining tools are then used to identify ranges of uncertain factor values that lead to unacceptable performance for the preferred alternative. The approach is compared to a multi-criteria scenario analysis approach to estimate whether the introduction of additional complexity has the potential to improve decision making. Dry season irrigation in Thailand is managed through non-binding recommendations about the maximum extent of rice cultivation along with incentives for less water-intensive crops. Management authorities lack authority to prevent river withdrawals for irrigation when rice cultivation exceeds recommendations. In practice, this means that water must be provided to irrigate the actual planted area because of downstream municipal water supply requirements and water quality constraints. This results in dry season reservoir withdrawals that exceed planned withdrawals, reducing carryover storage to hedge against insufficient wet season runoff. The dry season planning problem in Thailand can therefore be framed in terms of decisions, objectives, constraints, and uncertainties. Decisions include recommendations about the maximum extent of rice cultivation and incentives for growing less water-intensive crops. Objectives are to maximize benefits to farmers, minimize the risk of inadequate carryover storage, and minimize incentives. Constraints include downstream municipal demands and water quality requirements. Uncertainties include the actual extent of rice cultivation, dry season precipitation, and precipitation in the following wet season. The multi-objective robust decision making approach is implemented as follows. First, three baseline simulation models are developed, including a crop water demand model, a river basin simulation model, and model of the impact of incentives on cropping patterns. The crop water demand model estimates irrigation water demands; the river basin simulation model estimates reservoir drawdown required to meet demands given forecasts of precipitation, evaporation, and runoff; the model of incentive impacts estimates the cost of incentives as function of marginal changes in rice yields. Optimization is used to find a set of non-dominated alternatives as a function of rice area and incentive decisions. An ensemble of uncertain model inputs is generated to represent uncertain hydrological and crop area forecasts. An ensemble of indicator values is then generated for each of the decision objectives: farmer benefits, end-of-wet-season reservoir storage, and the cost of incentives. A single alternative is selected from the Pareto set using a robustness criterion. Threshold values are defined for each of the objectives to identify ensemble members for which objective values are unacceptable, and the PRIM data mining algorithm is then used to identify input values associated with unacceptable model outcomes.

Application of Multi-Criteria Decision Making (MCDM) Technique for Gradation of Jute Fibres

NASA Astrophysics Data System (ADS)

Choudhuri, P. K.

2014-12-01

Multi-Criteria Decision Making is a branch of Operation Research (OR) having a comparatively short history of about 40 years. It is being popularly used in the field of engineering, banking, fixing policy matters etc. It can also be applied for taking decisions in daily life like selecting a car to purchase, selecting bride or groom and many others. Various MCDM methods namely Weighted Sum Model (WSM), Weighted Product Model (WPM), Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) and Elimination and Choice Translating Reality (ELECTRE) are there to solve many decision making problems, each having its own limitations. However it is very difficult to decide which MCDM method is the best. MCDM methods are prospective quantitative approaches for solving decision problems involving finite number of alternatives and criteria. Very few research works in textiles have been carried out with the help of this technique particularly where decision taking among several alternatives becomes the major problem based on some criteria which are conflicting in nature. Gradation of jute fibres on the basis of the criteria like strength, root content, defects, colour, density, fineness etc. is an important task to perform. The MCDM technique provides enough scope to be applied for the gradation of jute fibres or ranking among several varieties keeping in view a particular object and on the basis of some selection criteria and their relative weightage. The present paper is an attempt to explore the scope of applying the multiplicative AHP method of multi-criteria decision making technique to determine the quality values of selected jute fibres on the basis of some above stated important criteria and ranking them accordingly. A good agreement in ranking is observed between the existing Bureau of Indian Standards (BIS) grading and proposed method.

Multi-criteria dynamic decision under uncertainty: a stochastic viability analysis and an application to sustainable fishery management.

PubMed

De Lara, M; Martinet, V

2009-02-01

Managing natural resources in a sustainable way is a hard task, due to uncertainties, dynamics and conflicting objectives (ecological, social, and economical). We propose a stochastic viability approach to address such problems. We consider a discrete-time control dynamical model with uncertainties, representing a bioeconomic system. The sustainability of this system is described by a set of constraints, defined in practice by indicators - namely, state, control and uncertainty functions - together with thresholds. This approach aims at identifying decision rules such that a set of constraints, representing various objectives, is respected with maximal probability. Under appropriate monotonicity properties of dynamics and constraints, having economic and biological content, we characterize an optimal feedback. The connection is made between this approach and the so-called Management Strategy Evaluation for fisheries. A numerical application to sustainable management of Bay of Biscay nephrops-hakes mixed fishery is given.

Objective criteria ranking framework for renewable energy policy decisions in Nigeria

NASA Astrophysics Data System (ADS)

K, Nwofor O.; N, Dike V.

2016-08-01

We present a framework that seeks to improve the objectivity of renewable energy policy decisions in Nigeria. It consists of expert ranking of resource abundance, resource efficiency and resource environmental comfort in the choice of renewable energy options for large scale power generation. The rankings are converted to a more objective function called Resource Appraisal Function (RAF) using dependence operators derived from logical relationships amongst the various criteria. The preferred option is that with the highest average RAF coupled with the least RAF variance. The method can be extended to more options, more criteria, and more opinions and can be adapted for similar decisions in education, environment and health sectors.

Determining flexor-tendon repair techniques via soft computing

NASA Technical Reports Server (NTRS)

Johnson, M.; Firoozbakhsh, K.; Moniem, M.; Jamshidi, M.

2001-01-01

An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.

Determining flexor-tendon repair techniques via soft computing.

PubMed

Johnson, M; Firoozbakhsh, K; Moniem, M; Jamshidi, M

2001-01-01

An SC-based multi-objective decision-making method for determining the optimal flexor-tendon repair technique from experimental and clinical survey data, and with variable circumstances, was presented. Results were compared with those from the Taguchi method. Using the Taguchi method results in the need to perform ad-hoc decisions when the outcomes for individual objectives are contradictory to a particular preference or circumstance, whereas the SC-based multi-objective technique provides a rigorous straightforward computational process in which changing preferences and importance of differing objectives are easily accommodated. Also, adding more objectives is straightforward and easily accomplished. The use of fuzzy-set representations of information categories provides insight into their performance throughout the range of their universe of discourse. The ability of the technique to provide a "best" medical decision given a particular physician, hospital, patient, situation, and other criteria was also demonstrated.

A multi-objective genetic algorithm for a mixed-model assembly U-line balancing type-I problem considering human-related issues, training, and learning

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Montazeri, Mona; Farrokhi-Asl, Hamed; Rafiei, Hamed

2016-12-01

Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate components. The first part of the objective function is related to balance problem. In this part, objective functions are minimizing the cycle time, minimizing the number of workstations, and maximizing the line efficiencies. The second part is related to human issues and consists of hiring cost, firing cost, training cost, and salary. To solve the presented model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm and multi-objective particle swarm optimization, have been used. A simple solution representation is provided in this paper to encode the solutions. Finally, the computational results are compared and analyzed.

Surrogate-based Analysis and Optimization

NASA Technical Reports Server (NTRS)

Queipo, Nestor V.; Haftka, Raphael T.; Shyy, Wei; Goel, Tushar; Vaidyanathan, Raj; Tucker, P. Kevin

2005-01-01

A major challenge to the successful full-scale development of modem aerospace systems is to address competing objectives such as improved performance, reduced costs, and enhanced safety. Accurate, high-fidelity models are typically time consuming and computationally expensive. Furthermore, informed decisions should be made with an understanding of the impact (global sensitivity) of the design variables on the different objectives. In this context, the so-called surrogate-based approach for analysis and optimization can play a very valuable role. The surrogates are constructed using data drawn from high-fidelity models, and provide fast approximations of the objectives and constraints at new design points, thereby making sensitivity and optimization studies feasible. This paper provides a comprehensive discussion of the fundamental issues that arise in surrogate-based analysis and optimization (SBAO), highlighting concepts, methods, techniques, as well as practical implications. The issues addressed include the selection of the loss function and regularization criteria for constructing the surrogates, design of experiments, surrogate selection and construction, sensitivity analysis, convergence, and optimization. The multi-objective optimal design of a liquid rocket injector is presented to highlight the state of the art and to help guide future efforts.

Collaborative real-time scheduling of multiple PTZ cameras for multiple object tracking in video surveillance

NASA Astrophysics Data System (ADS)

Liu, Yu-Che; Huang, Chung-Lin

2013-03-01

This paper proposes a multi-PTZ-camera control mechanism to acquire close-up imagery of human objects in a surveillance system. The control algorithm is based on the output of multi-camera, multi-target tracking. Three main concerns of the algorithm are (1) the imagery of human object's face for biometric purposes, (2) the optimal video quality of the human objects, and (3) minimum hand-off time. Here, we define an objective function based on the expected capture conditions such as the camera-subject distance, pan tile angles of capture, face visibility and others. Such objective function serves to effectively balance the number of captures per subject and quality of captures. In the experiments, we demonstrate the performance of the system which operates in real-time under real world conditions on three PTZ cameras.

Including robustness in multi-criteria optimization for intensity-modulated proton therapy

NASA Astrophysics Data System (ADS)

Chen, Wei; Unkelbach, Jan; Trofimov, Alexei; Madden, Thomas; Kooy, Hanne; Bortfeld, Thomas; Craft, David

2012-02-01

We present a method to include robustness in a multi-criteria optimization (MCO) framework for intensity-modulated proton therapy (IMPT). The approach allows one to simultaneously explore the trade-off between different objectives as well as the trade-off between robustness and nominal plan quality. In MCO, a database of plans each emphasizing different treatment planning objectives, is pre-computed to approximate the Pareto surface. An IMPT treatment plan that strikes the best balance between the different objectives can be selected by navigating on the Pareto surface. In our approach, robustness is integrated into MCO by adding robustified objectives and constraints to the MCO problem. Uncertainties (or errors) of the robust problem are modeled by pre-calculated dose-influence matrices for a nominal scenario and a number of pre-defined error scenarios (shifted patient positions, proton beam undershoot and overshoot). Objectives and constraints can be defined for the nominal scenario, thus characterizing nominal plan quality. A robustified objective represents the worst objective function value that can be realized for any of the error scenarios and thus provides a measure of plan robustness. The optimization method is based on a linear projection solver and is capable of handling large problem sizes resulting from a fine dose grid resolution, many scenarios, and a large number of proton pencil beams. A base-of-skull case is used to demonstrate the robust optimization method. It is demonstrated that the robust optimization method reduces the sensitivity of the treatment plan to setup and range errors to a degree that is not achieved by a safety margin approach. A chordoma case is analyzed in more detail to demonstrate the involved trade-offs between target underdose and brainstem sparing as well as robustness and nominal plan quality. The latter illustrates the advantage of MCO in the context of robust planning. For all cases examined, the robust optimization for each Pareto optimal plan takes less than 5 min on a standard computer, making a computationally friendly interface possible to the planner. In conclusion, the uncertainty pertinent to the IMPT procedure can be reduced during treatment planning by optimizing plans that emphasize different treatment objectives, including robustness, and then interactively seeking for a most-preferred one from the solution Pareto surface.

An outer approximation method for the road network design problem

PubMed Central

2018-01-01

Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well. PMID:29590111

An outer approximation method for the road network design problem.

PubMed

Asadi Bagloee, Saeed; Sarvi, Majid

2018-01-01

Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well.

Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis.

PubMed

Scholten, Lisa; Scheidegger, Andreas; Reichert, Peter; Maurer, Max; Mauer, Max; Lienert, Judit

2014-02-01

To overcome the difficulties of strategic asset management of water distribution networks, a pipe failure and a rehabilitation model are combined to predict the long-term performance of rehabilitation strategies. Bayesian parameter estimation is performed to calibrate the failure and replacement model based on a prior distribution inferred from three large water utilities in Switzerland. Multi-criteria decision analysis (MCDA) and scenario planning build the framework for evaluating 18 strategic rehabilitation alternatives under future uncertainty. Outcomes for three fundamental objectives (low costs, high reliability, and high intergenerational equity) are assessed. Exploitation of stochastic dominance concepts helps to identify twelve non-dominated alternatives and local sensitivity analysis of stakeholder preferences is used to rank them under four scenarios. Strategies with annual replacement of 1.5-2% of the network perform reasonably well under all scenarios. In contrast, the commonly used reactive replacement is not recommendable unless cost is the only relevant objective. Exemplified for a small Swiss water utility, this approach can readily be adapted to support strategic asset management for any utility size and based on objectives and preferences that matter to the respective decision makers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method.

PubMed

Liu, Hu-Chen; Wu, Jing; Li, Ping

2013-12-01

Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include "incineration", "steam sterilization", "microwave" and "landfill". The results obtained using the proposed approach are analyzed in a comparative way. Copyright © 2013. Published by Elsevier Ltd.

Multi-Objective Programming for Lot-Sizing with Quantity Discount

NASA Astrophysics Data System (ADS)

Kang, He-Yau; Lee, Amy H. I.; Lai, Chun-Mei; Kang, Mei-Sung

2011-11-01

Multi-objective programming (MOP) is one of the popular methods for decision making in a complex environment. In a MOP, decision makers try to optimize two or more objectives simultaneously under various constraints. A complete optimal solution seldom exists, and a Pareto-optimal solution is usually used. Some methods, such as the weighting method which assigns priorities to the objectives and sets aspiration levels for the objectives, are used to derive a compromise solution. The ɛ-constraint method is a modified weight method. One of the objective functions is optimized while the other objective functions are treated as constraints and are incorporated in the constraint part of the model. This research considers a stochastic lot-sizing problem with multi-suppliers and quantity discounts. The model is transformed into a mixed integer programming (MIP) model next based on the ɛ-constraint method. An illustrative example is used to illustrate the practicality of the proposed model. The results demonstrate that the model is an effective and accurate tool for determining the replenishment of a manufacturer from multiple suppliers for multi-periods.

How to constrain multi-objective calibrations of the SWAT model using water balance components

USDA-ARS?s Scientific Manuscript database

Automated procedures are often used to provide adequate fits between hydrologic model estimates and observed data. While the models may provide good fits based upon numeric criteria, they may still not accurately represent the basic hydrologic characteristics of the represented watershed. Here we ...

The Domains for the Multi-Criteria Decisions about E-Learning Systems

ERIC Educational Resources Information Center

Uysal, Murat Pasa

2012-01-01

Developments in computer and information technologies continue to give opportunities for designing advanced E-learning systems while entailing objective and technical evaluation methodologies. Design and development of E-learning systems require time-consuming and labor-intensive processes; therefore any decision about these systems and their…

Multi-objective possibilistic model for portfolio selection with transaction cost

NASA Astrophysics Data System (ADS)

Jana, P.; Roy, T. K.; Mazumder, S. K.

2009-06-01

In this paper, we introduce the possibilistic mean value and variance of continuous distribution, rather than probability distributions. We propose a multi-objective Portfolio based model and added another entropy objective function to generate a well diversified asset portfolio within optimal asset allocation. For quantifying any potential return and risk, portfolio liquidity is taken into account and a multi-objective non-linear programming model for portfolio rebalancing with transaction cost is proposed. The models are illustrated with numerical examples.

The Ways of the Hand: A Study of Hand Function among Blind, Visually Impaired and Visually Impaired Multi-Handicapped Children and Adolescents.

ERIC Educational Resources Information Center

Rogow, Sally M.

1987-01-01

The manual development of 148 blind, visually impaired, and visually impaired multi-handicapped students, aged 3-19, was studied. Results indicated a significant relationship between object manipulation and speech, and an inverse relationship between object manipulation and stereotypic hand mannerisms. Optimal development of manual functions and…

Environmental assessment in health care organizations.

PubMed

Romero, Isabel; Carnero, María Carmen

2017-12-22

The aim of this research is to design a multi-criteria model for environmental assessment of health care organizations. This is a model which guarantees the objectivity of the results obtained, is easy to apply, and incorporates a series of criteria, and their corresponding descriptors, relevant to the internal environmental auditing processes of the hospital. Furthermore, judgments were given by three experts from the areas of health, the environment, and multi-criteria decision techniques. From the values assigned, geometric means were calculated, giving weightings for the criteria of the model. This innovative model is intended for application within a continuous improvement process. A practical case from a Spanish hospital is included at the end. Information contained in the sustainability report provided the data needed to apply the model. The example contains all the criteria previously defined in the model. The results obtained show that the best-satisfied criteria are those related to energy consumption, generation of hazardous waste, legal matters, environmental sensitivity of staff, patients and others, and the environmental management of suppliers. On the other hand, those areas returning poor results are control of atmospheric emissions, increase in consumption of renewable energies, and the logistics of waste produced. It is recommended that steps be taken to correct these deficiencies, thus leading to an acceptable increase in the sustainability of the hospital.

A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

NASA Astrophysics Data System (ADS)

Bascetin, A.

2007-04-01

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.

Integrating Multiple Criteria Evaluation and GIS in Ecotourism: a Review

NASA Astrophysics Data System (ADS)

Mohd, Z. H.; Ujang, U.

2016-09-01

The concept of 'Eco-tourism' is increasingly heard in recent decades. Ecotourism is one adventure that environmentally responsible intended to appreciate the nature experiences and cultures. Ecotourism should have low impact on environment and must contribute to the prosperity of local residents. This article reviews the use of Multiple Criteria Evaluation (MCE) and Geographic Information System (GIS) in ecotourism. Multiple criteria evaluation mostly used to land suitability analysis or fulfill specific objectives based on various attributes that exist in the selected area. To support the process of environmental decision making, the application of GIS is used to display and analysis the data through Analytic Hierarchy Process (AHP). Integration between MCE and GIS tool is important to determine the relative weight for the criteria used objectively. With the MCE method, it can resolve the conflict between recreation and conservation which is to minimize the environmental and human impact. Most studies evidences that the GIS-based AHP as a multi criteria evaluation is a strong and effective in tourism planning which can aid in the development of ecotourism industry effectively.

A lexicographic weighted Tchebycheff approach for multi-constrained multi-objective optimization of the surface grinding process

NASA Astrophysics Data System (ADS)

Khalilpourazari, Soheyl; Khalilpourazary, Saman

2017-05-01

In this article a multi-objective mathematical model is developed to minimize total time and cost while maximizing the production rate and surface finish quality in the grinding process. The model aims to determine optimal values of the decision variables considering process constraints. A lexicographic weighted Tchebycheff approach is developed to obtain efficient Pareto-optimal solutions of the problem in both rough and finished conditions. Utilizing a polyhedral branch-and-cut algorithm, the lexicographic weighted Tchebycheff model of the proposed multi-objective model is solved using GAMS software. The Pareto-optimal solutions provide a proper trade-off between conflicting objective functions which helps the decision maker to select the best values for the decision variables. Sensitivity analyses are performed to determine the effect of change in the grain size, grinding ratio, feed rate, labour cost per hour, length of workpiece, wheel diameter and downfeed of grinding parameters on each value of the objective function.

An adaptive evolutionary multi-objective approach based on simulated annealing.

PubMed

Li, H; Landa-Silva, D

2011-01-01

A multi-objective optimization problem can be solved by decomposing it into one or more single objective subproblems in some multi-objective metaheuristic algorithms. Each subproblem corresponds to one weighted aggregation function. For example, MOEA/D is an evolutionary multi-objective optimization (EMO) algorithm that attempts to optimize multiple subproblems simultaneously by evolving a population of solutions. However, the performance of MOEA/D highly depends on the initial setting and diversity of the weight vectors. In this paper, we present an improved version of MOEA/D, called EMOSA, which incorporates an advanced local search technique (simulated annealing) and adapts the search directions (weight vectors) corresponding to various subproblems. In EMOSA, the weight vector of each subproblem is adaptively modified at the lowest temperature in order to diversify the search toward the unexplored parts of the Pareto-optimal front. Our computational results show that EMOSA outperforms six other well established multi-objective metaheuristic algorithms on both the (constrained) multi-objective knapsack problem and the (unconstrained) multi-objective traveling salesman problem. Moreover, the effects of the main algorithmic components and parameter sensitivities on the search performance of EMOSA are experimentally investigated.

Multi-point objective-oriented sequential sampling strategy for constrained robust design

NASA Astrophysics Data System (ADS)

Zhu, Ping; Zhang, Siliang; Chen, Wei

2015-03-01

Metamodelling techniques are widely used to approximate system responses of expensive simulation models. In association with the use of metamodels, objective-oriented sequential sampling methods have been demonstrated to be effective in balancing the need for searching an optimal solution versus reducing the metamodelling uncertainty. However, existing infilling criteria are developed for deterministic problems and restricted to one sampling point in one iteration. To exploit the use of multiple samples and identify the true robust solution in fewer iterations, a multi-point objective-oriented sequential sampling strategy is proposed for constrained robust design problems. In this article, earlier development of objective-oriented sequential sampling strategy for unconstrained robust design is first extended to constrained problems. Next, a double-loop multi-point sequential sampling strategy is developed. The proposed methods are validated using two mathematical examples followed by a highly nonlinear automotive crashworthiness design example. The results show that the proposed method can mitigate the effect of both metamodelling uncertainty and design uncertainty, and identify the robust design solution more efficiently than the single-point sequential sampling approach.

Multiple-objective evaluation of wastewater treatment plant control alternatives.

PubMed

Flores-Alsina, Xavier; Gallego, Alejandro; Feijoo, Gumersindo; Rodriguez-Roda, Ignasi

2010-05-01

Besides the evaluation of the environmental issues, the correct assessment of wastewater treatment plants (WWTP) should take into account several objectives such as: economic e.g. operation costs; technical e.g. risk of suffering microbiology-related TSS separation problems; or legal e.g. accomplishment with the effluent standards in terms of the different pollution loads. For this reason, the main objective of this paper is to show the benefits of complementing the environmental assessment carried out by life cycle assessment with economical, technical and legal criteria. Using a preliminary version of the BSM2 as a case study, different combinations of controllers are implemented, simulated and evaluated. In the following step, the resulting multi-criteria matrix is mined using multivariate statistical techniques. The results showed that the presence of an external carbon source addition, the type of aeration system and the TSS controller are the key elements creating the differences amongst the alternatives. Also, it was possible to characterize the different control strategies according to a set of aggregated criteria. Additionally, the existing synergies amongst different objectives and their consequent trade-offs were identified. Finally, it was discovered that from the initial extensive list of evaluation criteria, only a small set of five are really discriminant, being useful to differentiate within the generated alternatives. Copyright 2010 Elsevier Ltd. All rights reserved.

Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

NASA Astrophysics Data System (ADS)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright

Graph drawing using tabu search coupled with path relinking

PubMed Central

Rodgers, Peter

2018-01-01

Graph drawing, or the automatic layout of graphs, is a challenging problem. There are several search based methods for graph drawing which are based on optimizing an objective function which is formed from a weighted sum of multiple criteria. In this paper, we propose a new neighbourhood search method which uses a tabu search coupled with path relinking to optimize such objective functions for general graph layouts with undirected straight lines. To our knowledge, before our work, neither of these methods have been previously used in general multi-criteria graph drawing. Tabu search uses a memory list to speed up searching by avoiding previously tested solutions, while the path relinking method generates new solutions by exploring paths that connect high quality solutions. We use path relinking periodically within the tabu search procedure to speed up the identification of good solutions. We have evaluated our new method against the commonly used neighbourhood search optimization techniques: hill climbing and simulated annealing. Our evaluation examines the quality of the graph layout (objective function’s value) and the speed of layout in terms of the number of evaluated solutions required to draw a graph. We also examine the relative scalability of each method. Our experimental results were applied to both random graphs and a real-world dataset. We show that our method outperforms both hill climbing and simulated annealing by producing a better layout in a lower number of evaluated solutions. In addition, we demonstrate that our method has greater scalability as it can layout larger graphs than the state-of-the-art neighbourhood search methods. Finally, we show that similar results can be produced in a real world setting by testing our method against a standard public graph dataset. PMID:29746576

Analysis of Multi-Criteria Evaluation Method of Landfill Site Selection for Municipal Solid Waste Management

NASA Astrophysics Data System (ADS)

Mohammed, Habiba Ibrahim; Majid, Zulkepli; Yusof, Norhakim Bin; Bello Yamusa, Yamusa

2018-03-01

Landfilling remains the most common systematic technique of solid waste disposal in most of the developed and developing countries. Finding a suitable site for landfill is a very challenging task. Landfill site selection process aims to provide suitable areas that will protect the environment and public health from pollution and hazards. Therefore, various factors such as environmental, physical, socio-economic, and geological criteria must be considered before siting any landfill. This makes the site selection process vigorous and tedious because it involves the processing of large amount of spatial data, rules and regulations from different agencies and also policy from decision makers. This allows the incorporation of conflicting objectives and decision maker preferences into spatial decision models. This paper particularly analyzes the multi-criteria evaluation (MCE) method of landfill site selection for solid waste management by means of literature reviews and surveys. The study will help the decision makers and waste management authorities to choose the most effective method when considering landfill site selection.

DA white dwarfs from the LSS-GAC survey DR1: the preliminary luminosity and mass functions and formation rate

NASA Astrophysics Data System (ADS)

Rebassa-Mansergas, A.; Liu, X.-W.; Cojocaru, R.; Yuan, H.-B.; Torres, S.; García-Berro, E.; Xiang, M.-X.; Huang, Y.; Koester, D.; Hou, Y.; Li, G.; Zhang, Y.

2015-06-01

Modern large-scale surveys have allowed the identification of large numbers of white dwarfs. However, these surveys are subject to complicated target selection algorithms, which make it almost impossible to quantify to what extent the observational biases affect the observed populations. The LAMOST (Large Sky Area Multi-Object Fiber Spectroscopic Telescope) Spectroscopic Survey of the Galactic anticentre (LSS-GAC) follows a well-defined set of criteria for selecting targets for observations. This advantage over previous surveys has been fully exploited here to identify a small yet well-characterized magnitude-limited sample of hydrogen-rich (DA) white dwarfs. We derive preliminary LSS-GAC DA white dwarf luminosity and mass functions. The space density and average formation rate of DA white dwarfs we derive are 0.83 ± 0.16 × 10-3 pc-3 and 5.42 ± 0.08 × 10-13 pc-3 yr-1, respectively. Additionally, using an existing Monte Carlo population synthesis code we simulate the population of single DA white dwarfs in the Galactic anticentre, under various assumptions. The synthetic populations are passed through the LSS-GAC selection criteria, taking into account all possible observational biases. This allows us to perform a meaningful comparison of the observed and simulated distributions. We find that the LSS-GAC set of criteria is highly efficient in selecting white dwarfs for spectroscopic observations (80-85 per cent) and that, overall, our simulations reproduce well the observed luminosity function. However, they fail at reproducing an excess of massive white dwarfs present in the observed mass function. A plausible explanation for this is that a sizable fraction of massive white dwarfs in the Galaxy are the product of white dwarf-white dwarf mergers.

[Multi-mathematical modelings for compatibility optimization of Jiangzhi granules].

PubMed

Yang, Ming; Zhang, Li; Ge, Yingli; Lu, Yanliu; Ji, Guang

2011-12-01

To investigate into the method of "multi activity index evaluation and combination optimized of mult-component" for Chinese herbal formulas. According to the scheme of uniform experimental design, efficacy experiment, multi index evaluation, least absolute shrinkage, selection operator (LASSO) modeling, evolutionary optimization algorithm, validation experiment, we optimized the combination of Jiangzhi granules based on the activity indexes of blood serum ALT, ALT, AST, TG, TC, HDL, LDL and TG level of liver tissues, ratio of liver tissue to body. Analytic hierarchy process (AHP) combining with criteria importance through intercriteria correlation (CRITIC) for multi activity index evaluation was more reasonable and objective, it reflected the information of activity index's order and objective sample data. LASSO algorithm modeling could accurately reflect the relationship between different combination of Jiangzhi granule and the activity comprehensive indexes. The optimized combination of Jiangzhi granule showed better values of the activity comprehensive indexed than the original formula after the validation experiment. AHP combining with CRITIC can be used for multi activity index evaluation and LASSO algorithm, it is suitable for combination optimized of Chinese herbal formulas.

Assessment of Material Solutions of Multi-level Garage Structure Within Integrated Life Cycle Design Process

NASA Astrophysics Data System (ADS)

Wałach, Daniel; Sagan, Joanna; Gicala, Magdalena

2017-10-01

The paper presents an environmental and economic analysis of the material solutions of multi-level garage. The construction project approach considered reinforced concrete structure under conditions of use of ordinary concrete and high-performance concrete (HPC). Using of HPC allowed to significant reduction of reinforcement steel, mainly in compression elements (columns) in the construction of the object. The analysis includes elements of the methodology of integrated lice cycle design (ILCD). By making multi-criteria analysis based on established weight of the economic and environmental parameters, three solutions have been evaluated and compared within phase of material production (information modules A1-A3).

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in this case study namely: construction of defense structures, relocation, implementation of an early warning system and spatial planning regulations. Some of the criteria are determined partly in other modules of the CHANGES SDSS, such as the costs for implementation, the risk reduction in monetary values, and societal risk. Other criteria, which could be environmental, economic, cultural, perception in nature, are defined by different stakeholders such as local authorities, expert organizations, private sector, and local public. In the next step, the stakeholders weight the importance of the criteria by pairwise comparison and visualize the decision matrix, which is a matrix based on criteria versus alternatives values. Finally alternatives are ranked by Analytic Hierarchy Process (AHP) method. We expect that this approach will help the decision makers to ease their works and reduce their costs, because the process is more transparent, more accurate and involves a group decision. In that way there will be more confidence in the overall decision making process. Keywords: MCDM, Analytic Hierarchy Process (AHP), SDSS, Natural Hazard Risk Management

Multi-Objective Parallel Test-Sheet Composition Using Enhanced Particle Swarm Optimization

ERIC Educational Resources Information Center

Ho, Tsu-Feng; Yin, Peng-Yeng; Hwang, Gwo-Jen; Shyu, Shyong Jian; Yean, Ya-Nan

2009-01-01

For large-scale tests, such as certification tests or entrance examinations, the composed test sheets must meet multiple assessment criteria. Furthermore, to fairly compare the knowledge levels of the persons who receive tests at different times owing to the insufficiency of available examination halls or the occurrence of certain unexpected…

A Multi-criterial Decision Support System for Forest Management

Treesearch

Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch

1999-01-01

We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...

Decoupling optical function and geometrical form using conformal flexible dielectric metasurfaces

NASA Astrophysics Data System (ADS)

Kamali, Seyedeh Mahsa; Arbabi, Amir; Arbabi, Ehsan; Horie, Yu; Faraon, Andrei

2016-05-01

Physical geometry and optical properties of objects are correlated: cylinders focus light to a line, spheres to a point and arbitrarily shaped objects introduce optical aberrations. Multi-functional components with decoupled geometrical form and optical function are needed when specific optical functionalities must be provided while the shapes are dictated by other considerations like ergonomics, aerodynamics or aesthetics. Here we demonstrate an approach for decoupling optical properties of objects from their physical shape using thin and flexible dielectric metasurfaces which conform to objects' surface and change their optical properties. The conformal metasurfaces are composed of silicon nano-posts embedded in a polymer substrate that locally modify near-infrared (λ=915 nm) optical wavefronts. As proof of concept, we show that cylindrical lenses covered with metasurfaces can be transformed to function as aspherical lenses focusing light to a point. The conformal metasurface concept is highly versatile for developing arbitrarily shaped multi-functional optical devices.

A multi-criteria inference approach for anti-desertification management.

PubMed

Tervonen, Tommi; Sepehr, Adel; Kadziński, Miłosz

2015-10-01

We propose an approach for classifying land zones into categories indicating their resilience against desertification. Environmental management support is provided by a multi-criteria inference method that derives a set of value functions compatible with the given classification examples, and applies them to define, for the rest of the zones, their possible classes. In addition, a representative value function is inferred to explain the relative importance of the criteria to the stakeholders. We use the approach for classifying 28 administrative regions of the Khorasan Razavi province in Iran into three equilibrium classes: collapsed, transition, and sustainable zones. The model is parameterized with enhanced vegetation index measurements from 2005 to 2012, and 7 other natural and anthropogenic indicators for the status of the region in 2012. Results indicate that grazing density and land use changes are the main anthropogenic factors affecting desertification in Khorasan Razavi. The inference procedure suggests that the classification model is underdetermined in terms of attributes, but the approach itself is promising for supporting the management of anti-desertification efforts. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-objective decision-making under uncertainty: Fuzzy logic methods

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1994-01-01

Selecting the best option among alternatives is often a difficult process. This process becomes even more difficult when the evaluation criteria are vague or qualitative, and when the objectives vary in importance and scope. Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

Rooftop greenhouses in educational centers: A sustainability assessment of urban agriculture in compact cities.

PubMed

Nadal, Ana; Pons, Oriol; Cuerva, Eva; Rieradevall, Joan; Josa, Alejandro

2018-06-01

Today, urban agriculture is one of the most widely used sustainability strategies to improve the metabolism of a city. Schools can play an important role in the implementation of sustainability master plans, due their socio-educational activities and their cohesive links with families; all key elements in the development of urban agriculture. Thus, the main objective of this research is to develop a procedure, in compact cities, to assess the potential installation of rooftop greenhouses (RTGs) in schools. The generation of a dynamic assessment tool capable of identifying and prioritizing schools with a high potential for RTGs and their eventual implementation would also represent a significant factor in the environmental, social, and nutritional education of younger generations. The methodology has four-stages (Pre-selection criteria; Selection of necessities; Sustainability analysis; and Sensitivity analysis and selection of the best alternative) in which economic, environmental, social and governance aspects all are considered. It makes use of Multi-Attribute Utility Theory and Multi-Criteria Decision Making, through the Integrated Value Model for Sustainability Assessments and the participation of two panels of multidisciplinary specialists, for the preparation of a unified sustainability index that guarantees the objectivity of the selection process. This methodology has been applied and validated in a case study of 11 schools in Barcelona (Spain). The social perspective of the proposed methodology favored the school in the case-study with the most staff and the largest parent-teacher association (social and governance indicators) that obtained the highest sustainability index (S11); at a considerable distance (45%) from the worst case (S3) with fewer school staff and parental support. Finally, objective decisions may be taken with the assistance of this appropriate, adaptable, and reliable Multi-Criteria Decision-Making tool on the vertical integration and implementation of urban agriculture in schools, in support of the goals of sustainable development and the circular economy. Copyright © 2018 Elsevier B.V. All rights reserved.

Application of multi-criteria decision-making on strategic municipal solid waste management in Dalmatia, Croatia.

PubMed

Vego, Goran; Kucar-Dragicević, Savka; Koprivanac, Natalija

2008-11-01

The efficiency of providing a waste management system in the coastal part of Croatia consisting of four Dalmatian counties has been modelled. Two multi-criteria decision-making (MCDM) methods, PROMETHEE and GAIA, were applied to assist with the systematic analysis and evaluation of the alternatives. The analysis covered two levels; first, the potential number of waste management centres resulting from possible inter-county cooperation; and second, the relative merits of siting of waste management centres in the coastal or hinterland zone was evaluated. The problem was analysed according to several criteria; and ecological, economic, social and functional criteria sets were identified as relevant to the decision-making process. The PROMETHEE and GAIA methods were shown to be efficient tools for analysing the problem considered. Such an approach provided new insights to waste management planning at the strategic level, and gave a reason for rethinking some of the existing strategic waste management documents in Croatia.

Linguistic hesitant fuzzy multi-criteria decision-making method based on evidential reasoning

NASA Astrophysics Data System (ADS)

Zhou, Huan; Wang, Jian-qiang; Zhang, Hong-yu; Chen, Xiao-hong

2016-01-01

Linguistic hesitant fuzzy sets (LHFSs), which can be used to represent decision-makers' qualitative preferences as well as reflect their hesitancy and inconsistency, have attracted a great deal of attention due to their flexibility and efficiency. This paper focuses on a multi-criteria decision-making approach that combines LHFSs with the evidential reasoning (ER) method. After reviewing existing studies of LHFSs, a new order relationship and Hamming distance between LHFSs are introduced and some linguistic scale functions are applied. Then, the ER algorithm is used to aggregate the distributed assessment of each alternative. Subsequently, the set of aggregated alternatives on criteria are further aggregated to get the overall value of each alternative. Furthermore, a nonlinear programming model is developed and genetic algorithms are used to obtain the optimal weights of the criteria. Finally, two illustrative examples are provided to show the feasibility and usability of the method, and comparison analysis with the existing method is made.

Iberian Spanish Function Catalog. Method for Determining Language Objectives and Criteria, Volume VI.

ERIC Educational Resources Information Center

Setzler, Hubert H., Jr.; And Others

This Iberian Spanish Function Catalog presents sentences, phrases, and patterns organized by language functions and functional categories. This catalog is part of the communication/language objectives-based system (C/LOBS), which supports the front-end analysis efforts of the Defense Language Institute Foreign Language Center. The C/LOBS project,…

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

Catchment-wide wetland assessment and prioritization using the multi-criteria decision-making method TOPSIS.

PubMed

Liu, Canran; Frazier, Paul; Kumar, Lalit; Macgregor, Catherine; Blake, Nigel

2006-08-01

It is widely accepted that wetland ecosystems are under threat worldwide. Many communities are now trying to establish wetland rehabilitation programs, but are confounded by a lack of objective information on wetland condition or significance. In this study, a multi-criteria decision-making method, TOPSIS (the Technique for Order Preference by Similarity to Ideal Solution), was adapted to assist in the role of assessing wetland condition and rehabilitation priority in the Clarence River Catchment (New South Wales, Australia). Using 13 GIS data layers that described wetland character, wetland protection, and wetland threats, the wetlands were ranked in terms of condition. Through manipulation of the original model, the wetlands were prioritized for rehabilitation. The method offered a screening tool for the managers in choosing potential candidate wetlands for rehabilitation in a region.

Multi-criteria decision analysis for health technology assessment in Canada: insights from an expert panel discussion.

PubMed

Diaby, Vakaramoko; Goeree, Ron; Hoch, Jeffrey; Siebert, Uwe

2015-02-01

Multi-criteria decision analysis (MCDA), a decision-making tool, has received increasing attention in recent years, notably in the healthcare field. For Canada, it is unclear whether and how MCDA should be incorporated into the existing health technology assessment (HTA) decision-making process. To facilitate debate on improving HTA decision-making in Canada, a workshop was held in conjunction with the 8th World Congress on Health Economics of the International Health Economics Association in Toronto, Canada in July 2011. The objective of the workshop was to discuss the potential benefits and challenges related to the use of MCDA for HTA decision-making in Canada. This paper summarizes and discusses the recommendations of an expert panel convened at the workshop to discuss opportunities and concerns with reference to the implementation of MCDA in Canada.

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

NASA Astrophysics Data System (ADS)

Gardi, Alessandro; Sabatini, Roberto; Ramasamy, Subramanian

2016-05-01

The continuous increase of air transport demand worldwide and the push for a more economically viable and environmentally sustainable aviation are driving significant evolutions of aircraft, airspace and airport systems design and operations. Although extensive research has been performed on the optimisation of aircraft trajectories and very efficient algorithms were widely adopted for the optimisation of vertical flight profiles, it is only in the last few years that higher levels of automation were proposed for integrated flight planning and re-routing functionalities of innovative Communication Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems. In this context, the implementation of additional environmental targets and of multiple operational constraints introduces the need to efficiently deal with multiple objectives as part of the trajectory optimisation algorithm. This article provides a comprehensive review of Multi-Objective Trajectory Optimisation (MOTO) techniques for transport aircraft flight operations, with a special focus on the recent advances introduced in the CNS+A research context. In the first section, a brief introduction is given, together with an overview of the main international research initiatives where this topic has been studied, and the problem statement is provided. The second section introduces the mathematical formulation and the third section reviews the numerical solution techniques, including discretisation and optimisation methods for the specific problem formulated. The fourth section summarises the strategies to articulate the preferences and to select optimal trajectories when multiple conflicting objectives are introduced. The fifth section introduces a number of models defining the optimality criteria and constraints typically adopted in MOTO studies, including fuel consumption, air pollutant and noise emissions, operational costs, condensation trails, airspace and airport operations. A brief overview of atmospheric and weather modelling is also included. Key equations describing the optimality criteria are presented, with a focus on the latest advancements in the respective application areas. In the sixth section, a number of MOTO implementations in the CNS+A systems context are mentioned with relevant simulation case studies addressing different operational tasks. The final section draws some conclusions and outlines guidelines for future research on MOTO and associated CNS+A system implementations.

Algorithm for designing smart factory Industry 4.0

NASA Astrophysics Data System (ADS)

Gurjanov, A. V.; Zakoldaev, D. A.; Shukalov, A. V.; Zharinov, I. O.

2018-03-01

The designing task of production division of the Industry 4.0 item designing company is being studied. The authors proposed an algorithm, which is based on the modified V L Volkovich method. This algorithm allows generating options how to arrange the production with robotized technological equipment functioning in the automatic mode. The optimization solution of the multi-criteria task for some additive criteria is the base of the algorithm.

Multi-criteria decision aid approach for the selection of the best compromise management scheme for ELVs: the case of Cyprus.

PubMed

Mergias, I; Moustakas, K; Papadopoulos, A; Loizidou, M

2007-08-25

Each alternative scheme for treating a vehicle at its end of life has its own consequences from a social, environmental, economic and technical point of view. Furthermore, the criteria used to determine these consequences are often contradictory and not equally important. In the presence of multiple conflicting criteria, an optimal alternative scheme never exists. A multiple-criteria decision aid (MCDA) method to aid the Decision Maker (DM) in selecting the best compromise scheme for the management of End-of-Life Vehicles (ELVs) is presented in this paper. The constitution of a set of alternatives schemes, the selection of a list of relevant criteria to evaluate these alternative schemes and the choice of an appropriate management system are also analyzed in this framework. The proposed procedure relies on the PROMETHEE method which belongs to the well-known family of multiple criteria outranking methods. For this purpose, level, linear and Gaussian functions are used as preference functions.

Multi-Objective Community Detection Based on Memetic Algorithm

PubMed Central

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

Multi-objective community detection based on memetic algorithm.

PubMed

Wu, Peng; Pan, Li

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

Path synthesis of four-bar mechanisms using synergy of polynomial neural network and Stackelberg game theory

NASA Astrophysics Data System (ADS)

Ahmadi, Bahman; Nariman-zadeh, Nader; Jamali, Ali

2017-06-01

In this article, a novel approach based on game theory is presented for multi-objective optimal synthesis of four-bar mechanisms. The multi-objective optimization problem is modelled as a Stackelberg game. The more important objective function, tracking error, is considered as the leader, and the other objective function, deviation of the transmission angle from 90° (TA), is considered as the follower. In a new approach, a group method of data handling (GMDH)-type neural network is also utilized to construct an approximate model for the rational reaction set (RRS) of the follower. Using the proposed game-theoretic approach, the multi-objective optimal synthesis of a four-bar mechanism is then cast into a single-objective optimal synthesis using the leader variables and the obtained RRS of the follower. The superiority of using the synergy game-theoretic method of Stackelberg with a GMDH-type neural network is demonstrated for two case studies on the synthesis of four-bar mechanisms.

Fuzzy Multi-Objective Vendor Selection Problem with Modified S-CURVE Membership Function

NASA Astrophysics Data System (ADS)

Díaz-Madroñero, Manuel; Peidro, David; Vasant, Pandian

2010-06-01

In this paper, the S-Curve membership function methodology is used in a vendor selection (VS) problem. An interactive method for solving multi-objective VS problems with fuzzy goals is developed. The proposed method attempts simultaneously to minimize the total order costs, the number of rejected items and the number of late delivered items with reference to several constraints such as meeting buyers' demand, vendors' capacity, vendors' quota flexibility, vendors' allocated budget, etc. We compare in an industrial case the performance of S-curve membership functions, representing uncertainty goals and constraints in VS problems, with linear membership functions.

Parameter Estimation of Computationally Expensive Watershed Models Through Efficient Multi-objective Optimization and Interactive Decision Analytics

NASA Astrophysics Data System (ADS)

Akhtar, Taimoor; Shoemaker, Christine

2016-04-01

Watershed model calibration is inherently a multi-criteria problem. Conflicting trade-offs exist between different quantifiable calibration criterions indicating the non-existence of a single optimal parameterization. Hence, many experts prefer a manual approach to calibration where the inherent multi-objective nature of the calibration problem is addressed through an interactive, subjective, time-intensive and complex decision making process. Multi-objective optimization can be used to efficiently identify multiple plausible calibration alternatives and assist calibration experts during the parameter estimation process. However, there are key challenges to the use of multi objective optimization in the parameter estimation process which include: 1) multi-objective optimization usually requires many model simulations, which is difficult for complex simulation models that are computationally expensive; and 2) selection of one from numerous calibration alternatives provided by multi-objective optimization is non-trivial. This study proposes a "Hybrid Automatic Manual Strategy" (HAMS) for watershed model calibration to specifically address the above-mentioned challenges. HAMS employs a 3-stage framework for parameter estimation. Stage 1 incorporates the use of an efficient surrogate multi-objective algorithm, GOMORS, for identification of numerous calibration alternatives within a limited simulation evaluation budget. The novelty of HAMS is embedded in Stages 2 and 3 where an interactive visual and metric based analytics framework is available as a decision support tool to choose a single calibration from the numerous alternatives identified in Stage 1. Stage 2 of HAMS provides a goodness-of-fit measure / metric based interactive framework for identification of a small subset (typically less than 10) of meaningful and diverse set of calibration alternatives from the numerous alternatives obtained in Stage 1. Stage 3 incorporates the use of an interactive visual analytics framework for decision support in selection of one parameter combination from the alternatives identified in Stage 2. HAMS is applied for calibration of flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville watershed in upstate New York. Results from the application of HAMS to Cannonsville indicate that efficient multi-objective optimization and interactive visual and metric based analytics can bridge the gap between the effective use of both automatic and manual strategies for parameter estimation of computationally expensive watershed models.

Building a picture: Prioritisation of exotic diseases for the pig industry in Australia using multi-criteria decision analysis.

PubMed

Brookes, V J; Hernández-Jover, M; Cowled, B; Holyoake, P K; Ward, M P

2014-01-01

Diseases that are exotic to the pig industry in Australia were prioritised using a multi-criteria decision analysis framework that incorporated weights of importance for a range of criteria important to industry stakeholders. Measurements were collected for each disease for nine criteria that described potential disease impacts. A total score was calculated for each disease using a weighted sum value function that aggregated the nine disease criterion measurements and weights of importance for the criteria that were previously elicited from two groups of industry stakeholders. One stakeholder group placed most value on the impacts of disease on livestock, and one group placed more value on the zoonotic impacts of diseases. Prioritisation lists ordered by disease score were produced for both of these groups. Vesicular diseases were found to have the highest priority for the group valuing disease impacts on livestock, followed by acute forms of African and classical swine fever, then highly pathogenic porcine reproductive and respiratory syndrome. The group who valued zoonotic disease impacts prioritised rabies, followed by Japanese encephalitis, Eastern equine encephalitis and Nipah virus, interspersed with vesicular diseases. The multi-criteria framework used in this study systematically prioritised diseases using a multi-attribute theory based technique that provided transparency and repeatability in the process. Flexibility of the framework was demonstrated by aggregating the criterion weights from more than one stakeholder group with the disease measurements for the criteria. This technique allowed industry stakeholders to be active in resource allocation for their industry without the need to be disease experts. We believe it is the first prioritisation of livestock diseases using values provided by industry stakeholders. The prioritisation lists will be used by industry stakeholders to identify diseases for further risk analysis and disease spread modelling to understand biosecurity risks to this industry. Copyright © 2013 Elsevier B.V. All rights reserved.

DCMDN: Deep Convolutional Mixture Density Network

NASA Astrophysics Data System (ADS)

D'Isanto, Antonio; Polsterer, Kai Lars

2017-09-01

Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

SU-F-R-46: Predicting Distant Failure in Lung SBRT Using Multi-Objective Radiomics Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Z; Folkert, M; Iyengar, P

2016-06-15

Purpose: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. Methods: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously. The new model is used to predict distant failure in lung SBRT using 52 patients treated at our institute. Quantitative imaging features of PETmore » and CT as well as clinical parameters are utilized to build the predictive model. Image features include intensity features (9), textural features (12) and geometric features (8). Clinical parameters for each patient include demographic parameters (4), tumor characteristics (8), treatment faction schemes (4) and pretreatment medicines (6). The modelling procedure consists of two steps: extracting features from segmented tumors in PET and CT; and selecting features and training model parameters based on multi-objective. Support Vector Machine (SVM) is used as the predictive model, while a nondominated sorting-based multi-objective evolutionary computation algorithm II (NSGA-II) is used for solving the multi-objective optimization. Results: The accuracy for PET, clinical, CT, PET+clinical, PET+CT, CT+clinical, PET+CT+clinical are 71.15%, 84.62%, 84.62%, 85.54%, 82.69%, 84.62%, 86.54%, respectively. The sensitivities for the above seven combinations are 41.76%, 58.33%, 50.00%, 50.00%, 41.67%, 41.67%, 58.33%, while the specificities are 80.00%, 92.50%, 90.00%, 97.50%, 92.50%, 97.50%, 97.50%. Conclusion: A new multi-objective radiomics model for predicting distant failure in NSCLC treated with SBRT was developed. The experimental results show that the best performance can be obtained by combining all features.« less

PGA/MOEAD: a preference-guided evolutionary algorithm for multi-objective decision-making problems with interval-valued fuzzy preferences

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin; Zhong, ShiSheng

2018-02-01

In this research, we propose a preference-guided optimisation algorithm for multi-criteria decision-making (MCDM) problems with interval-valued fuzzy preferences. The interval-valued fuzzy preferences are decomposed into a series of precise and evenly distributed preference-vectors (reference directions) regarding the objectives to be optimised on the basis of uniform design strategy firstly. Then the preference information is further incorporated into the preference-vectors based on the boundary intersection approach, meanwhile, the MCDM problem with interval-valued fuzzy preferences is reformulated into a series of single-objective optimisation sub-problems (each sub-problem corresponds to a decomposed preference-vector). Finally, a preference-guided optimisation algorithm based on MOEA/D (multi-objective evolutionary algorithm based on decomposition) is proposed to solve the sub-problems in a single run. The proposed algorithm incorporates the preference-vectors within the optimisation process for guiding the search procedure towards a more promising subset of the efficient solutions matching the interval-valued fuzzy preferences. In particular, lots of test instances and an engineering application are employed to validate the performance of the proposed algorithm, and the results demonstrate the effectiveness and feasibility of the algorithm.

A game theory-reinforcement learning (GT-RL) method to develop optimal operation policies for multi-operator reservoir systems

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Hooshyar, Milad

2014-11-01

Reservoir systems with multiple operators can benefit from coordination of operation policies. To maximize the total benefit of these systems the literature has normally used the social planner's approach. Based on this approach operation decisions are optimized using a multi-objective optimization model with a compound system's objective. While the utility of the system can be increased this way, fair allocation of benefits among the operators remains challenging for the social planner who has to assign controversial weights to the system's beneficiaries and their objectives. Cooperative game theory provides an alternative framework for fair and efficient allocation of the incremental benefits of cooperation. To determine the fair and efficient utility shares of the beneficiaries, cooperative game theory solution methods consider the gains of each party in the status quo (non-cooperation) as well as what can be gained through the grand coalition (social planner's solution or full cooperation) and partial coalitions. Nevertheless, estimation of the benefits of different coalitions can be challenging in complex multi-beneficiary systems. Reinforcement learning can be used to address this challenge and determine the gains of the beneficiaries for different levels of cooperation, i.e., non-cooperation, partial cooperation, and full cooperation, providing the essential input for allocation based on cooperative game theory. This paper develops a game theory-reinforcement learning (GT-RL) method for determining the optimal operation policies in multi-operator multi-reservoir systems with respect to fairness and efficiency criteria. As the first step to underline the utility of the GT-RL method in solving complex multi-agent multi-reservoir problems without a need for developing compound objectives and weight assignment, the proposed method is applied to a hypothetical three-agent three-reservoir system.

Sustainability assessment of tertiary wastewater treatment technologies: a multi-criteria analysis.

PubMed

Plakas, K V; Georgiadis, A A; Karabelas, A J

2016-01-01

The multi-criteria analysis gives the opportunity to researchers, designers and decision-makers to examine decision options in a multi-dimensional fashion. On this basis, four tertiary wastewater treatment (WWT) technologies were assessed regarding their sustainability performance in producing recycled wastewater, considering a 'triple bottom line' approach (i.e. economic, environmental, and social). These are powdered activated carbon adsorption coupled with ultrafiltration membrane separation (PAC-UF), reverse osmosis, ozone/ultraviolet-light oxidation and heterogeneous photo-catalysis coupled with low-pressure membrane separation (photocatalytic membrane reactor, PMR). The participatory method called simple multi-attribute rating technique exploiting ranks was employed for assigning weights to selected sustainability indicators. This sustainability assessment approach resulted in the development of a composite index as a final metric, for each WWT technology evaluated. The PAC-UF technology appears to be the most appropriate technology, attaining the highest composite value regarding the sustainability performance. A scenario analysis confirmed the results of the original scenario in five out of seven cases. In parallel, the PMR was highlighted as the technology with the least variability in its performance. Nevertheless, additional actions and approaches are proposed to strengthen the objectivity of the final results.

Addressing subjective decision-making inherent in GLUE-based multi-criteria rainfall-runoff model calibration

NASA Astrophysics Data System (ADS)

Shafii, Mahyar; Tolson, Bryan; Shawn Matott, L.

2015-04-01

GLUE is one of the most commonly used informal methodologies for uncertainty estimation in hydrological modelling. Despite the ease-of-use of GLUE, it involves a number of subjective decisions such as the strategy for identifying the behavioural solutions. This study evaluates the impact of behavioural solution identification strategies in GLUE on the quality of model output uncertainty. Moreover, two new strategies are developed to objectively identify behavioural solutions. The first strategy considers Pareto-based ranking of parameter sets, while the second one is based on ranking the parameter sets based on an aggregated criterion. The proposed strategies, as well as the traditional strategies in the literature, are evaluated with respect to reliability (coverage of observations by the envelope of model outcomes) and sharpness (width of the envelope of model outcomes) in different numerical experiments. These experiments include multi-criteria calibration and uncertainty estimation of three rainfall-runoff models with different number of parameters. To demonstrate the importance of behavioural solution identification strategy more appropriately, GLUE is also compared with two other informal multi-criteria calibration and uncertainty estimation methods (Pareto optimization and DDS-AU). The results show that the model output uncertainty varies with the behavioural solution identification strategy, and furthermore, a robust GLUE implementation would require considering multiple behavioural solution identification strategies and choosing the one that generates the desired balance between sharpness and reliability. The proposed objective strategies prove to be the best options in most of the case studies investigated in this research. Implementing such an approach for a high-dimensional calibration problem enables GLUE to generate robust results in comparison with Pareto optimization and DDS-AU.

Rehabilitation after anterior cruciate ligament reconstruction: criteria-based progression through the return-to-sport phase.

PubMed

Myer, Gregory D; Paterno, Mark V; Ford, Kevin R; Quatman, Carmen E; Hewett, Timothy E

2006-06-01

Rehabilitation following anterior cruciate ligament (ACL) reconstruction has undergone a relatively rapid and global evolution over the past 25 years. However, there is an absence of standardized, objective criteria to accurately assess an athlete's ability to progress through the end stages of rehabilitation and safe return to sport. Return-to-sport rehabilitation, progressed by quantitatively measured functional goals, may improve the athlete's integration back into sport participation. The purpose of the following clinical commentary is to introduce an example of a criteria-driven algorithm for progression through return-to-sport rehabilitation following ACL reconstruction. Our criteria-based protocol incorporates a dynamic assessment of baseline limb strength, patient-reported outcomes, functional knee stability, bilateral limb symmetry with functional tasks, postural control, power, endurance, agility, and technique with sport-specific tasks. Although this algorithm has limitations, it serves as a foundation to expand future evidence-based evaluation and to foster critical investigation into the development of objective measures to accurately determine readiness to safely return to sport following injury.

Indication Criteria for Total Knee Arthroplasty in Patients with Osteoarthritis - A Multi-perspective Consensus Study.

PubMed

Schmitt, Jochen; Lange, Toni; Günther, Klaus-Peter; Kopkow, Christian; Rataj, Elisabeth; Apfelbacher, Christian; Aringer, Martin; Böhle, Eckhardt; Bork, Hartmut; Dreinhöfer, Karsten; Friederich, Niklaus; Frosch, Karl-Heinz; Gravius, Sascha; Gromnica-Ihle, Erika; Heller, Karl-Dieter; Kirschner, Stephan; Kladny, Bernd; Kohlhof, Hendrik; Kremer, Michael; Leuchten, Nicolai; Lippmann, Maike; Malzahn, Jürgen; Meyer, Heiko; Sabatowski, Rainer; Scharf, Hanns-Peter; Stoeve, Johannes; Wagner, Richard; Lützner, Jörg

2017-10-01

Background and Objectives Knee osteoarthritis (OA) is a significant public health burden. Rates of total knee arthroplasty (TKA) in OA vary substantially between geographical regions, most likely due to the lack of standardised indication criteria. We set out to define indication criteria for the German healthcare system for TKA in patients with knee OA, on the basis of best evidence and transparent multi-stakeholder consensus. Methods We undertook a complex mixed methods study, including an iterative process of systematic appraisal of existing evidence, Delphi consensus methods and stakeholder conferences. We established a consensus panel representing key German national societies of healthcare providers (orthopaedic surgeons, rheumatologists, pain physicians, psychologists, physiotherapists), payers, and patient representatives. A priori defined consensus criteria were at least 70% agreement and less than 20% disagreement among the consensus panel. Agreement was sought for (1) core indication criteria defined as criteria that must be met to consider TKA in a normal patient with knee OA, (2) additional (not obligatory) indication criteria, (3) absolute contraindication criteria that generally prohibit TKA, and (4) risk factors that do not prohibit TKA, but usually do not lead to a recommendation for TKA. Results The following 5 core indication criteria were agreed within the panel: 1. intermittent (several times per week) or constant knee pain for at least 3 - 6 months; 2. radiological confirmation of structural knee damage (osteoarthritis, osteonecrosis); 3. inadequate response to conservative treatment, including pharmacological and non-pharmacological treatment for at least 3 - 6 months; 4. adverse impact of knee disease on patient's quality of life for at least 3 - 6 months; 5. patient-reported suffering/impairment due to knee disease. Additional indication criteria, contraindication criteria, and risk factors for adverse outcome were also agreed by a large majority within the multi-perspective stakeholder panel. Conclusion The defined indication criteria constitute a prerequisite for appropriate provision of TKA in patients with knee OA in Germany. In eligible patients, shared-decision making should eventually determine if TKA is performed or not. The next important steps are the implementation of the defined indication criteria, and the prospective investigation of predictors of success or failure of TKA in the context of routine care provision in Germany. Georg Thieme Verlag KG Stuttgart · New York.

Inhalation of Simulated Smog Affects Cardiac Function in Mice

EPA Science Inventory

Rationale: The health effects of individual criteria air pollutants have been well investigated. Little is known about health effects of inhaled multi-pollutant mixtures that more realistically represent environmental exposures. The present study was designed to evaluate the card...

Exploring the perspectives and preferences for HTA across German healthcare stakeholders using a multi-criteria assessment of a pulmonary heart sensor as a case study.

PubMed

Wahlster, Philip; Goetghebeur, Mireille; Schaller, Sandra; Kriza, Christine; Kolominsky-Rabas, Peter

2015-04-28

Health technology assessment and healthcare decision-making are based on multiple criteria and evidence, and heterogeneous opinions of participating stakeholders. Multi-criteria decision analysis (MCDA) offers a potential framework to systematize this process and take different perspectives into account. The objectives of this study were to explore perspectives and preferences across German stakeholders when appraising healthcare interventions, using multi-criteria assessment of a heart pulmonary sensor as a case study. An online survey of 100 German healthcare stakeholders was conducted using a comprehensive MCDA framework (EVIDEM V2.2). Participants were asked to provide i) relative weights for each criterion of the framework; ii) performance scores for a health pulmonary sensor, based on available data synthesized for each criterion; and iii) qualitative feedback on the consideration of contextual criteria. Normalized weights and scores were combined using a linear model to calculate a value estimate across different stakeholders. Differences across types of stakeholders were explored. The survey was completed by 54 participants. The most important criteria were efficacy, patient reported outcomes, disease severity, safety, and quality of evidence (relative weight >0.075 each). Compared to all participants, policymakers gave more weight to budget impact and quality of evidence. The quantitative appraisal of a pulmonary heart sensor revealed differences in scoring performance of this intervention at the criteria level between stakeholder groups. The highest value estimate of the sensor reached 0.68 (on a scale of 0 to 1, 1 representing maximum value) for industry representatives and the lowest value of 0.40 was reported for policymakers, compared to 0.48 for all participants. Participants indicated that most qualitative criteria should be considered and their impact on the quantitative appraisal was captured transparently. The study identified important variations in perspectives across German stakeholders when appraising a healthcare intervention and revealed that MCDA can demonstrate the value of a specified technology for all participating stakeholders. Better understanding of these differences at the criteria level, in particular between policymakers and industry representatives, is important to focus innovation aligned with patient health and healthcare system values and constraints.

A comparison of partial order technique with three methods of multi-criteria analysis for ranking of chemical substances.

PubMed

Lerche, Dorte; Brüggemann, Rainer; Sørensen, Peter; Carlsen, Lars; Nielsen, Ole John

2002-01-01

An alternative to the often cumbersome and time-consuming risk assessments of chemical substances could be more reliable and advanced priority setting methods. An elaboration of the simple scoring methods is provided by Hasse Diagram Technique (HDT) and/or Multi-Criteria Analysis (MCA). The present study provides an in depth evaluation of HDT relative to three MCA techniques. The new and main methodological step in the comparison is the use of probability concepts based on mathematical tools such as linear extensions of partially ordered sets and Monte Carlo simulations. A data set consisting of 12 High Production Volume Chemicals (HPVCs) is used for illustration. It is a paradigm in this investigation to claim that the need of external input (often subjective weightings of criteria) should be minimized and that the transparency should be maximized in any multicriteria prioritisation. The study illustrates that the Hasse diagram technique (HDT) needs least external input, is most transparent and is least subjective. However, HDT has some weaknesses if there are criteria which exclude each other. Then weighting is needed. Multi-Criteria Analysis (i.e. Utility Function approach, PROMETHEE and concordance analysis) can deal with such mutual exclusions because their formalisms to quantify preferences allow participation e.g. weighting of criteria. Consequently MCA include more subjectivity and loose transparency. The recommendation which arises from this study is that the first step in decision making is to run HDT and as the second step possibly is to run one of the MCA algorithms.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop.

PubMed

Li, Lian-Hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

PubMed Central

Li, Lian-hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility. PMID:26414758

Fuzzy Multi-Objective Transportation Planning with Modified S-Curve Membership Function

NASA Astrophysics Data System (ADS)

Peidro, D.; Vasant, P.

2009-08-01

In this paper, the S-Curve membership function methodology is used in a transportation planning decision (TPD) problem. An interactive method for solving multi-objective TPD problems with fuzzy goals, available supply and forecast demand is developed. The proposed method attempts simultaneously to minimize the total production and transportation costs and the total delivery time with reference to budget constraints and available supply, machine capacities at each source, as well as forecast demand and warehouse space constraints at each destination. We compare in an industrial case the performance of S-curve membership functions, representing uncertainty goals and constraints in TPD problems, with linear membership functions.

Common modular avionics - Partitioning and design philosophy

NASA Astrophysics Data System (ADS)

Scott, D. M.; Mulvaney, S. P.

The design objectives and definition criteria for common modular hardware that will perform digital processing functions in multiple avionic subsystems are examined. In particular, attention is given to weapon system-level objectives, such as increased supportability, reduced life cycle costs, and increased upgradability. These objectives dictate the following overall modular design goals: reduce test equipment requirements; have a large number of subsystem applications; design for architectural growth; and standardize for technology transparent implementations. Finally, specific partitioning criteria are derived on the basis of the weapon system-level objectives and overall design goals.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

PubMed

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.

Does Maintenance CBT Contribute to Long-Term Treatment Response of Panic Disorder with or without Agoraphobia? A Randomized Controlled Clinical Trial

ERIC Educational Resources Information Center

White, Kamila S.; Payne, Laura A.; Gorman, Jack M.; Shear, M. Katherine; Woods, Scott W.; Saksa, John R.; Barlow, David H.

2013-01-01

Objective: We examined the possibility that maintenance cognitive behavior therapy (M-CBT) may improve the likelihood of sustained improvement and reduced relapse in a multi-site randomized controlled clinical trial of patients who met criteria for panic disorder with or without agoraphobia. Method: Participants were all patients (N = 379) who…

Acoustical considerations for secondary uses of government facilities

NASA Astrophysics Data System (ADS)

Evans, Jack B.

2003-10-01

Government buildings are by their nature, public and multi-functional. Whether in meetings, presentations, documentation processing, work instructions or dispatch, speech communications are critical. Full-time occupancy facilities may require sleep or rest areas adjacent to active spaces. Rooms designed for some other primary use may be used for public assembly, receptions or meetings. In addition, environmental noise impacts to the building or from the building should be considered, especially where adjacent to hospitals, hotels, apartments or other urban sensitive land uses. Acoustical criteria and design parameters for reverberation, background noise and sound isolation should enhance speech intelligibility and privacy. This presentation looks at unusual spaces and unexpected uses of spaces with regard to room acoustics and noise control. Examples of various spaces will be discussed, including an atrium used for reception and assembly, multi-jurisdictional (911) emergency control center, frequent or long-duration use of emergency generators, renovations of historically significant buildings, and the juxtaposition of acoustically incompatible functions. Brief case histories of acoustical requirements, constraints and design solutions will be presented, including acoustical measurements, plan illustrations and photographs. Acoustical criteria for secondary functional uses of spaces will be proposed.

ELICIT: An alternative imprecise weight elicitation technique for use in multi-criteria decision analysis for healthcare

PubMed Central

Diaby, Vakaramoko; Sanogo, Vassiki; Moussa, Kouame Richard

2015-01-01

Objective In this paper, the readers are introduced to ELICIT, an imprecise weight elicitation technique for multicriteria decision analysis for healthcare. Methods The application of ELICIT consists of two steps: the rank ordering of evaluation criteria based on decision-makers’ (DMs) preferences using the principal component analysis; and the estimation of criteria weights and their descriptive statistics using the variable interdependent analysis and the Monte Carlo method. The application of ELICIT is illustrated with a hypothetical case study involving the elicitation of weights for five criteria used to select the best device for eye surgery. Results The criteria were ranked from 1–5, based on a strict preference relationship established by the DMs. For each criterion, the deterministic weight was estimated as well as the standard deviation and 95% credibility interval. Conclusions ELICIT is appropriate in situations where only ordinal DMs’ preferences are available to elicit decision criteria weights. PMID:26361235

Solving a Multi Objective Transportation Problem(MOTP) Under Fuzziness on Using Interval Numbers

NASA Astrophysics Data System (ADS)

Saraj, Mansour; Mashkoorzadeh, Feryal

2010-09-01

In this paper we present a solution procedure of the Multi Objective Transportation Problem(MOTP) where the coefficients of the objective functions, the source and destination parameters which determined by the decision maker(DM) are symmetric triangular fuzzy numbers. The constraints with interval source and destination parameters have been converted in to deterministic ones. A numerical example is provided to illustrate the approach.

Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

NASA Astrophysics Data System (ADS)

Omagari, Hiroki; Higashino, Shin-Ichiro

2018-04-01

In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

Investigation and optimization of performance of nano-scale Stirling refrigerator using working fluid as Maxwell-Boltzmann gases

NASA Astrophysics Data System (ADS)

Ahmadi, Mohammad H.; Amin Nabakhteh, Mohammad; Ahmadi, Mohammad-Ali; Pourfayaz, Fathollah; Bidi, Mokhtar

2017-10-01

The motivation behind this work is to explore a nanoscale irreversible Stirling refrigerator with respect to size impacts and shows two novel thermo-ecological criteria. Two distinct strategies were suggested in the optimization process and the consequences of every strategy were examined independently. In the primary strategy, with the purpose of maximizing the energetic sustainability index and modified the ecological coefficient of performance (MECOP) and minimizing the dimensionless Ecological function, a multi-objective optimization algorithm (MOEA) was used. In the second strategy, with the purpose of maximizing the ECOP and MECOP and minimizing the dimensionless Ecological function, a MOEA was used. To conclude the final solution from each strategy, three proficient decision makers were utilized. Additionally, to quantify the deviation of the results gained from each decision makers, two different statistical error indexes were employed. Finally, based on the comparison between the results achieved from proposed scenarios reveals that by maximizing the MECOP the maximum values of ESI, ECOP, and a minimum of ecfare achieved.

Systemic Sclerosis Classification Criteria: Developing methods for multi-criteria decision analysis with 1000Minds

PubMed Central

Johnson, Sindhu R.; Naden, Raymond P.; Fransen, Jaap; van den Hoogen, Frank; Pope, Janet E.; Baron, Murray; Tyndall, Alan; Matucci-Cerinic, Marco; Denton, Christopher P.; Distler, Oliver; Gabrielli, Armando; van Laar, Jacob M.; Mayes, Maureen; Steen, Virginia; Seibold, James R.; Clements, Phillip; Medsger, Thomas A.; Carreira, Patricia E.; Riemekasten, Gabriela; Chung, Lorinda; Fessler, Barri J.; Merkel, Peter A.; Silver, Richard; Varga, John; Allanore, Yannick; Mueller-Ladner, Ulf; Vonk, Madelon C.; Walker, Ulrich A.; Cappelli, Susanna; Khanna, Dinesh

2014-01-01

Objective Classification criteria for systemic sclerosis (SSc) are being developed. The objectives were to: develop an instrument for collating case-data and evaluate its sensibility; use forced-choice methods to reduce and weight criteria; and explore agreement between experts on the probability that cases were classified as SSc. Study Design and Setting A standardized instrument was tested for sensibility. The instrument was applied to 20 cases covering a range of probabilities that each had SSc. Experts rank-ordered cases from highest to lowest probability; reduced and weighted the criteria using forced-choice methods; and re-ranked the cases. Consistency in rankings was evaluated using intraclass correlation coefficients (ICC). Results Experts endorsed clarity (83%), comprehensibility (100%), face and content validity (100%). Criteria were weighted (points): finger skin thickening (14–22), finger-tip lesions (9–21), friction rubs (21), finger flexion contractures (16), pulmonary fibrosis (14), SSc-related antibodies (15), Raynaud’s phenomenon (13), calcinosis (12), pulmonary hypertension (11), renal crisis (11), telangiectasia (10), abnormal nailfold capillaries (10), esophageal dilation (7) and puffy fingers (5). The ICC across experts was 0.73 (95%CI 0.58,0.86) and improved to 0.80 (95%CI 0.68,0.90). Conclusions Using a sensible instrument and forced-choice methods, the number of criteria were reduced by 39% (23 to 14) and weighted. Our methods reflect the rigors of measurement science, and serves as a template for developing classification criteria. PMID:24721558

An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

NASA Astrophysics Data System (ADS)

Gorsevski, Pece V.; Jankowski, Piotr

2010-08-01

The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

Derivative-free generation and interpolation of convex Pareto optimal IMRT plans

NASA Astrophysics Data System (ADS)

Hoffmann, Aswin L.; Siem, Alex Y. D.; den Hertog, Dick; Kaanders, Johannes H. A. M.; Huizenga, Henk

2006-12-01

In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be considered a multi-objective optimization problem, for which a set of Pareto optimal solutions exists: the Pareto efficient frontier (PEF). In this paper, a constrained optimization method is pursued to iteratively estimate the PEF up to some predefined error. We use the property that the PEF is convex for a convex optimization problem to construct piecewise-linear upper and lower bounds to approximate the PEF from a small initial set of Pareto optimal plans. A derivative-free Sandwich algorithm is presented in which these bounds are used with three strategies to determine the location of the next Pareto optimal solution such that the uncertainty in the estimated PEF is maximally reduced. We show that an intelligent initial solution for a new Pareto optimal plan can be obtained by interpolation of fluence maps from neighbouring Pareto optimal plans. The method has been applied to a simplified clinical test case using two convex objective functions to map the trade-off between tumour dose heterogeneity and critical organ sparing. All three strategies produce representative estimates of the PEF. The new algorithm is particularly suitable for dynamic generation of Pareto optimal plans in interactive treatment planning.

Role of exponential type random invexities for asymptotically sufficient efficiency conditions in semi-infinite multi-objective fractional programming.

PubMed

Verma, Ram U; Seol, Youngsoo

2016-01-01

First a new notion of the random exponential Hanson-Antczak type [Formula: see text]-V-invexity is introduced, which generalizes most of the existing notions in the literature, second a random function [Formula: see text] of the second order is defined, and finally a class of asymptotically sufficient efficiency conditions in semi-infinite multi-objective fractional programming is established. Furthermore, several sets of asymptotic sufficiency results in which various generalized exponential type [Formula: see text]-V-invexity assumptions are imposed on certain vector functions whose components are the individual as well as some combinations of the problem functions are examined and proved. To the best of our knowledge, all the established results on the semi-infinite aspects of the multi-objective fractional programming are new, which is a significantly new emerging field of the interdisciplinary research in nature. We also observed that the investigated results can be modified and applied to several special classes of nonlinear programming problems.

Identification of multi-criteria for supplier selection in IT project outsourcing

NASA Astrophysics Data System (ADS)

Fusiripong, Prashaya; Baharom, Fauziah; Yusof, Yuhanis

2017-10-01

In the increasing global business competitiveness, most organizations have attempted to determine the suitable external parties to support their core and non-core competency, particularly, in IT project outsourcing. The IT supplier selection is required to apply multi-criteria which comprised tangible criteria and intangible criteria in consider optimal IT supplier. Most researches attempted to identify optimal criteria for selecting IT supplier, however, the criteria cannot be the considered common criteria support the variety of IT outsourcing. Therefore, the study aimed to identify a common set of criteria being used in the various types of IT outsourcing. The common criteria are constructed by multi-criteria and success criteria, which were collected by literature review with comprehensive and comparative approach. Consequently, the researchers are able to identify a common set of criteria adopted in the variety of selection problem IT outsourcing supplier.

Implications of proposed fibromyalgia criteria across other functional pain syndromes.

PubMed

Egloff, N; von Känel, R; Müller, V; Egle, U T; Kokinogenis, G; Lederbogen, S; Durrer, B; Stauber, S

2015-01-01

In 2010, the American College of Rheumatology (ACR) proposed new criteria for the diagnosis of fibromyalgia (FM) in the context of objections to components of the criteria of 1990. The new criteria consider the Widespread Pain Index (WPI) and the Symptom Severity Score (SSS). This study evaluated the implications of the new diagnostic criteria for FM across other functional pain syndromes. A cohort of 300 consecutive in-patients with functional pain syndromes underwent a diagnostic screen according to the ACR 2010 criteria. Additionally, systematic pain assessment including algometric and psychometric data was carried out. Twenty-five patients (8.3%) had been diagnosed with FM according to the ACR 1990 criteria. Twenty-one of them (84%) also met the new ACR 2010 criteria. In total, 130 patients (43%) fulfilled the new ACR 2010 criteria. A comparison of new vs. old cases showed a high degree of conformity in most of the pain characteristics. The new FM cases, however, revealed a pronounced heterogeneity in the anatomical pain locations, including several types of localized pain syndromes. Furthermore, patients fulfilling the ACR 2010 FM criteria differed from those with other functional pain syndromes; they had increased pain sensitivity scores and increased psychometric values for depression, anxiety, and psychological distress (p<0.01). FM according to the ACR 2010 criteria describes the 'severe half' of the spectrum of functional pain syndromes. By dropping the requirement of 'generalized pain', these criteria result in a blurring of the distinction between FM and more localized functional pain syndromes.

a Novel Approach to Support Majority Voting in Spatial Group Mcdm Using Density Induced Owa Operator for Seismic Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Moradi, M.; Delavar, M. R.; Moshiri, B.; Khamespanah, F.

2014-10-01

Being one of the most frightening disasters, earthquakes frequently cause huge damages to buildings, facilities and human beings. Although the prediction of characteristics of an earthquake seems to be impossible, its loss and damage is predictable in advance. Seismic loss estimation models tend to evaluate the extent to which the urban areas are vulnerable to earthquakes. Many factors contribute to the vulnerability of urban areas against earthquakes including age and height of buildings, the quality of the materials, the density of population and the location of flammable facilities. Therefore, seismic vulnerability assessment is a multi-criteria problem. A number of multi criteria decision making models have been proposed based on a single expert. The main objective of this paper is to propose a model which facilitates group multi criteria decision making based on the concept of majority voting. The main idea of majority voting is providing a computational tool to measure the degree to which different experts support each other's opinions and make a decision regarding this measure. The applicability of this model is examined in Tehran metropolitan area which is located in a seismically active region. The results indicate that neglecting the experts which get lower degrees of support from others enables the decision makers to avoid the extreme strategies. Moreover, a computational method is proposed to calculate the degree of optimism in the experts' opinions.

Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil.

PubMed

Garfì, Marianna; Ferrer-Martí, Laia; Bonoli, Alessandra; Tondelli, Simona

2011-03-01

Multi-criteria analysis (MCA) is a family of decision-making tools that can be used in strategic environmental assessment (SEA) procedures to ensure that environmental, social and economic aspects are integrated into the design of human development strategies and planning, in order to increase the contribution of the environment and natural resources to poverty reduction. The aim of this paper is to highlight the contribution of a particular multi-criteria technique, the analytic hierarchy process (AHP), in two stages of the SEA procedure applied to water programmes in developing countries: the comparison of alternatives and monitoring. This proposal was validated through its application to a case study in Brazilian semi-arid region. The objective was to select and subsequently monitor the most appropriate programme for safe water availability. On the basis of the SEA results, a project was identified and implemented with successful results. In terms of comparisons of alternatives, AHP meets the requirements of human development programme assessment, including the importance of simplicity, a multidisciplinary and flexible approach, and a focus on the beneficiaries' concerns. With respect to monitoring, the study shows that AHP contributes to SEA by identifying the most appropriate indicators, in order to control the impacts of a project. Copyright © 2010 Elsevier Ltd. All rights reserved.

Multi Criteria Decision Making to evaluate control strategies of contagious animal diseases.

PubMed

Mourits, M C M; van Asseldonk, M A P M; Huirne, R B M

2010-09-01

The decision on which strategy to use in the control of contagious animal diseases involves complex trade-offs between multiple objectives. This paper describes a Multi Criteria Decision Making (MCDM) application to illustrate its potential support to policy makers in choosing the control strategy that best meets all of the conflicting interests. The presented application focused on the evaluation of alternative strategies to control Classical Swine Fever (CSF) epidemics within the European Union (EU) according to the preferences of the European Chief Veterinary Officers (CVO). The performed analysis was centred on the three high-level objectives of epidemiology, economics and social ethics. The appraised control alternatives consisted of the EU compulsory control strategy, a pre-emptive slaughter strategy, a protective vaccination strategy and a suppressive vaccination strategy. Using averaged preference weights of the elicited CVOs, the preference ranking of the control alternatives was determined for six EU regions. The obtained results emphasized the need for EU region-specific control. Individual CVOs differed in their views on the relative importance of the various (sub)criteria by which the performance of the alternatives were judged. Nevertheless, the individual rankings of the control alternatives within a region appeared surprisingly similar. Based on the results of the described application it was concluded that the structuring feature of the MCDM technique provides a suitable tool in assisting the complex decision making process of controlling contagious animal diseases. 2010 Elsevier B.V. All rights reserved.

Multi-camera sensor system for 3D segmentation and localization of multiple mobile robots.

PubMed

Losada, Cristina; Mazo, Manuel; Palazuelos, Sira; Pizarro, Daniel; Marrón, Marta

2010-01-01

This paper presents a method for obtaining the motion segmentation and 3D localization of multiple mobile robots in an intelligent space using a multi-camera sensor system. The set of calibrated and synchronized cameras are placed in fixed positions within the environment (intelligent space). The proposed algorithm for motion segmentation and 3D localization is based on the minimization of an objective function. This function includes information from all the cameras, and it does not rely on previous knowledge or invasive landmarks on board the robots. The proposed objective function depends on three groups of variables: the segmentation boundaries, the motion parameters and the depth. For the objective function minimization, we use a greedy iterative algorithm with three steps that, after initialization of segmentation boundaries and depth, are repeated until convergence.

Control system of the inspection robots group applying auctions and multi-criteria analysis for task allocation

NASA Astrophysics Data System (ADS)

Panfil, Wawrzyniec; Moczulski, Wojciech

2017-10-01

In the paper presented is a control system of a mobile robots group intended for carrying out inspection missions. The main research problem was to define such a control system in order to facilitate a cooperation of the robots resulting in realization of the committed inspection tasks. Many of the well-known control systems use auctions for tasks allocation, where a subject of an auction is a task to be allocated. It seems that in the case of missions characterized by much larger number of tasks than number of robots it will be better if robots (instead of tasks) are subjects of auctions. The second identified problem concerns the one-sided robot-to-task fitness evaluation. Simultaneous assessment of the robot-to-task fitness and task attractiveness for robot should affect positively for the overall effectiveness of the multi-robot system performance. The elaborated system allows to assign tasks to robots using various methods for evaluation of fitness between robots and tasks, and using some tasks allocation methods. There is proposed the method for multi-criteria analysis, which is composed of two assessments, i.e. robot's concurrency position for task among other robots and task's attractiveness for robot among other tasks. Furthermore, there are proposed methods for tasks allocation applying the mentioned multi-criteria analysis method. The verification of both the elaborated system and the proposed tasks' allocation methods was carried out with the help of simulated experiments. The object under test was a group of inspection mobile robots being a virtual counterpart of the real mobile-robot group.

Desired Precision in Multi-Objective Optimization: Epsilon Archiving or Rounding Objectives?

NASA Astrophysics Data System (ADS)

Asadzadeh, M.; Sahraei, S.

2016-12-01

Multi-objective optimization (MO) aids in supporting the decision making process in water resources engineering and design problems. One of the main goals of solving a MO problem is to archive a set of solutions that is well-distributed across a wide range of all the design objectives. Modern MO algorithms use the epsilon dominance concept to define a mesh with pre-defined grid-cell size (often called epsilon) in the objective space and archive at most one solution at each grid-cell. Epsilon can be set to the desired precision level of each objective function to make sure that the difference between each pair of archived solutions is meaningful. This epsilon archiving process is computationally expensive in problems that have quick-to-evaluate objective functions. This research explores the applicability of a similar but computationally more efficient approach to respect the desired precision level of all objectives in the solution archiving process. In this alternative approach each objective function is rounded to the desired precision level before comparing any new solution to the set of archived solutions that already have rounded objective function values. This alternative solution archiving approach is compared to the epsilon archiving approach in terms of efficiency and quality of archived solutions for solving mathematical test problems and hydrologic model calibration problems.

Combined Economic and Hydrologic Modeling to Support Collaborative Decision Making Processes

NASA Astrophysics Data System (ADS)

Sheer, D. P.

2008-12-01

For more than a decade, the core concept of the author's efforts in support of collaborative decision making has been a combination of hydrologic simulation and multi-objective optimization. The modeling has generally been used to support collaborative decision making processes. The OASIS model developed by HydroLogics Inc. solves a multi-objective optimization at each time step using a mixed integer linear program (MILP). The MILP can be configured to include any user defined objective, including but not limited too economic objectives. For example, an estimated marginal value for water for crops and M&I use were included in the objective function to drive trades in a model of the lower Rio Grande. The formulation of the MILP, constraints and objectives, in any time step is conditional: it changes based on the value of state variables and dynamic external forcing functions, such as rainfall, hydrology, market prices, arrival of migratory fish, water temperature, etc. It therefore acts as a dynamic short term multi-objective economic optimization for each time step. MILP is capable of solving a general problem that includes a very realistic representation of the physical system characteristics in addition to the normal multi-objective optimization objectives and constraints included in economic models. In all of these models, the short term objective function is a surrogate for achieving long term multi-objective results. The long term performance for any alternative (especially including operating strategies) is evaluated by simulation. An operating rule is the combination of conditions, parameters, constraints and objectives used to determine the formulation of the short term optimization in each time step. Heuristic wrappers for the simulation program have been developed improve the parameters of an operating rule, and are initiating research on a wrapper that will allow us to employ a genetic algorithm to improve the form of the rule (conditions, constraints, and short term objectives) as well. In the models operating rules represent different models of human behavior, and the objective of the modeling is to find rules for human behavior that perform well in terms of long term human objectives. The conceptual model used to represent human behavior incorporates economic multi-objective optimization for surrogate objectives, and rules that set those objectives based on current conditions and accounting for uncertainty, at least implicitly. The author asserts that real world operating rules follow this form and have evolved because they have been perceived as successful in the past. Thus, the modeling efforts focus on human behavior in much the same way that economic models focus on human behavior. This paper illustrates the above concepts with real world examples.

Multi Objective Optimization of Yarn Quality and Fibre Quality Using Evolutionary Algorithm

NASA Astrophysics Data System (ADS)

Ghosh, Anindya; Das, Subhasis; Banerjee, Debamalya

2013-03-01

The quality and cost of resulting yarn play a significant role to determine its end application. The challenging task of any spinner lies in producing a good quality yarn with added cost benefit. The present work does a multi-objective optimization on two objectives, viz. maximization of cotton yarn strength and minimization of raw material quality. The first objective function has been formulated based on the artificial neural network input-output relation between cotton fibre properties and yarn strength. The second objective function is formulated with the well known regression equation of spinning consistency index. It is obvious that these two objectives are conflicting in nature i.e. not a single combination of cotton fibre parameters does exist which produce maximum yarn strength and minimum cotton fibre quality simultaneously. Therefore, it has several optimal solutions from which a trade-off is needed depending upon the requirement of user. In this work, the optimal solutions are obtained with an elitist multi-objective evolutionary algorithm based on Non-dominated Sorting Genetic Algorithm II (NSGA-II). These optimum solutions may lead to the efficient exploitation of raw materials to produce better quality yarns at low costs.

Initial Studies of the Bidirectional Reflectance Distribution Function of Multi-Walled Carbon Nanotube Structures for Stray Light Control Applications

NASA Technical Reports Server (NTRS)

Butler, J. J.; Tveekrem, J. L.; Quijada, M. A.; Getty, S. A.; Hagopian, J. G.; Georglev, G. T.

2010-01-01

The presentation examines the application of low reflectance surfaces in optical instruments, multi-walled carbon nanotubes (MWCNTs), research objects, MWCNT samples, measurement of 8 deg. directional/hemispherical reflectance, measurement of bidirectional reflectance distribution function (BRDF), and what is current the "blackest ever black".

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics

PubMed Central

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics. PMID:26295151

Calculating and controlling the error of discrete representations of Pareto surfaces in convex multi-criteria optimization.

PubMed

Craft, David

2010-10-01

A discrete set of points and their convex combinations can serve as a sparse representation of the Pareto surface in multiple objective convex optimization. We develop a method to evaluate the quality of such a representation, and show by example that in multiple objective radiotherapy planning, the number of Pareto optimal solutions needed to represent Pareto surfaces of up to five dimensions grows at most linearly with the number of objectives. The method described is also applicable to the representation of convex sets. Copyright © 2009 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

United States Marine Corps Basic Reconnaissance Course: Predictors of Success

DTIC Science & Technology

2017-03-01

PAGE INTENTIONALLY LEFT BLANK 81 VI. CONCLUSIONS AND RECOMMENDATIONS A. CONCLUSIONS The objective of my research is to provide quantitative ...percent over the last three years, illustrating there is room for improvement. This study conducts a quantitative and qualitative analysis of the...criteria used to select candidates for the BRC. The research uses multi-variate logistic regression models and survival analysis to determine to what

Optimal glass-ceramic structures: Components of giant mirror telescopes

NASA Technical Reports Server (NTRS)

Eschenauer, Hans A.

1990-01-01

Detailed investigations are carried out on optimal glass-ceramic mirror structures of terrestrial space technology (optical telescopes). In order to find an optimum design, a nonlinear multi-criteria optimization problem is formulated. 'Minimum deformation' at 'minimum weight' are selected as contradictory objectives, and a set of further constraints (quilting effect, optical faults etc.) is defined and included. A special result of the investigations is described.

Desirability function combining metabolic stability and functionality of peptides.

PubMed

Van Dorpe, Sylvia; Adriaens, Antita; Vermeire, Simon; Polis, Ingeborgh; Peremans, Kathelijne; Spiegeleer, Bart De

2011-05-01

The evaluation of peptides as potential therapeutic or diagnostic agents requires the consideration of several criteria that are targeted around two axes: functionality and metabolic stability. Most often, a compromise has to be made between these mutually opposing characteristics. In this study, Derringer's desirability function, a multi-criteria decision-making method, was applied to determine the best peptide for opioid studies in a single figure-of-merit. The penetration of the blood-brain barrier (BBB) determines the biological functionality of neuropeptides in the brain target tissue, and consists of an influx and an efflux component. The metabolic stability in the two concerned tissues, i.e. plasma and brain, are taken into consideration as well. The overall selection of the peptide drug candidate having the highest BBB-drugability is difficult due to these conflicting responses as well as the different scalings of the four biological parameters under consideration. The highest desirability, representing the best BBB-drugability, was observed for dermorphin. This peptide is thus the most promising drug candidate from the set of eight opioid peptides that were investigated. The least desirable candidate, with the worst BBB influx and/or metabolic stability, was found to be CTAP. Validation of the desirability function by in vivo medical imaging showed that dermorphin and DAMGO penetrate the BBB, whereas EM-1 and TAPP did not. These results are thus consistent with those obtained with the desirability evaluation. To conclude, the multi-criteria decision method was proven to be useful in biomedical research, where a selection of the best candidate based on opposing characteristics is often required. Copyright © 2011 European Peptide Society and John Wiley & Sons, Ltd.

Fuzzy multi-objective optimization case study based on an anaerobic co-digestion process of food waste leachate and piggery wastewater.

PubMed

Choi, Angelo Earvin Sy; Park, Hung Suck

2018-06-20

This paper presents the development and evaluation of fuzzy multi-objective optimization for decision-making that includes the process optimization of anaerobic digestion (AD) process. The operating cost criteria which is a fundamental research gap in previous AD analysis was integrated for the case study in this research. In this study, the mixing ratio of food waste leachate (FWL) and piggery wastewater (PWW), calcium carbonate (CaCO 3 ) and sodium chloride (NaCl) concentrations were optimized to enhance methane production while minimizing operating cost. The results indicated a maximum of 63.3% satisfaction for both methane production and operating cost under the following optimal conditions: mixing ratio (FWL: PWW) - 1.4, CaCO 3 - 2970.5 mg/L and NaCl - 2.7 g/L. In multi-objective optimization, the specific methane yield (SMY) was 239.0 mL CH 4 /g VS added , while 41.2% volatile solids reduction (VSR) was obtained at an operating cost of 56.9 US$/ton. In comparison with the previous optimization study that utilized the response surface methodology, the SMY, VSR and operating cost of the AD process were 310 mL/g, 54% and 83.2 US$/ton, respectively. The results from multi-objective fuzzy optimization proves to show the potential application of this technique for practical decision-making in the process optimization of AD process. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multi-modal trip planning system : Northeastern Illinois Regional Transportation Authority.

DOT National Transportation Integrated Search

2013-01-01

This report evaluates the Multi-Modal Trip Planner System (MMTPS) implemented by the Northeastern Illinois Regional Transportation Authority (RTA) against the specific functional objectives enumerated by the Federal Transit Administration (FTA) in it...

Clinical value of DSM IV and DSM 5 criteria for diagnosing the most prevalent somatoform disorders in patients with medically unexplained physical symptoms (MUPS).

PubMed

van Dessel, Nikki Claassen-; van der Wouden, Johannes C; Dekker, Joost; van der Horst, Henriette E

2016-03-01

This study aimed (1) to describe frequencies of DSM IV somatisation disorder, undifferentiated somatoform disorder and pain disorder versus DSM 5 somatic symptom disorder (SSD) in a multi-setting population of patients with medically unexplained physical symptoms (MUPS), (2) to investigate differences in sociodemographic and (psycho)pathological characteristics between these diagnostic groups and (3) to explore the clinical relevance of the distinction between mild and moderate DSM 5 SSD. We used baseline data of a cohort of 325 MUPS patients. Measurements included questionnaires about symptom severity, physical functioning, anxiety, depression, health anxiety and illness perceptions. These questionnaires were used as proxy measures for operationalization of DSM IV and DSM 5 diagnostic criteria. 92.9% of participants fulfilled criteria of a DSM IV somatoform disorder, while 45.5% fulfilled criteria of DSM 5 SSD. Participants fulfilling criteria of DSM 5 SSD suffered from more severe symptoms than those only fulfilling criteria of a DSM IV somatoform disorder(mean PHQ-15 score of 13.98 (SD 5.17) versus 11.23 (SD 4.71), P-value<0.001). Furthermore their level of physical functioning was significantly lower. Compared to patients with mild SSD, patients with moderate SSD suffered from significantly lower physical functioning and higher levels of depression. Within a population of MUPS patients DSM 5 SSD criteria are more restrictive than DSM IV criteria for somatoform disorders. They are associated with higher symptom severity and lower physical functioning. However, further specification of the positive psychological criteria of DSM 5 SSD may improve utility in research and practice. Copyright © 2016 Elsevier Inc. All rights reserved.

Structural optimization of large structural systems by optimality criteria methods

NASA Technical Reports Server (NTRS)

Berke, Laszlo

1992-01-01

The fundamental concepts of the optimality criteria method of structural optimization are presented. The effect of the separability properties of the objective and constraint functions on the optimality criteria expressions is emphasized. The single constraint case is treated first, followed by the multiple constraint case with a more complex evaluation of the Lagrange multipliers. Examples illustrate the efficiency of the method.

MultiMetEval: Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

PubMed Central

Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko

2012-01-01

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads. PMID:23272111

A fuzzy MCDM approach for evaluating school performance based on linguistic information

NASA Astrophysics Data System (ADS)

Musani, Suhaina; Jemain, Abdul Aziz

2013-11-01

Decision making is the process of finding the best option among the feasible alternatives. This process should consider a variety of criteria, but this study only focus on academic achievement. The data used is the percentage of candidates who obtained Malaysian Certificate of Education (SPM) in Melaka based on school academic achievement for each subject. 57 secondary schools in Melaka as listed by the Ministry of Education involved in this study. Therefore the school ranking can be done using MCDM (Multi Criteria Decision Making) methods. The objective of this study is to develop a rational method for evaluating school performance based on linguistic information. Since the information or level of academic achievement provided in linguistic manner, there is a possible chance of getting incomplete or uncertain problems. So in order to overcome the situation, the information could be provided as fuzzy numbers. Since fuzzy set represents the uncertainty in human perceptions. In this research, VIKOR (Multi Criteria Optimization and Compromise Solution) has been used as a MCDM tool for the school ranking process in fuzzy environment. Results showed that fuzzy set theory can solve the limitations of using MCDM when there is uncertainty problems exist in the data.

Selecting wool-type fabrics for sensorial comfort in women office clothing for the cold season, using the multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Harpa, Rodica

2017-10-01

This article presents the strategy and the procedure used to achieve the declared goal: fabrics selection, pursuing sensorial comfort of a specific women-clothing item, by using the multi-criteria decision analysis. First, the objective evaluation of seven wool-type woven fabrics, suitable to the quality profile expected for the defined destination, was accomplished. Then, a survey was conducted on a sample of 187 consumers, women aged between 18 to 60 years old, with a background in the textile field, regarding both the preferences manifested in purchasing products, and the importance of various sensory perceptions through handling materials used in clothing products. Finally, the MCDM applied through the implementation of previous accomplished software STAT-ADM, allowed choosing the preferred wool-type fabric in order to get the expected sensorial comfort of women office trousers for the cold season, according to the previously established criteria. This overall approach showed good results in fabrics selection for assuring the sensorial comfort in women’s clothing, by using the multicriteria decision analysis based on a rating scale delivered by customers with knowledge in the textile field, but non-experts in the fabrics hand evaluation topic.

Energy crops on landfills: functional, environmental, and costs analysis of different landfill configurations.

PubMed

Pivato, Alberto; Garbo, Francesco; Moretto, Marco; Lavagnolo, Maria Cristina

2018-02-09

The cultivation of energy crops on landfills represents an important challenge for the near future, as the possibility to use devalued sites for energy production is very attractive. In this study, four scenarios have been assessed and compared with respect to a reference case defined for northern Italy. The scenarios were defined taking into consideration current energy crops issues. In particular, the first three scenarios were based on energy maximisation, phytotreatment ability, and environmental impact, respectively. The fourth scenario was a combination of these characteristics emphasised by the previous scenarios. A multi-criteria analysis, based on economic, energetic, and environmental aspects, was performed. From the analysis, the best scenario resulted to be the fourth, with its ability to pursue several objectives simultaneously and obtain the best score relatively to both environmental and energetic criteria. On the contrary, the economic criterion emerges as weak, as all the considered scenarios showed some limits from this point of view. Important indications for future designs can be derived. The decrease of leachate production due to the presence of energy crops on the top cover, which enhances evapotranspiration, represents a favourable but critical aspect in the definition of the results.

Electro-Optic Computing Architectures. Volume I

DTIC Science & Technology

1998-02-01

The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit (OW

A hybrid flower pollination algorithm based modified randomized location for multi-threshold medical image segmentation.

PubMed

Wang, Rui; Zhou, Yongquan; Zhao, Chengyan; Wu, Haizhou

2015-01-01

Multi-threshold image segmentation is a powerful image processing technique that is used for the preprocessing of pattern recognition and computer vision. However, traditional multilevel thresholding methods are computationally expensive because they involve exhaustively searching the optimal thresholds to optimize the objective functions. To overcome this drawback, this paper proposes a flower pollination algorithm with a randomized location modification. The proposed algorithm is used to find optimal threshold values for maximizing Otsu's objective functions with regard to eight medical grayscale images. When benchmarked against other state-of-the-art evolutionary algorithms, the new algorithm proves itself to be robust and effective through numerical experimental results including Otsu's objective values and standard deviations.

Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Hu-Chen; Department of Industrial Engineering and Management, Tokyo Institute of Technology, Tokyo 152-8552; Wu, Jing

Highlights: • Propose a VIKOR-based fuzzy MCDM technique for evaluating HCW disposal methods. • Linguistic variables are used to assess the ratings and weights for the criteria. • The OWA operator is utilized to aggregate individual opinions of decision makers. • A case study is given to illustrate the procedure of the proposed framework. - Abstract: Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires considerationmore » of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include “incineration”, “steam sterilization”, “microwave” and “landfill”. The results obtained using the proposed approach are analyzed in a comparative way.« less

Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

NASA Astrophysics Data System (ADS)

Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

2017-06-01

This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

Optimizing Constrained Single Period Problem under Random Fuzzy Demand

NASA Astrophysics Data System (ADS)

Taleizadeh, Ata Allah; Shavandi, Hassan; Riazi, Afshin

2008-09-01

In this paper, we consider the multi-product multi-constraint newsboy problem with random fuzzy demands and total discount. The demand of the products is often stochastic in the real word but the estimation of the parameters of distribution function may be done by fuzzy manner. So an appropriate option to modeling the demand of products is using the random fuzzy variable. The objective function of proposed model is to maximize the expected profit of newsboy. We consider the constraints such as warehouse space and restriction on quantity order for products, and restriction on budget. We also consider the batch size for products order. Finally we introduce a random fuzzy multi-product multi-constraint newsboy problem (RFM-PM-CNP) and it is changed to a multi-objective mixed integer nonlinear programming model. Furthermore, a hybrid intelligent algorithm based on genetic algorithm, Pareto and TOPSIS is presented for the developed model. Finally an illustrative example is presented to show the performance of the developed model and algorithm.

An application of PSO algorithm for multi-criteria geometry optimization of printed low-pass filters based on conductive periodic structures

NASA Astrophysics Data System (ADS)

Steckiewicz, Adam; Butrylo, Boguslaw

2017-08-01

In this paper we discussed the results of a multi-criteria optimization scheme as well as numerical calculations of periodic conductive structures with selected geometry. Thin printed structures embedded on a flexible dielectric substrate may be applied as simple, cheap, passive low-pass filters with an adjustable cutoff frequency in low (up to 1 MHz) radio frequency range. The analysis of an electromagnetic phenomena in presented structures was realized on the basis of a three-dimensional numerical model of three proposed geometries of periodic elements. The finite element method (FEM) was used to obtain a solution of an electromagnetic harmonic field. Equivalent lumped electrical parameters of printed cells obtained in such manner determine the shape of an amplitude transmission characteristic of a low-pass filter. A nonlinear influence of a printed cell geometry on equivalent parameters of cells electric model, makes it difficult to find the desired optimal solution. Therefore an optimization problem of optimal cell geometry estimation with regard to an approximation of the determined amplitude transmission characteristic with an adjusted cutoff frequency, was obtained by the particle swarm optimization (PSO) algorithm. A dynamically suitable inertia factor was also introduced into the algorithm to improve a convergence to a global extremity of a multimodal objective function. Numerical results as well as PSO simulation results were characterized in terms of approximation accuracy of predefined amplitude characteristics in a pass-band, stop-band and cutoff frequency. Three geometries of varying degrees of complexity were considered and their use in signal processing systems was evaluated.

Evaluation of healthcare waste treatment/disposal alternatives by using multi-criteria decision-making techniques.

PubMed

Özkan, Aysun

2013-02-01

Healthcare waste should be managed carefully because of infected, pathological, etc. content especially in developing countries. Applied management systems must be the most appropriate solution from a technical, environmental, economic and social point of view. The main objective of this study was to analyse the current status of healthcare waste management in Turkey, and to investigate the most appropriate treatment/disposal option by using different decision-making techniques. For this purpose, five different healthcare waste treatment/disposal alternatives including incineration, microwaving, on-site sterilization, off-site sterilization and landfill were evaluated according to two multi-criteria decision-making techniques: analytic network process (ANP) and ELECTRE. In this context, benefits, costs and risks for the alternatives were taken into consideration. Furthermore, the prioritization and ranking of the alternatives were determined and compared for both methods. According to the comparisons, the off-site sterilization technique was found to be the most appropriate solution in both cases.

Russian Function Catalog and Rolebooks. Methods for Determining Language Objectives and Criteria, Volume XIII.

ERIC Educational Resources Information Center

Setzler, Hubert H., Jr.; And Others

A Russian Function Catalog and Instructor and Advisor Rolebooks for Russian are presented. The catalog and rolebooks are part of the communication/language objectives-based system (C/LOBS), which supports the front-end analysis efforts of the Defense Language Institute Foreign Language Center. The C/LOBS projects, which is described in 13 volumes…

Assessing the value of healthcare interventions using multi-criteria decision analysis: a review of the literature.

PubMed

Marsh, Kevin; Lanitis, Tereza; Neasham, David; Orfanos, Panagiotis; Caro, Jaime

2014-04-01

The objective of this study is to support those undertaking a multi-criteria decision analysis (MCDA) by reviewing the approaches adopted in healthcare MCDAs to date, how these varied with the objective of the study, and the lessons learned from this experience. Searches of EMBASE and MEDLINE identified 40 studies that provided 41 examples of MCDA in healthcare. Data were extracted on the objective of the study, methods employed, and decision makers' and study authors' reflections on the advantages and disadvantages of the methods. The recent interest in MCDA in healthcare is mirrored in an increase in the application of MCDA to evaluate healthcare interventions. Of the studies identified, the first was published in 1990, but more than half were published since 2011. They were undertaken in 18 different countries, and were designed to support investment (coverage and reimbursement), authorization, prescription, and research funding allocation decisions. Many intervention types were assessed: pharmaceuticals, public health interventions, screening, surgical interventions, and devices. Most used the value measurement approach and scored performance using predefined scales. Beyond these similarities, a diversity of different approaches were adopted, with only limited correspondence between the approach and the type of decision or product. Decision makers consulted as part of these studies, as well as the authors of the studies are positive about the potential of MCDA to improve decision making. Further work is required, however, to develop guidance for those undertaking MCDA.

An integrated prediction and optimization model of biogas production system at a wastewater treatment facility.

PubMed

Akbaş, Halil; Bilgen, Bilge; Turhan, Aykut Melih

2015-11-01

This study proposes an integrated prediction and optimization model by using multi-layer perceptron neural network and particle swarm optimization techniques. Three different objective functions are formulated. The first one is the maximization of methane percentage with single output. The second one is the maximization of biogas production with single output. The last one is the maximization of biogas quality and biogas production with two outputs. Methane percentage, carbon dioxide percentage, and other contents' percentage are used as the biogas quality criteria. Based on the formulated models and data from a wastewater treatment facility, optimal values of input variables and their corresponding maximum output values are found out for each model. It is expected that the application of the integrated prediction and optimization models increases the biogas production and biogas quality, and contributes to the quantity of electricity production at the wastewater treatment facility. Copyright © 2015 Elsevier Ltd. All rights reserved.

Statin Selection in Qatar Based on Multi-indication Pharmacotherapeutic Multi-criteria Scoring Model, and Clinician Preference.

PubMed

Al-Badriyeh, Daoud; Fahey, Michael; Alabbadi, Ibrahim; Al-Khal, Abdullatif; Zaidan, Manal

2015-12-01

Statin selection for the largest hospital formulary in Qatar is not systematic, not comparative, and does not consider the multi-indication nature of statins. There are no reports in the literature of multi-indication-based comparative scoring models of statins or of statin selection criteria weights that are based primarily on local clinicians' preferences and experiences. This study sought to comparatively evaluate statins for first-line therapy in Qatar, and to quantify the economic impact of this. An evidence-based, multi-indication, multi-criteria pharmacotherapeutic model was developed for the scoring of statins from the perspective of the main health care provider in Qatar. The literature and an expert panel informed the selection criteria of statins. Relative weighting of selection criteria was based on the input of the relevant local clinician population. Statins were comparatively scored based on literature evidence, with those exceeding a defined scoring threshold being recommended for use. With 95% CI and 5% margin of error, the scoring model was successfully developed. Selection criteria comprised 28 subcriteria under the following main criteria: clinical efficacy, best publish evidence and experience, adverse effects, drug interaction, dosing time, and fixed dose combination availability. Outcome measures for multiple indications were related to effects on LDL cholesterol, HDL cholesterol, triglyceride, total cholesterol, and C-reactive protein. Atorvastatin, pravastatin, and rosuvastatin exceeded defined pharmacotherapeutic thresholds. Atorvastatin and pravastatin were recommended as first-line use and rosuvastatin as a nonformulary alternative. It was estimated that this would produce a 17.6% cost savings in statins expenditure. Sensitivity analyses confirmed the robustness of the evaluation's outcomes against input uncertainties. Incorporating a comparative evaluation of statins in Qatari practices based on a locally developed, transparent, multi-indication, multi-criteria scoring model has the potential to considerably reduce expenditures on statins. Atorvastatin and pravastatin should be the first-line statin therapies in the main Qatari health care provider, with rosuvastatin as an alternative. Copyright © 2015 Elsevier HS Journals, Inc. All rights reserved.

A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge.

PubMed

Rahman, M Azizur; Rusteberg, Bernd; Gogu, R C; Lobo Ferreira, J P; Sauter, Martin

2012-05-30

This study reports the development of a new spatial multi-criteria decision analysis (SMCDA) software tool for selecting suitable sites for Managed Aquifer Recharge (MAR) systems. The new SMCDA software tool functions based on the combination of existing multi-criteria evaluation methods with modern decision analysis techniques. More specifically, non-compensatory screening, criteria standardization and weighting, and Analytical Hierarchy Process (AHP) have been combined with Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). This SMCDA tool may be implemented with a wide range of decision maker's preferences. The tool's user-friendly interface helps guide the decision maker through the sequential steps for site selection, those steps namely being constraint mapping, criteria hierarchy, criteria standardization and weighting, and criteria overlay. The tool offers some predetermined default criteria and standard methods to increase the trade-off between ease-of-use and efficiency. Integrated into ArcGIS, the tool has the advantage of using GIS tools for spatial analysis, and herein data may be processed and displayed. The tool is non-site specific, adaptive, and comprehensive, and may be applied to any type of site-selection problem. For demonstrating the robustness of the new tool, a case study was planned and executed at Algarve Region, Portugal. The efficiency of the SMCDA tool in the decision making process for selecting suitable sites for MAR was also demonstrated. Specific aspects of the tool such as built-in default criteria, explicit decision steps, and flexibility in choosing different options were key features, which benefited the study. The new SMCDA tool can be augmented by groundwater flow and transport modeling so as to achieve a more comprehensive approach to the selection process for the best locations of the MAR infiltration basins, as well as the locations of recovery wells and areas of groundwater protection. The new spatial multicriteria analysis tool has already been implemented within the GIS based Gabardine decision support system as an innovative MAR planning tool. Copyright © 2012 Elsevier Ltd. All rights reserved.

Non-linear multi-objective model for planning water-energy modes of Novosibirsk Hydro Power Plant

NASA Astrophysics Data System (ADS)

Alsova, O. K.; Artamonova, A. V.

2018-05-01

This paper presents a non-linear multi-objective model for planning and optimizing of water-energy modes for the Novosibirsk Hydro Power Plant (HPP) operation. There is a very important problem of developing a strategy to improve the scheme of water-power modes and ensure the effective operation of hydropower plants. It is necessary to determine the methods and criteria for the optimal distribution of water resources, to develop a set of models and to apply them to the software implementation of a DSS (decision-support system) for managing Novosibirsk HPP modes. One of the possible versions of the model is presented and investigated in this paper. Experimental study of the model has been carried out with 2017 data and the task of ten-day period planning from April to July (only 12 ten-day periods) was solved.

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

DOE PAGES

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...

2014-10-23

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

Approach to proliferation risk assessment based on multiple objective analysis framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrianov, A.; Kuptsov, I.; Studgorodok 1, Obninsk, Kaluga region, 249030

2013-07-01

The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materialsmore » circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk.« less

Lessons from mouse chimaera experiments with a reiterated transgene marker: revised marker criteria and a review of chimaera markers.

PubMed

Keighren, Margaret A; Flockhart, Jean; Hodson, Benjamin A; Shen, Guan-Yi; Birtley, James R; Notarnicola-Harwood, Antonio; West, John D

2015-08-01

Recent reports of a new generation of ubiquitous transgenic chimaera markers prompted us to consider the criteria used to evaluate new chimaera markers and develop more objective assessment methods. To investigate this experimentally we used several series of fetal and adult chimaeras, carrying an older, multi-copy transgenic marker. We used two additional independent markers and objective, quantitative criteria for cell selection and cell mixing to investigate quantitative and spatial aspects of developmental neutrality. We also suggest how the quantitative analysis we used could be simplified for future use with other markers. As a result, we recommend a five-step procedure for investigators to evaluate new chimaera markers based partly on criteria proposed previously but with a greater emphasis on examining the developmental neutrality of prospective new markers. These five steps comprise (1) review of published information, (2) evaluation of marker detection, (3) genetic crosses to check for effects on viability and growth, (4) comparisons of chimaeras with and without the marker and (5) analysis of chimaeras with both cell populations labelled. Finally, we review a number of different chimaera markers and evaluate them using the extended set of criteria. These comparisons indicate that, although the new generation of ubiquitous fluorescent markers are the best of those currently available and fulfil most of the criteria required of a chimaera marker, further work is required to determine whether they are developmentally neutral.

Getting the most out of additional guidance information in deformable image registration by leveraging multi-objective optimization

NASA Astrophysics Data System (ADS)

Alderliesten, Tanja; Bosman, Peter A. N.; Bel, Arjan

2015-03-01

Incorporating additional guidance information, e.g., landmark/contour correspondence, in deformable image registration is often desirable and is typically done by adding constraints or cost terms to the optimization function. Commonly, deciding between a "hard" constraint and a "soft" additional cost term as well as the weighting of cost terms in the optimization function is done on a trial-and-error basis. The aim of this study is to investigate the advantages of exploiting guidance information by taking a multi-objective optimization perspective. Hereto, next to objectives related to match quality and amount of deformation, we define a third objective related to guidance information. Multi-objective optimization eliminates the need to a-priori tune a weighting of objectives in a single optimization function or the strict requirement of fulfilling hard guidance constraints. Instead, Pareto-efficient trade-offs between all objectives are found, effectively making the introduction of guidance information straightforward, independent of its type or scale. Further, since complete Pareto fronts also contain less interesting parts (i.e., solutions with near-zero deformation effort), we study how adaptive steering mechanisms can be incorporated to automatically focus more on solutions of interest. We performed experiments on artificial and real clinical data with large differences, including disappearing structures. Results show the substantial benefit of using additional guidance information. Moreover, compared to the 2-objective case, additional computational cost is negligible. Finally, with the same computational budget, use of the adaptive steering mechanism provides superior solutions in the area of interest.

General Metals: Grades 7-12.

ERIC Educational Resources Information Center

Instructional Objectives Exchange, Los Angeles, CA.

Ninety objectives and related test items for use in grades 7 through 12 are presented. Each sample contains an objective, test items, and criteria for judging the adequacy of the response. Objectives are organized into the following categories: (1) property of metals; (2) operations and functions; (3) cutting and shearing; (4) filing; (5) cutting…

Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty.

PubMed

Wibowo, Santoso; Deng, Hepu

2015-06-01

This paper presents a multi-criteria group decision making approach for effectively evaluating the performance of e-waste recycling programs under uncertainty in an organization. Intuitionistic fuzzy numbers are used for adequately representing the subjective and imprecise assessments of the decision makers in evaluating the relative importance of evaluation criteria and the performance of individual e-waste recycling programs with respect to individual criteria in a given situation. An interactive fuzzy multi-criteria decision making algorithm is developed for facilitating consensus building in a group decision making environment to ensure that all the interest of individual decision makers have been appropriately considered in evaluating alternative e-waste recycling programs with respect to their corporate sustainability performance. The developed algorithm is then incorporated into a multi-criteria decision support system for making the overall performance evaluation process effectively and simple to use. Such a multi-criteria decision making system adequately provides organizations with a proactive mechanism for incorporating the concept of corporate sustainability into their regular planning decisions and business practices. An example is presented for demonstrating the applicability of the proposed approach in evaluating the performance of e-waste recycling programs in organizations. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Note on the Validity and Reliability of Multi-Criteria Decision Analysis for the Benefit-Risk Assessment of Medicines.

PubMed

Garcia-Hernandez, Alberto

2015-11-01

The comparative evaluation of benefits and risks is one of the most important tasks during the development, market authorization and post-approval pharmacovigilance of medicinal products. Multi-criteria decision analysis (MCDA) has been recommended to support decision making in the benefit-risk assessment (BRA) of medicines. This paper identifies challenges associated with bias or variability that practitioners may encounter in this field and presents solutions to overcome them. The inclusion of overlapping or preference-complementary criteria, which are frequent violations to the assumptions of this model, should be avoided. For each criterion, a value function translates the original outcomes into preference-related scores. Applying non-linear value functions to criteria defined as the risk of suffering a certain event during the study introduces specific risk behaviours in this prescriptive, rather than descriptive, model and is therefore a questionable practice. MCDA uses weights to compare the importance of the model criteria with each other; during their elicitation a frequent situation where (generally favourable) mild effects are directly traded off against low probabilities of suffering (generally unfavourable) severe effects during the study is known to lead to biased and variable weights and ought to be prevented. The way the outcomes are framed during the elicitation process, positively versus negatively for instance, may also lead to differences in the preference weights, warranting an appropriate justification during each implementation. Finally, extending the weighted-sum MCDA model into a fully inferential tool through a probabilistic sensitivity analysis is desirable. However, this task is troublesome and should not ignore that clinical trial endpoints generally are positively correlated.

Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

NASA Astrophysics Data System (ADS)

Qiu, J. P.; Niu, D. X.

Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

Prediction of protein-protein interaction network using a multi-objective optimization approach.

PubMed

Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

2016-06-01

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

Fuzzy approaches to supplier selection problem

NASA Astrophysics Data System (ADS)

Ozkok, Beyza Ahlatcioglu; Kocken, Hale Gonce

2013-09-01

Supplier selection problem is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In the selection process many criteria may conflict with each other, therefore decision-making process becomes complicated. In this study, we handled the supplier selection problem under uncertainty. In this context; we used minimum criterion, arithmetic mean criterion, regret criterion, optimistic criterion, geometric mean and harmonic mean. The membership functions created with the help of the characteristics of used criteria, and we tried to provide consistent supplier selection decisions by using these memberships for evaluating alternative suppliers. During the analysis, no need to use expert opinion is a strong aspect of the methodology used in the decision-making.

Scientific Issues Relevant to Setting Regulatory Criteria to Identify Endocrine-Disrupting Substances in the European Union

PubMed Central

Slama, Rémy; Bourguignon, Jean-Pierre; Demeneix, Barbara; Ivell, Richard; Panzica, Giancarlo; Kortenkamp, Andreas; Zoeller, R. Thomas

2016-01-01

Background: Endocrine disruptors (EDs) are defined by the World Health Organization (WHO) as exogenous compounds or mixtures that alter function(s) of the endocrine system and consequently cause adverse effects in an intact organism, or its progeny, or (sub)populations. European regulations on pesticides, biocides, cosmetics, and industrial chemicals require the European Commission to establish scientific criteria to define EDs. Objectives: We address the scientific relevance of four options for the identification of EDs proposed by the European Commission. Discussion: Option 1, which does not define EDs and leads to using interim criteria unrelated to the WHO definition of EDs, is not relevant. Options 2 and 3 rely on the WHO definition of EDs, which is widely accepted by the scientific community, with option 3 introducing additional categories based on the strength of evidence (suspected EDs and endocrine-active substances). Option 4 adds potency to the WHO definition, as a decision criterion. We argue that potency is dependent on the adverse effect considered and is scientifically ambiguous, and note that potency is not used as a criterion to define other particularly hazardous substances such as carcinogens and reproductive toxicants. The use of potency requires a context that goes beyond hazard identification and corresponds to risk characterization, in which potency (or, more relevantly, the dose–response function) is combined with exposure levels. Conclusions: There is scientific agreement regarding the adequacy of the WHO definition of EDs. The potency concept is not relevant to the identification of particularly serious hazards such as EDs. As is common practice for carcinogens, mutagens, and reproductive toxicants, a multi-level classification of ED based on the WHO definition, and not considering potency, would be relevant (corresponding to option 3 proposed by the European Commission). Citation: Slama R, Bourguignon JP, Demeneix B, Ivell R, Panzica G, Kortenkamp A, Zoeller RT. 2016. Scientific issues relevant to setting regulatory criteria to identify endocrine disrupting substances in the European Union. Environ Health Perspect 124:1497–1503; http://dx.doi.org/10.1289/EHP217 PMID:27108591

Optimal site selection for sitting a solar park using multi-criteria decision analysis and geographical information systems

NASA Astrophysics Data System (ADS)

Georgiou, Andreas; Skarlatos, Dimitrios

2016-07-01

Among the renewable power sources, solar power is rapidly becoming popular because it is inexhaustible, clean, and dependable. It has also become more efficient since the power conversion efficiency of photovoltaic solar cells has increased. Following these trends, solar power will become more affordable in years to come and considerable investments are to be expected. Despite the size of solar plants, the sitting procedure is a crucial factor for their efficiency and financial viability. Many aspects influence such a decision: legal, environmental, technical, and financial to name a few. This paper describes a general integrated framework to evaluate land suitability for the optimal placement of photovoltaic solar power plants, which is based on a combination of a geographic information system (GIS), remote sensing techniques, and multi-criteria decision-making methods. An application of the proposed framework for the Limassol district in Cyprus is further illustrated. The combination of a GIS and multi-criteria methods produces an excellent analysis tool that creates an extensive database of spatial and non-spatial data, which will be used to simplify problems as well as solve and promote the use of multiple criteria. A set of environmental, economic, social, and technical constrains, based on recent Cypriot legislation, European's Union policies, and expert advice, identifies the potential sites for solar park installation. The pairwise comparison method in the context of the analytic hierarchy process (AHP) is applied to estimate the criteria weights in order to establish their relative importance in site evaluation. In addition, four different methods to combine information layers and check their sensitivity were used. The first considered all the criteria as being equally important and assigned them equal weight, whereas the others grouped the criteria and graded them according to their objective perceived importance. The overall suitability of the study region for sitting solar parks is appraised through the summation rule. Strict application of the framework depicts 3.0 % of the study region scoring a best-suitability index for solar resource exploitation, hence minimizing the risk in a potential investment. However, using different weighting schemes for criteria, suitable areas may reach up to 83 % of the study region. The suggested methodological framework applied can be easily utilized by potential investors and renewable energy developers, through a front end web-based application with proper GUI for personalized weighting schemes.

Mandarin Chinese Function Catalog and Rolebook. Method for Determining Language Objectives and Criteria, Volume IX.

ERIC Educational Resources Information Center

Setzler, Hubert H., Jr.; And Others

A Mandarin Chinese Function Catalog and Instructor Rolebook for Mandarin Chinese are presented. The catalog and rolebook are part of the communication/language objectives-based system (C/LOBS), which supports the front-end analysis efforts of the Defense Language Institute Foreign Language Center. The C/LOBS project, which is described in 13…

A measured approach to sustainability and other multi-criteria assessment

EPA Science Inventory

From determining what to have for lunch to deciding where to invest our resources, we, as individuals and societies, are constantly involved in multi-criteria assessment. Using sustainability assessment as a case study, in this talk I will demonstrate the ubiquity of multi-crite...

Criteria for the evaluation of a cloud-based hospital information system outsourcing provider.

PubMed

Low, Chinyao; Hsueh Chen, Ya

2012-12-01

As cloud computing technology has proliferated rapidly worldwide, there has been a trend toward adopting cloud-based hospital information systems (CHISs). This study examines the critical criteria for selecting the CHISs outsourcing provider. The fuzzy Delphi method (FDM) is used to evaluate the primary indicator collected from 188 useable responses at a working hospital in Taiwan. Moreover, the fuzzy analytic hierarchy process (FAHP) is employed to calculate the weights of these criteria and establish a fuzzy multi-criteria model of CHISs outsourcing provider selection from 42 experts. The results indicate that the five most critical criteria related to CHISs outsourcing provider selection are (1) system function, (2) service quality, (3) integration, (4) professionalism, and (5) economics. This study may contribute to understanding how cloud-based hospital systems can reinforce content design and offer a way to compete in the field by developing more appropriate systems.

Electro-Optic Computing Architectures: Volume II. Components and System Design and Analysis

DTIC Science & Technology

1998-02-01

The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit

Optimizing the construction of devices to control inaccesible surfaces - case study

NASA Astrophysics Data System (ADS)

Niţu, E. L.; Costea, A.; Iordache, M. D.; Rizea, A. D.; Babă, Al

2017-10-01

The modern concept for the evolution of manufacturing systems requires multi-criteria optimization of technological processes and equipments, prioritizing associated criteria according to their importance. Technological preparation of the manufacturing can be developed, depending on the volume of production, to the limit of favourable economical effects related to the recovery of the costs for the design and execution of the technological equipment. Devices, as subsystems of the technological system, in the general context of modernization and diversification of machines, tools, semi-finished products and drives, are made in a multitude of constructive variants, which in many cases do not allow their identification, study and improvement. This paper presents a case study in which the multi-criteria analysis of some structures, based on a general optimization method, of novelty character, is used in order to determine the optimal construction variant of a control device. The rational construction of the control device confirms that the optimization method and the proposed calculation methods are correct and determine a different system configuration, new features and functions, and a specific method of working to control inaccessible surfaces.

Stakeholder engagement in dredged material management decisions.

PubMed

Collier, Zachary A; Bates, Matthew E; Wood, Matthew D; Linkov, Igor

2014-10-15

Dredging and disposal issues often become controversial with local stakeholders because of their competing interests. These interests tend to manifest themselves in stakeholders holding onto entrenched positions, and deadlock can result without a methodology to move the stakeholder group past the status quo. However, these situations can be represented as multi-stakeholder, multi-criteria decision problems. In this paper, we describe a case study in which multi-criteria decision analysis was implemented in a multi-stakeholder setting in order to generate recommendations on dredged material placement for Long Island Sound's Dredged Material Management Plan. A working-group of representatives from various stakeholder organizations was formed and consulted to help prioritize sediment placement sites for each dredging center in the region by collaboratively building a multi-criteria decision model. The resulting model framed the problem as several alternatives, criteria, sub-criteria, and metrics relevant to stakeholder interests in the Long Island Sound region. An elicitation of values, represented as criteria weights, was then conducted. Results show that in general, stakeholders tended to agree that all criteria were at least somewhat important, and on average there was strong agreement on the order of preferences among the diverse groups of stakeholders. By developing the decision model iteratively with stakeholders as a group and soliciting their preferences, the process sought to increase stakeholder involvement at the front-end of the prioritization process and lead to increased knowledge and consensus regarding the importance of site-specific criteria. Published by Elsevier B.V.

How learning might strengthen existing visual object representations in human object-selective cortex.

PubMed

Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

2016-02-15

Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

Analysis of 2000 cases treated with gamma knife surgery: validating eligibility criteria for a prospective multi-institutional study of stereotactic radiosurgery alone for treatment of patients with 1-10 brain metastases (JLGK0901) in Japan

PubMed Central

Higuchi, Yoshinori; Nagano, Osamu; Sato, Yasunori; Yamamoto, Masaaki; Ono, Junichi; Saeki, Naokatsu; Miyakawa, Akifumi; Hirai, Tatsuo

2012-01-01

Objective The Japan Leksell Gamma Knife (JLGK) Society has conducted a prospective multi-institute study (JLGK0901, UNIN000001812) for selected patients in order to prove the effectiveness of stereotactic radiosurgery (SRS) alone using the gamma knife (GK) for 1-10 brain lesions. Herein, we verify the validity of 5 major patient selection criteria for the JLGK0901 trial. Materials and Methods Between 1998 and 2010, 2246 consecutive cases with 10352 brain metastases treated with GK were analyzed to determine the validity of the following 5 major JLGK0901 criteria; 1) 1-10 brain lesions, 2) less than 10 cm3 volume of the largest tumor, 3) no more than 15 cm3 total tumor volume, 4) no cerebrospinal fluid (CSF) dissemination, 5) Karnofsky performance status (KPS) score ≥70. Results For cases with >10 brain metastases, salvage treatments for new lesions were needed more frequently. The tumor control rate for lesions larger than 10 cm3 was significantly lower than that of tumors <10 cm3. Overall, neurological and qualitative survivals (OS, NS, QS) of cases with >15 cm3 total tumor volume or positive magnetic resonance imaging findings of CSF were significantly poorer. Outcomes in cases with KPS <70 were significantly poorer in terms of OS. Conclusion Our retrospective results of 2246 GK-treated cases verified the validity of the 5 major JLGK0901 criteria. The inclusion criteria for the JLGK0901 study are appearently good indications for SRS. PMID:29296339

A decision support model for improving a multi-family housing complex based on CO2 emission from electricity consumption.

PubMed

Hong, Taehoon; Koo, Choongwan; Kim, Hyunjoong

2012-12-15

The number of deteriorated multi-family housing complexes in South Korea continues to rise, and consequently their electricity consumption is also increasing. This needs to be addressed as part of the nation's efforts to reduce energy consumption. The objective of this research was to develop a decision support model for determining the need to improve multi-family housing complexes. In this research, 1664 cases located in Seoul were selected for model development. The research team collected the characteristics and electricity energy consumption data of these projects in 2009-2010. The following were carried out in this research: (i) using the Decision Tree, multi-family housing complexes were clustered based on their electricity energy consumption; (ii) using Case-Based Reasoning, similar cases were retrieved from the same cluster; and (iii) using a combination of Multiple Regression Analysis, Artificial Neural Network, and Genetic Algorithm, the prediction performance of the developed model was improved. The results of this research can be used as follows: (i) as basic research data for continuously managing several energy consumption data of multi-family housing complexes; (ii) as advanced research data for predicting energy consumption based on the project characteristics; (iii) as practical research data for selecting the most optimal multi-family housing complex with the most potential in terms of energy savings; and (iv) as consistent and objective criteria for incentives and penalties. Copyright © 2012 Elsevier Ltd. All rights reserved.

Integrated multi-choice goal programming and multi-segment goal programming for supplier selection considering imperfect-quality and price-quantity discounts in a multiple sourcing environment

NASA Astrophysics Data System (ADS)

Chang, Ching-Ter; Chen, Huang-Mu; Zhuang, Zheng-Yun

2014-05-01

Supplier selection (SS) is a multi-criteria and multi-objective problem, in which multi-segment (e.g. imperfect-quality discount (IQD) and price-quantity discount (PQD)) and multi-aspiration level problems may be significantly important; however, little attention had been given to dealing with both of them simultaneously in the past. This study proposes a model for integrating multi-choice goal programming and multi-segment goal programming to solve the above-mentioned problems by providing the following main contributions: (1) it allows decision-makers to set multiple aspiration levels on the right-hand side of each goal to suit real-world situations, (2) the PQD and IQD conditions are considered in the proposed model simultaneously and (3) the proposed model can solve a SS problem with n suppliers where each supplier offers m IQD with r PQD intervals, where only ? extra binary variables are required. The usefulness of the proposed model is explained using a real case. The results indicate that the proposed model not only can deal with a SS problem with multi-segment and multi-aspiration levels, but also can help the decision-maker to find the appropriate order quantities for each supplier by considering cost, quality and delivery.

Structural optimization of framed structures using generalized optimality criteria

NASA Technical Reports Server (NTRS)

Kolonay, R. M.; Venkayya, Vipperla B.; Tischler, V. A.; Canfield, R. A.

1989-01-01

The application of a generalized optimality criteria to framed structures is presented. The optimality conditions, Lagrangian multipliers, resizing algorithm, and scaling procedures are all represented as a function of the objective and constraint functions along with their respective gradients. The optimization of two plane frames under multiple loading conditions subject to stress, displacement, generalized stiffness, and side constraints is presented. These results are compared to those found by optimizing the frames using a nonlinear mathematical programming technique.

Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention

PubMed Central

Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

2015-01-01

Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases. PMID:26295344

Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

PubMed

Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

2015-01-01

Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases.

An integrative multi-criteria decision making techniques for supplier evaluation problem with its application

NASA Astrophysics Data System (ADS)

Fatrias, D.; Kamil, I.; Meilani, D.

2018-03-01

Coordinating business operation with suppliers becomes increasingly important to survive and prosper under the dynamic business environment. A good partnership with suppliers not only increase efficiency, but also strengthen corporate competitiveness. Associated with such concern, this study aims to develop a practical approach of multi-criteria supplier evaluation using combined methods of Taguchi loss function (TLF), best-worst method (BWM) and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR). A new framework of integrative approach adopting these methods is our main contribution for supplier evaluation in literature. In this integrated approach, a compromised supplier ranking list based on the loss score of suppliers is obtained using efficient steps of a pairwise comparison based decision making process. Implemetation to the case problem with real data from crumb rubber industry shows the usefulness of the proposed approach. Finally, a suitable managerial implication is presented.

Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms

NASA Astrophysics Data System (ADS)

Babier, Aaron; Boutilier, Justin J.; Sharpe, Michael B.; McNiven, Andrea L.; Chan, Timothy C. Y.

2018-05-01

We developed and evaluated a novel inverse optimization (IO) model to estimate objective function weights from clinical dose-volume histograms (DVHs). These weights were used to solve a treatment planning problem to generate ‘inverse plans’ that had similar DVHs to the original clinical DVHs. Our methodology was applied to 217 clinical head and neck cancer treatment plans that were previously delivered at Princess Margaret Cancer Centre in Canada. Inverse plan DVHs were compared to the clinical DVHs using objective function values, dose-volume differences, and frequency of clinical planning criteria satisfaction. Median differences between the clinical and inverse DVHs were within 1.1 Gy. For most structures, the difference in clinical planning criteria satisfaction between the clinical and inverse plans was at most 1.4%. For structures where the two plans differed by more than 1.4% in planning criteria satisfaction, the difference in average criterion violation was less than 0.5 Gy. Overall, the inverse plans were very similar to the clinical plans. Compared with a previous inverse optimization method from the literature, our new inverse plans typically satisfied the same or more clinical criteria, and had consistently lower fluence heterogeneity. Overall, this paper demonstrates that DVHs, which are essentially summary statistics, provide sufficient information to estimate objective function weights that result in high quality treatment plans. However, as with any summary statistic that compresses three-dimensional dose information, care must be taken to avoid generating plans with undesirable features such as hotspots; our computational results suggest that such undesirable spatial features were uncommon. Our IO-based approach can be integrated into the current clinical planning paradigm to better initialize the planning process and improve planning efficiency. It could also be embedded in a knowledge-based planning or adaptive radiation therapy framework to automatically generate a new plan given a predicted or updated target DVH, respectively.

Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms.

PubMed

Babier, Aaron; Boutilier, Justin J; Sharpe, Michael B; McNiven, Andrea L; Chan, Timothy C Y

2018-05-10

We developed and evaluated a novel inverse optimization (IO) model to estimate objective function weights from clinical dose-volume histograms (DVHs). These weights were used to solve a treatment planning problem to generate 'inverse plans' that had similar DVHs to the original clinical DVHs. Our methodology was applied to 217 clinical head and neck cancer treatment plans that were previously delivered at Princess Margaret Cancer Centre in Canada. Inverse plan DVHs were compared to the clinical DVHs using objective function values, dose-volume differences, and frequency of clinical planning criteria satisfaction. Median differences between the clinical and inverse DVHs were within 1.1 Gy. For most structures, the difference in clinical planning criteria satisfaction between the clinical and inverse plans was at most 1.4%. For structures where the two plans differed by more than 1.4% in planning criteria satisfaction, the difference in average criterion violation was less than 0.5 Gy. Overall, the inverse plans were very similar to the clinical plans. Compared with a previous inverse optimization method from the literature, our new inverse plans typically satisfied the same or more clinical criteria, and had consistently lower fluence heterogeneity. Overall, this paper demonstrates that DVHs, which are essentially summary statistics, provide sufficient information to estimate objective function weights that result in high quality treatment plans. However, as with any summary statistic that compresses three-dimensional dose information, care must be taken to avoid generating plans with undesirable features such as hotspots; our computational results suggest that such undesirable spatial features were uncommon. Our IO-based approach can be integrated into the current clinical planning paradigm to better initialize the planning process and improve planning efficiency. It could also be embedded in a knowledge-based planning or adaptive radiation therapy framework to automatically generate a new plan given a predicted or updated target DVH, respectively.

The use of multi criteria analysis to compare the operating scenarios of the hybrid generation system of wind turbines, photovoltaic modules and a fuel cell

NASA Astrophysics Data System (ADS)

Ceran, Bartosz

2017-11-01

The paper presents the results of the use of multi-criteria analysis to compare hybrid power generation system collaboration scenarios (HSW) consisting of wind turbines, solar panels and energy storage electrolyzer - PEM type fuel cell with electricity system. The following scenarios were examined: the base S-I-hybrid system powers the off-grid mode receiver, S-II, S-III, S-IV scenarios-electricity system covers 25%, 50%, 75% of energy demand by the recipient. The effect of weights of the above-mentioned criteria on the final result of the multi-criteria analysis was examined.

Multi-Criteria Optimization of Regulation in Metabolic Networks

PubMed Central

Higuera, Clara; Villaverde, Alejandro F.; Banga, Julio R.; Ross, John; Morán, Federico

2012-01-01

Determining the regulation of metabolic networks at genome scale is a hard task. It has been hypothesized that biochemical pathways and metabolic networks might have undergone an evolutionary process of optimization with respect to several criteria over time. In this contribution, a multi-criteria approach has been used to optimize parameters for the allosteric regulation of enzymes in a model of a metabolic substrate-cycle. This has been carried out by calculating the Pareto set of optimal solutions according to two objectives: the proper direction of flux in a metabolic cycle and the energetic cost of applying the set of parameters. Different Pareto fronts have been calculated for eight different “environments” (specific time courses of end product concentrations). For each resulting front the so-called knee point is identified, which can be considered a preferred trade-off solution. Interestingly, the optimal control parameters corresponding to each of these points also lead to optimal behaviour in all the other environments. By calculating the average of the different parameter sets for the knee solutions more frequently found, a final and optimal consensus set of parameters can be obtained, which is an indication on the existence of a universal regulation mechanism for this system.The implications from such a universal regulatory switch are discussed in the framework of large metabolic networks. PMID:22848435

The use of multi-criteria decision analysis to tackle waste management problems: a literature review.

PubMed

Achillas, Charisios; Moussiopoulos, Nicolas; Karagiannidis, Avraam; Banias, Georgias; Perkoulidis, George

2013-02-01

Problems in waste management have become more and more complex during recent decades. The increasing volumes of waste produced and social environmental consciousness present prominent drivers for environmental managers towards the achievement of a sustainable waste management scheme. However, in practice, there are many factors and influences - often mutually conflicting - criteria for finding solutions in real-life applications. This paper presents a review of the literature on multi-criteria decision aiding in waste management problems for all reported waste streams. Despite limitations, which are clearly stated, most of the work published in this field is reviewed. The present review aims to provide environmental managers and decision-makers with a thorough list of practical applications of the multi-criteria decision analysis techniques that are used to solve real-life waste management problems, as well as the criteria that are mostly employed in such applications according to the nature of the problem under study. Moreover, the paper explores the advantages and disadvantages of using multi-criteria decision analysis techniques in waste management problems in comparison to other available alternatives.

Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

NASA Astrophysics Data System (ADS)

Cao, Jia; Yan, Zheng; He, Guangyu

2016-06-01

This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

Man vs. Machine: An interactive poll to evaluate hydrological model performance of a manual and an automatic calibration

NASA Astrophysics Data System (ADS)

Wesemann, Johannes; Burgholzer, Reinhard; Herrnegger, Mathew; Schulz, Karsten

2017-04-01

In recent years, a lot of research in hydrological modelling has been invested to improve the automatic calibration of rainfall-runoff models. This includes for example (1) the implementation of new optimisation methods, (2) the incorporation of new and different objective criteria and signatures in the optimisation and (3) the usage of auxiliary data sets apart from runoff. Nevertheless, in many applications manual calibration is still justifiable and frequently applied. The hydrologist performing the manual calibration, with his expert knowledge, is able to judge the hydrographs simultaneously concerning details but also in a holistic view. This integrated eye-ball verification procedure available to man can be difficult to formulate in objective criteria, even when using a multi-criteria approach. Comparing the results of automatic and manual calibration is not straightforward. Automatic calibration often solely involves objective criteria such as Nash-Sutcliffe Efficiency Coefficient or the Kling-Gupta-Efficiency as a benchmark during the calibration. Consequently, a comparison based on such measures is intrinsically biased towards automatic calibration. Additionally, objective criteria do not cover all aspects of a hydrograph leaving questions concerning the quality of a simulation open. This contribution therefore seeks to examine the quality of manually and automatically calibrated hydrographs by interactively involving expert knowledge in the evaluation. Simulations have been performed for the Mur catchment in Austria with the rainfall-runoff model COSERO using two parameter sets evolved from a manual and an automatic calibration. A subset of resulting hydrographs for observation and simulation, representing the typical flow conditions and events, will be evaluated in this study. In an interactive crowdsourcing approach experts attending the session can vote for their preferred simulated hydrograph without having information on the calibration method that produced the respective hydrograph. Therefore, the result of the poll can be seen as an additional quality criterion for the comparison of the two different approaches and help in the evaluation of the automatic calibration method.

Use of Online Assessment Tools by Instructional Designers-by-Assignment: Necessary Features and Functionalities

ERIC Educational Resources Information Center

Halloran, Jo-Ann

2013-01-01

Government entities set criteria for institutions that have teacher educator programs to use online assessment tools to show continuous ongoing evaluation, and use data from the tools to guide the improvement of courses. The purpose of this qualitative, multi-case study was to discover how Instructional Designers-by-Assignment (IDBA) are using…

Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews.

PubMed

Kuesten, Carla; Bi, Jian

2018-06-03

Conventional drivers of liking analysis was extended with a time dimension into temporal drivers of liking (TDOL) based on functional data analysis methodology and non-additive models for multiple-attribute time-intensity (MATI) data. The non-additive models, which consider both direct effects and interaction effects of attributes to consumer overall liking, include Choquet integral and fuzzy measure in the multi-criteria decision-making, and linear regression based on variance decomposition. Dynamics of TDOL, i.e., the derivatives of the relative importance functional curves were also explored. Well-established R packages 'fda', 'kappalab' and 'relaimpo' were used in the paper for developing TDOL. Applied use of these methods shows that the relative importance of MATI curves offers insights for understanding the temporal aspects of consumer liking for fruit chews.

Study on multimodal transport route under low carbon background

NASA Astrophysics Data System (ADS)

Liu, Lele; Liu, Jie

2018-06-01

Low-carbon environmental protection is the focus of attention around the world, scientists are constantly researching on production of carbon emissions and living carbon emissions. However, there is little literature about multimodal transportation based on carbon emission at home and abroad. Firstly, this paper introduces the theory of multimodal transportation, the multimodal transport models that didn't consider carbon emissions and consider carbon emissions are analyzed. On this basis, a multi-objective programming 0-1 programming model with minimum total transportation cost and minimum total carbon emission is proposed. The idea of weight is applied to Ideal point method for solving problem, multi-objective programming is transformed into a single objective function. The optimal solution of carbon emission to transportation cost under different weights is determined by a single objective function with variable weights. Based on the model and algorithm, an example is given and the results are analyzed.

Sampled-Data Consensus of Linear Multi-agent Systems With Packet Losses.

PubMed

Zhang, Wenbing; Tang, Yang; Huang, Tingwen; Kurths, Jurgen

In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.

Coastal zone management with stochastic multi-criteria analysis.

PubMed

Félix, A; Baquerizo, A; Santiago, J M; Losada, M A

2012-12-15

The methodology for coastal management proposed in this study takes into account the physical processes of the coastal system and the stochastic nature of forcing agents. Simulation techniques are used to assess the uncertainty in the performance of a set of predefined management strategies based on different criteria representing the main concerns of interest groups. This statistical information as well as the distribution function that characterizes the uncertainty regarding the preferences of the decision makers is fed into a stochastic multi-criteria acceptability analysis that provides the probability of alternatives obtaining certain ranks and also calculates the preferences of a typical decision maker who supports an alternative. This methodology was applied as a management solution for Playa Granada in the Guadalfeo River Delta (Granada, Spain), where the construction of a dam in the river basin is causing severe erosion. The analysis of shoreline evolution took into account the coupled action of atmosphere, ocean, and land agents and their intrinsic stochastic character. This study considered five different management strategies. The criteria selected for the analysis were the economic benefits for three interest groups: (i) indirect beneficiaries of tourist activities; (ii) beach homeowners; and (iii) the administration. The strategies were ranked according to their effectiveness, and the relative importance given to each criterion was obtained. Copyright © 2012 Elsevier Ltd. All rights reserved.

a New Multi-Criteria Evaluation Model Based on the Combination of Non-Additive Fuzzy Ahp, Choquet Integral and Sugeno λ-MEASURE

NASA Astrophysics Data System (ADS)

Nadi, S.; Samiei, M.; Salari, H. R.; Karami, N.

2017-09-01

This paper proposes a new model for multi-criteria evaluation under uncertain condition. In this model we consider the interaction between criteria as one of the most challenging issues especially in the presence of uncertainty. In this case usual pairwise comparisons and weighted sum cannot be used to calculate the importance of criteria and to aggregate them. Our model is based on the combination of non-additive fuzzy linguistic preference relation AHP (FLPRAHP), Choquet integral and Sugeno λ-measure. The proposed model capture fuzzy preferences of users and fuzzy values of criteria and uses Sugeno λ -measure to determine the importance of criteria and their interaction. Then, integrating Choquet integral and FLPRAHP, all the interaction between criteria are taken in to account with least number of comparison and the final score for each alternative is determined. So we would model a comprehensive set of interactions between criteria that can lead us to more reliable result. An illustrative example presents the effectiveness and capability of the proposed model to evaluate different alternatives in a multi-criteria decision problem.

Developing the snow component of a distributed hydrological model: a step-wise approach based on multi-objective analysis

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Colohan, R. J. E.

1999-09-01

A snow component has been developed for the distributed hydrological model, DIY, using an approach that sequentially evaluates the behaviour of different functions as they are implemented in the model. The evaluation is performed using multi-objective functions to ensure that the internal structure of the model is correct. The development of the model, using a sub-catchment in the Cairngorm Mountains in Scotland, demonstrated that the degree-day model can be enhanced for hydroclimatic conditions typical of those found in Scotland, without increasing meteorological data requirements. An important element of the snow model is a function to account for wind re-distribution. This causes large accumulations of snow in small pockets, which are shown to be important in sustaining baseflows in the rivers during the late spring and early summer, long after the snowpack has melted from the bulk of the catchment. The importance of the wind function would not have been identified using a single objective function of total streamflow to evaluate the model behaviour.

Stochastic HKMDHE: A multi-objective contrast enhancement algorithm

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Mukhopadhyay, Sabyasachi; Maity, Srideep; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2018-02-01

This contribution proposes a novel extension of the existing `Hyper Kurtosis based Modified Duo-Histogram Equalization' (HKMDHE) algorithm, for multi-objective contrast enhancement of biomedical images. A novel modified objective function has been formulated by joint optimization of the individual histogram equalization objectives. The optimal adequacy of the proposed methodology with respect to image quality metrics such as brightness preserving abilities, peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM) and universal image quality metric has been experimentally validated. The performance analysis of the proposed Stochastic HKMDHE with existing histogram equalization methodologies like Global Histogram Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) has been given for comparative evaluation.

TeraSCREEN: multi-frequency multi-mode Terahertz screening for border checks

NASA Astrophysics Data System (ADS)

Alexander, Naomi E.; Alderman, Byron; Allona, Fernando; Frijlink, Peter; Gonzalo, Ramón; Hägelen, Manfred; Ibáñez, Asier; Krozer, Viktor; Langford, Marian L.; Limiti, Ernesto; Platt, Duncan; Schikora, Marek; Wang, Hui; Weber, Marc Andree

2014-06-01

The challenge for any security screening system is to identify potentially harmful objects such as weapons and explosives concealed under clothing. Classical border and security checkpoints are no longer capable of fulfilling the demands of today's ever growing security requirements, especially with respect to the high throughput generally required which entails a high detection rate of threat material and a low false alarm rate. TeraSCREEN proposes to develop an innovative concept of multi-frequency multi-mode Terahertz and millimeter-wave detection with new automatic detection and classification functionalities. The system developed will demonstrate, at a live control point, the safe automatic detection and classification of objects concealed under clothing, whilst respecting privacy and increasing current throughput rates. This innovative screening system will combine multi-frequency, multi-mode images taken by passive and active subsystems which will scan the subjects and obtain complementary spatial and spectral information, thus allowing for automatic threat recognition. The TeraSCREEN project, which will run from 2013 to 2016, has received funding from the European Union's Seventh Framework Programme under the Security Call. This paper will describe the project objectives and approach.

Multifocal necrotising fasciitis: an overlooked entity?

PubMed

El-Khani, Ussamah; Nehme, Jean; Darwish, Ammar; Jamnadas-Khoda, Benjamin; Scerri, Godwin; Heppell, Simon; Bennett, Nicholas

2012-04-01

The aim of the study is to report a case of multi-focal necrotising fasciitis, review research on this subject to identify common aetiological factors and highlight suggestions to improve management. Necrotising fasciitis is a severe, life-threatening soft tissue infection that typically arises from a single area, usually secondary to a minor penetrating injury. Multi-focal necrotising fasciitis, where there is more than one non-contiguous area of necrosis, is much less commonly reported. There are no guidelines specific to the management of multi-focal necrotising fasciitis, and its under-reporting may lead to missed management opportunities. A systematic literature review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. A search of MEDLINE, OLD MEDLINE and the Cochrane Collaboration was performed from 1966 to March 2011 using 16 search terms. All articles were screened for genuine non-contiguous multi-focal necrotising fasciitis. Of the papers that met this criterion, data on patient demographics, likely inciting injury, presentation time-line, microbial agents, sites affected, objective assessment scores, treatment and outcome were extracted. A total of 31 studies met our inclusion criteria and 33 individual cases of multi-focal necrotising fasciitis were included in the quantitative analysis. About half (52%) of cases were type II necrotising fasciitis; 42% of cases had identifiable inciting injuries; 21% of cases developed multi-focal lesions non-synchronously, of which 86% were type II. Nearly all (94%) of cases had incomplete objective assessment scores. One case identified inflammatory imaging findings prior to clinical necrosis. Multifocality in necrotising fasciitis is likely to be associated with type II disease. We postulate that validated objective tools will aid necrotising fasciitis management pathways that will identify high-risk groups for multifocality and advise early pre-emptive imaging. We recommend the adoption of regional multi-focal necrotising fasciitis registers. Copyright © 2011 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

The impact of expert knowledge on natural hazard susceptibility assessment using spatial multi-criteria analysis

NASA Astrophysics Data System (ADS)

Karlsson, Caroline; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve

2016-04-01

Road and railway networks are one of the key factors to a country's economic growth. Inadequate infrastructural networks could be detrimental to a society if the transport between locations are hindered or delayed. Logistical hindrances can often be avoided whereas natural hindrances are more difficult to control. One natural hindrance that can have a severe adverse effect on both infrastructure and society is flooding. Intense and heavy rainfall events can trigger other natural hazards such as landslides and debris flow. Disruptions caused by landslides are similar to that of floods and increase the maintenance cost considerably. The effect on society by natural disasters is likely to increase due to a changed climate with increasing precipitation. Therefore, there is a need for risk prevention and mitigation of natural hazards. Determining susceptible areas and incorporating them in the decision process may reduce the infrastructural harm. Spatial multi-criteria analysis (SMCA) is a part of decision analysis, which provides a set of procedures for analysing complex decision problems through a Geographic Information System (GIS). The objective and aim of this study was to evaluate the usefulness of expert judgements for inundation, landslide and debris flow susceptibility assessments through a SMCA approach using hydrological, geological and land use factors. The sensitivity of the SMCA model was tested in relation to each perspective and impact on the resulting susceptibility. A least cost path function was used to compare new alternative road lines with the existing ones. This comparison was undertaken to identify the resulting differences in the susceptibility assessments using expert judgements as well as historic incidences of flooding and landslides in order to discuss the usefulness of the model in road planning.

Developing Multi-Dimensional Evaluation Criteria for English Learning Websites with University Students and Professors

ERIC Educational Resources Information Center

Liu, Gi-Zen; Liu, Zih-Hui; Hwang, Gwo-Jen

2011-01-01

Many English learning websites have been developed worldwide, but little research has been conducted concerning the development of comprehensive evaluation criteria. The main purpose of this study is thus to construct a multi-dimensional set of criteria to help learners and teachers evaluate the quality of English learning websites. These…

A method for optimizing multi-objective reservoir operation upon human and riverine ecosystem demands

NASA Astrophysics Data System (ADS)

Ai, Xueshan; Dong, Zuo; Mo, Mingzhu

2017-04-01

The optimal reservoir operation is in generally a multi-objective problem. In real life, most of the reservoir operation optimization problems involve conflicting objectives, for which there is no single optimal solution which can simultaneously gain an optimal result of all the purposes, but rather a set of well distributed non-inferior solutions or Pareto frontier exists. On the other hand, most of the reservoirs operation rules is to gain greater social and economic benefits at the expense of ecological environment, resulting to the destruction of riverine ecology and reduction of aquatic biodiversity. To overcome these drawbacks, this study developed a multi-objective model for the reservoir operating with the conflicting functions of hydroelectric energy generation, irrigation and ecological protection. To solve the model with the objectives of maximize energy production, maximize the water demand satisfaction rate of irrigation and ecology, we proposed a multi-objective optimization method of variable penalty coefficient (VPC), which was based on integrate dynamic programming (DP) with discrete differential dynamic programming (DDDP), to generate a well distributed non-inferior along the Pareto front by changing the penalties coefficient of different objectives. This method was applied to an existing China reservoir named Donggu, through a course of a year, which is a multi-annual storage reservoir with multiple purposes. The case study results showed a good relationship between any two of the objectives and a good Pareto optimal solutions, which provide a reference for the reservoir decision makers.

Risk Factors Associated with Falls in Older Adults with Dementia: A Systematic Review

PubMed Central

Fernando, Eresha; Fraser, Michelle; Hendriksen, Jane; Kim, Corey H.

2017-01-01

Purpose: People with dementia fall more often than cognitively healthy older adults, but their risk factors are not well understood. A review is needed to determine a fall risk profile for this population. The objective was to critically evaluate the literature and identify the factors associated with fall risk in older adults with dementia. Methods: Articles published between January 1988 and October 2014 in EMBASE, PubMed, PsycINFO, and CINAHL were searched. Inclusion criteria were participants aged 55 years or older with dementia or cognitive impairment, prospective cohort design, detailed fall definition, falls as the primary outcome, and multi-variable regression analysis. Two authors independently reviewed and extracted data on study characteristics, quality assessment, and outcomes. Adjusted risk estimates were extracted from the articles. Results: A total of 17 studies met the inclusion criteria. Risk factors were categorized into demographic, balance, gait, vision, functional status, medications, psychosocial, severity of dementia, and other. Risk factors varied with living setting and were not consistent across all studies within a setting. Conclusion: Falls in older adults with dementia are associated with multiple intrinsic and extrinsic risk factors, some shared with older adults in general and others unique to the disease. Risk factors vary between community- and institution-dwelling samples of adults with dementia or cognitive impairment. PMID:28539696

An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

PubMed

Deb, Kalyanmoy; Sinha, Ankur

2010-01-01

Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

Universal approximators for multi-objective direct policy search in water reservoir management problems: a comparative analysis

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Mason, Emanuele; Castelletti, Andrea; Pianosi, Francesca

2014-05-01

The optimal operation of water resources systems is a wide and challenging problem due to non-linearities in the model and the objectives, high dimensional state-control space, and strong uncertainties in the hydroclimatic regimes. The application of classical optimization techniques (e.g., SDP, Q-learning, gradient descent-based algorithms) is strongly limited by the dimensionality of the system and by the presence of multiple, conflicting objectives. This study presents a novel approach which combines Direct Policy Search (DPS) and Multi-Objective Evolutionary Algorithms (MOEAs) to solve high-dimensional state and control space problems involving multiple objectives. DPS, also known as parameterization-simulation-optimization in the water resources literature, is a simulation-based approach where the reservoir operating policy is first parameterized within a given family of functions and, then, the parameters optimized with respect to the objectives of the management problem. The selection of a suitable class of functions to which the operating policy belong to is a key step, as it might restrict the search for the optimal policy to a subspace of the decision space that does not include the optimal solution. In the water reservoir literature, a number of classes have been proposed. However, many of these rules are based largely on empirical or experimental successes and they were designed mostly via simulation and for single-purpose reservoirs. In a multi-objective context similar rules can not easily inferred from the experience and the use of universal function approximators is generally preferred. In this work, we comparatively analyze two among the most common universal approximators: artificial neural networks (ANN) and radial basis functions (RBF) under different problem settings to estimate their scalability and flexibility in dealing with more and more complex problems. The multi-purpose HoaBinh water reservoir in Vietnam, accounting for hydropower production and flood control, is used as a case study. Preliminary results show that the RBF policy parametrization is more effective than the ANN one. In particular, the approximated Pareto front obtained with RBF control policies successfully explores the full tradeoff space between the two conflicting objectives, while most of the ANN solutions results to be Pareto-dominated by the RBF ones.

Structural Optimization of a Force Balance Using a Computational Experiment Design

NASA Technical Reports Server (NTRS)

Parker, P. A.; DeLoach, R.

2002-01-01

This paper proposes a new approach to force balance structural optimization featuring a computational experiment design. Currently, this multi-dimensional design process requires the designer to perform a simplification by executing parameter studies on a small subset of design variables. This one-factor-at-a-time approach varies a single variable while holding all others at a constant level. Consequently, subtle interactions among the design variables, which can be exploited to achieve the design objectives, are undetected. The proposed method combines Modern Design of Experiments techniques to direct the exploration of the multi-dimensional design space, and a finite element analysis code to generate the experimental data. To efficiently search for an optimum combination of design variables and minimize the computational resources, a sequential design strategy was employed. Experimental results from the optimization of a non-traditional force balance measurement section are presented. An approach to overcome the unique problems associated with the simultaneous optimization of multiple response criteria is described. A quantitative single-point design procedure that reflects the designer's subjective impression of the relative importance of various design objectives, and a graphical multi-response optimization procedure that provides further insights into available tradeoffs among competing design objectives are illustrated. The proposed method enhances the intuition and experience of the designer by providing new perspectives on the relationships between the design variables and the competing design objectives providing a systematic foundation for advancements in structural design.

Amplifying Each Patient's Voice: A Systematic Review of Multi-criteria Decision Analyses Involving Patients.

PubMed

Marsh, Kevin; Caro, J Jaime; Hamed, Alaa; Zaiser, Erica

2017-04-01

Qualitative methods tend to be used to incorporate patient preferences into healthcare decision making. However, for patient preferences to be given adequate consideration by decision makers they need to be quantified. Multi-criteria decision analysis (MCDA) is one way to quantify and capture the patient voice. The objective of this review was to report on existing MCDAs involving patients to support the future use of MCDA to capture the patient voice. MEDLINE and EMBASE were searched in June 2014 for English-language papers with no date restriction. The following search terms were used: 'multi-criteria decision*', 'multiple criteria decision*', 'MCDA', 'benefit risk assessment*', 'risk benefit assessment*', 'multicriteri* decision*', 'MCDM', 'multi-criteri* decision*'. Abstracts were included if they reported the application of MCDA to assess healthcare interventions where patients were the source of weights. Abstracts were excluded if they did not apply MCDA, such as discussions of how MCDA could be used; or did not evaluate healthcare interventions, such as MCDAs to assess the level of health need in a locality. Data were extracted on weighting method, variation in patient and expert preferences, and discussion on different weighting techniques. The review identified ten English-language studies that reported an MCDA to assess healthcare interventions and involved patients as a source of weights. These studies reported 12 applications of MCDA. Different methods of preference elicitation were employed: direct weighting in workshops; discrete choice experiment surveys; and the analytical hierarchy process using both workshops and surveys. There was significant heterogeneity in patient responses and differences between patients, who put greater weight on disease characteristics and treatment convenience, and experts, who put more weight on efficacy. The studies highlighted cognitive challenges associated with some weighting methods, though patients' views on their ability to undertake weighting tasks was positive. This review identified several recent examples of MCDA used to elicit patient preferences, which support the feasibility of using MCDA to capture the patient voice. Challenges identified included, how best to reflect the heterogeneity of patient preferences in decision making and how to manage the cognitive burden associated with some MCDA tasks.

OBJECT REPRESENTATION, IDENTITY, AND THE PARADOX OF EARLY PERMANENCE: Steps Toward a New Framework.

PubMed

Meltzoff, Andrew N; Moore, M Keith

1998-01-01

The sensorimotor theory of infancy has been overthrown, but there is little consensus on a replacement. We hypothesize that a capacity for representation is the starting point for infant development, not its culmination. Logical distinctions are drawn between object representation, identity, and permanence. Modern experiments on early object permanence and deferred imitation suggest: (a) even for young infants, representations persist over breaks in sensory contact, (b) numerical identity of objects ( O s) is initially specified by spatiotemporal criteria (place and trajectory), (c) featural and functional identity criteria develop, (d) events are analyzed by comparing representations to current perception, and (e) representation operates both prospectively, anticipating future contacts with an O , and retrospectively, reidentifying an O as the "same one again." A model of the architecture and functioning of the early representational system is proposed. It accounts for young infants' behavior toward absent people and things in terms of their efforts to determine the identity of objects. Our proposal is developmental without denying innate structure and elevates the power of perception and representation while being cautious about attributing complex concepts to young infants.

OBJECT REPRESENTATION, IDENTITY, AND THE PARADOX OF EARLY PERMANENCE: Steps Toward a New Framework

PubMed Central

Meltzoff, Andrew N.; Moore, M. Keith

2013-01-01

The sensorimotor theory of infancy has been overthrown, but there is little consensus on a replacement. We hypothesize that a capacity for representation is the starting point for infant development, not its culmination. Logical distinctions are drawn between object representation, identity, and permanence. Modern experiments on early object permanence and deferred imitation suggest: (a) even for young infants, representations persist over breaks in sensory contact, (b) numerical identity of objects (Os) is initially specified by spatiotemporal criteria (place and trajectory), (c) featural and functional identity criteria develop, (d) events are analyzed by comparing representations to current perception, and (e) representation operates both prospectively, anticipating future contacts with an O, and retrospectively, reidentifying an O as the “same one again.” A model of the architecture and functioning of the early representational system is proposed. It accounts for young infants’ behavior toward absent people and things in terms of their efforts to determine the identity of objects. Our proposal is developmental without denying innate structure and elevates the power of perception and representation while being cautious about attributing complex concepts to young infants. PMID:25147418

Identification of dusty massive stars in star-forming dwarf irregular galaxies in the Local Group with mid-IR photometry

NASA Astrophysics Data System (ADS)

Britavskiy, N. E.; Bonanos, A. Z.; Mehner, A.; Boyer, M. L.; McQuinn, K. B. W.

2015-12-01

Context. Increasing the statistics of spectroscopically confirmed evolved massive stars in the Local Group enables the investigation of the mass loss phenomena that occur in these stars in the late stages of their evolution. Aims: We aim to complete the census of luminous mid-IR sources in star-forming dwarf irregular (dIrr) galaxies of the Local Group. To achieve this we employed mid-IR photometric selection criteria to identify evolved massive stars, such as red supergiants (RSGs) and luminous blue variables (LBVs), by using the fact that these types of stars have infrared excess due to dust. Methods: The method is based on 3.6 μm and 4.5 μm photometry from archival Spitzer Space Telescope images of nearby galaxies. We applied our criteria to four dIrr galaxies: Pegasus, Phoenix, Sextans A, and WLM, selecting 79 point sources that we observed with the VLT/FORS2 spectrograph in multi-object spectroscopy mode. Results: We identified 13 RSGs, of which 6 are new discoveries, as well as two new emission line stars, and one candidate yellow supergiant. Among the other observed objects we identified carbon stars, foreground giants, and background objects, such as a quasar and an early-type galaxy that contaminate our survey. We use the results of our spectroscopic survey to revise the mid-IR and optical selection criteria for identifying RSGs from photometric measurements. The optical selection criteria are more efficient in separating extragalactic RSGs from foreground giants than mid-IR selection criteria, but the mid-IR selection criteria are useful for identifying dusty stars in the Local Group. This work serves as a basis for further investigation of the newly discovered dusty massive stars and their host galaxies. Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme IDs 090.D-0009 and 091.D-0010.Appendix A is available in electronic form at http://www.aanda.org

Life cycle tools combined with multi-criteria and participatory methods for agricultural sustainability: Insights from a systematic and critical review.

PubMed

De Luca, Anna Irene; Iofrida, Nathalie; Leskinen, Pekka; Stillitano, Teodora; Falcone, Giacomo; Strano, Alfio; Gulisano, Giovanni

2017-10-01

Life cycle (LC) methodologies have attracted a great interest in agricultural sustainability assessments, even if, at the same time, they have sometimes been criticized for making unrealistic assumptions and subjective choices. To cope with these weaknesses, Multi-Criteria Decision Analysis (MCDA) and/or participatory methods can be used to balance and integrate different sustainability dimensions. The purpose of this study is to highlight how life cycle approaches were combined with MCDA and participatory methods to address agricultural sustainability in the published scientific literature. A systematic and critical review was developed, highlighting the following features: which multi-criterial and/or participatory methods have been associated with LC tools; how they have been integrated or complemented (methodological relationships); the intensity of the involvement of stakeholders (degree of participation); and which synergies have been achieved by combining the methods. The main typology of integration was represented by multi-criterial frameworks integrating LC evaluations. LC tools can provide MCDA studies with local and global information on how to reduce negative impacts and avoid burden shifts, while MCDA methods can help LC practitioners deal with subjective assumptions in an objective way, to take into consideration actors' values and to overcome trade-offs among the different dimensions of sustainability. Considerations concerning the further development of Life Cycle Sustainability Assessment (LCSA) have been identified as well. Copyright © 2017 Elsevier B.V. All rights reserved.

An optimization model to design and manage subsurface drip irrigation system for alfalfa

NASA Astrophysics Data System (ADS)

Kandelous, M.; Kamai, T.; Vrugt, J. A.; Simunek, J.; Hanson, B.; Hopmans, J. W.

2010-12-01

Subsurface drip irrigation (SDI) is one of the most efficient and cost-effective methods for watering alfalfa plants. Lateral installation depth and distance, emitter discharge, and irrigation time and frequency of SDI, in addition to soil and climatic conditions affect alfalfa’s root water uptake and yield. Here we use a multi-objective optimization approach to find optimal SDI strategies. Our approach uses the AMALGAM evolutionary search method, in combination with the HYDRUS-2D unsaturated flow model to maximize water uptake by alfalfa’s plant roots, and minimize loss of irrigation and drainage water to the atmosphere or groundwater. We use a variety of different objective functions to analyze SDI. These criteria include the lateral installation depth and distance, the lateral discharge, irrigation duration, and irrigation frequency. Our framework includes explicit recognition of the soil moisture status during the simulation period to make sure that the top soil is dry for harvesting during the growing season. Initial results show a wide spectrum of optimized SDI strategies for different root distributions, soil textures and climate conditions. The developed tool should be useful in helping farmers optimize their irrigation strategy and design.

Performance assessment and optimization of an irreversible nano-scale Stirling engine cycle operating with Maxwell-Boltzmann gas

NASA Astrophysics Data System (ADS)

Ahmadi, Mohammad H.; Ahmadi, Mohammad-Ali; Pourfayaz, Fathollah

2015-09-01

Developing new technologies like nano-technology improves the performance of the energy industries. Consequently, emerging new groups of thermal cycles in nano-scale can revolutionize the energy systems' future. This paper presents a thermo-dynamical study of a nano-scale irreversible Stirling engine cycle with the aim of optimizing the performance of the Stirling engine cycle. In the Stirling engine cycle the working fluid is an Ideal Maxwell-Boltzmann gas. Moreover, two different strategies are proposed for a multi-objective optimization issue, and the outcomes of each strategy are evaluated separately. The first strategy is proposed to maximize the ecological coefficient of performance (ECOP), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F . Furthermore, the second strategy is suggested to maximize the thermal efficiency ( η), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F). All the strategies in the present work are executed via a multi-objective evolutionary algorithms based on NSGA∥ method. Finally, to achieve the final answer in each strategy, three well-known decision makers are executed. Lastly, deviations of the outcomes gained in each strategy and each decision maker are evaluated separately.

Combination of uncertainty theories and decision-aiding methods for natural risk management in a context of imperfect information

NASA Astrophysics Data System (ADS)

Tacnet, Jean-Marc; Dupouy, Guillaume; Carladous, Simon; Dezert, Jean; Batton-Hubert, Mireille

2017-04-01

In mountain areas, natural phenomena such as snow avalanches, debris-flows and rock-falls, put people and objects at risk with sometimes dramatic consequences. Risk is classically considered as a combination of hazard, the combination of the intensity and frequency of the phenomenon, and vulnerability which corresponds to the consequences of the phenomenon on exposed people and material assets. Risk management consists in identifying the risk level as well as choosing the best strategies for risk prevention, i.e. mitigation. In the context of natural phenomena in mountainous areas, technical and scientific knowledge is often lacking. Risk management decisions are therefore based on imperfect information. This information comes from more or less reliable sources ranging from historical data, expert assessments, numerical simulations etc. Finally, risk management decisions are the result of complex knowledge management and reasoning processes. Tracing the information and propagating information quality from data acquisition to decisions are therefore important steps in the decision-making process. One major goal today is therefore to assist decision-making while considering the availability, quality and reliability of information content and sources. A global integrated framework is proposed to improve the risk management process in a context of information imperfection provided by more or less reliable sources: uncertainty as well as imprecision, inconsistency and incompleteness are considered. Several methods are used and associated in an original way: sequential decision context description, development of specific multi-criteria decision-making methods, imperfection propagation in numerical modeling and information fusion. This framework not only assists in decision-making but also traces the process and evaluates the impact of information quality on decision-making. We focus and present two main developments. The first one relates to uncertainty and imprecision propagation in numerical modeling using both classical Monte-Carlo probabilistic approach and also so-called Hybrid approach using possibility theory. Second approach deals with new multi-criteria decision-making methods which consider information imperfection, source reliability, importance and conflict, using fuzzy sets as well as possibility and belief function theories. Implemented methods consider information imperfection propagation and information fusion in total aggregation methods such as AHP (Saaty, 1980) or partial aggregation methods such as the Electre outranking method (see Soft Electre Tri ) or decisions in certain but also risky or uncertain contexts (see new COWA-ER and FOWA-ER- Cautious and Fuzzy Ordered Weighted Averaging-Evidential Reasoning). For example, the ER-MCDA methodology considers expert assessment as a multi-criteria decision process based on imperfect information provided by more or less heterogeneous, reliable and conflicting sources: it mixes AHP, fuzzy sets theory, possibility theory and belief function theory using DSmT (Dezert-Smarandache Theory) framework which provides powerful fusion rules.

Multi-criteria decision analysis of breast cancer control in low- and middle- income countries: development of a rating tool for policy makers.

PubMed

Venhorst, Kristie; Zelle, Sten G; Tromp, Noor; Lauer, Jeremy A

2014-01-01

The objective of this study was to develop a rating tool for policy makers to prioritize breast cancer interventions in low- and middle- income countries (LMICs), based on a simple multi-criteria decision analysis (MCDA) approach. The definition and identification of criteria play a key role in MCDA, and our rating tool could be used as part of a broader priority setting exercise in a local setting. This tool may contribute to a more transparent priority-setting process and fairer decision-making in future breast cancer policy development. First, an expert panel (n = 5) discussed key considerations for tool development. A literature review followed to inventory all relevant criteria and construct an initial set of criteria. A Delphi study was then performed and questionnaires used to discuss a final list of criteria with clear definitions and potential scoring scales. For this Delphi study, multiple breast cancer policy and priority-setting experts from different LMICs were selected and invited by the World Health Organization. Fifteen international experts participated in all three Delphi rounds to assess and evaluate each criterion. This study resulted in a preliminary rating tool for assessing breast cancer interventions in LMICs. The tool consists of 10 carefully crafted criteria (effectiveness, quality of the evidence, magnitude of individual health impact, acceptability, cost-effectiveness, technical complexity, affordability, safety, geographical coverage, and accessibility), with clear definitions and potential scoring scales. This study describes the development of a rating tool to assess breast cancer interventions in LMICs. Our tool can offer supporting knowledge for the use or development of rating tools as part of a broader (MCDA based) priority setting exercise in local settings. Further steps for improving the tool are proposed and should lead to its useful adoption in LMICs.

Sociodemographic correlates of cognition in the multi-ethnic study of atherosclerosis (MESA)

USDA-ARS?s Scientific Manuscript database

Our objective was to describe the methodology utilized to evaluate cognitive function in the Multi-Ethnic Study of Atherosclerosis (MESA) and to present preliminary results by age, sex, and race/ethnicity. Cross-sectional measurements of a prospective observational cohort. Residents of 6 U.S. commun...

A Integrated Service Platform for Remote Sensing Image 3D Interpretation and Draughting based on HTML5

NASA Astrophysics Data System (ADS)

LIU, Yiping; XU, Qing; ZhANG, Heng; LV, Liang; LU, Wanjie; WANG, Dandi

2016-11-01

The purpose of this paper is to solve the problems of the traditional single system for interpretation and draughting such as inconsistent standards, single function, dependence on plug-ins, closed system and low integration level. On the basis of the comprehensive analysis of the target elements composition, map representation and similar system features, a 3D interpretation and draughting integrated service platform for multi-source, multi-scale and multi-resolution geospatial objects is established based on HTML5 and WebGL, which not only integrates object recognition, access, retrieval, three-dimensional display and test evaluation but also achieves collection, transfer, storage, refreshing and maintenance of data about Geospatial Objects and shows value in certain prospects and potential for growth.

Implications of Preference and Problem Formulation on the Operating Policies of Complex Multi-Reservoir Systems

NASA Astrophysics Data System (ADS)

Quinn, J.; Reed, P. M.; Giuliani, M.; Castelletti, A.

2016-12-01

Optimizing the operations of multi-reservoir systems poses several challenges: 1) the high dimension of the problem's states and controls, 2) the need to balance conflicting multi-sector objectives, and 3) understanding how uncertainties impact system performance. These difficulties motivated the development of the Evolutionary Multi-Objective Direct Policy Search (EMODPS) framework, in which multi-reservoir operating policies are parameterized in a given family of functions and then optimized for multiple objectives through simulation over a set of stochastic inputs. However, properly framing these objectives remains a severe challenge and a neglected source of uncertainty. Here, we use EMODPS to optimize operating policies for a 4-reservoir system in the Red River Basin in Vietnam, exploring the consequences of optimizing to different sets of objectives related to 1) hydropower production, 2) meeting multi-sector water demands, and 3) providing flood protection to the capital city of Hanoi. We show how coordinated operation of the reservoirs can differ markedly depending on how decision makers weigh these concerns. Moreover, we illustrate how formulation choices that emphasize the mean, tail, or variability of performance across objective combinations must be evaluated carefully. Our results show that these choices can significantly improve attainable system performance, or yield severe unintended consequences. Finally, we show that satisfactory validation of the operating policies on a set of out-of-sample stochastic inputs depends as much or more on the formulation of the objectives as on effective optimization of the policies. These observations highlight the importance of carefully considering how we abstract stakeholders' objectives and of iteratively optimizing and visualizing multiple problem formulation hypotheses to ensure that we capture the most important tradeoffs that emerge from different stakeholder preferences.

Supplemental design requirements document, Multifunction Waste Tank Facility, Project W-236A. Revision 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groth, B.D.

The Multi-Function Waste Tank Facility (MWTF) consists of four, nominal 1 million gallon, underground double-shell tanks, located in the 200-East area, and two tanks of the same capacity in the 200-West area. MWTF will provide environmentally safe storage capacity for wastes generated during remediation/retrieval activities of existing waste storage tanks. This document delineates in detail the information to be used for effective implementation of the Functional Design Criteria requirements.

Regression analysis as a design optimization tool

NASA Technical Reports Server (NTRS)

Perley, R.

1984-01-01

The optimization concepts are described in relation to an overall design process as opposed to a detailed, part-design process where the requirements are firmly stated, the optimization criteria are well established, and a design is known to be feasible. The overall design process starts with the stated requirements. Some of the design criteria are derived directly from the requirements, but others are affected by the design concept. It is these design criteria that define the performance index, or objective function, that is to be minimized within some constraints. In general, there will be multiple objectives, some mutually exclusive, with no clear statement of their relative importance. The optimization loop that is given adjusts the design variables and analyzes the resulting design, in an iterative fashion, until the objective function is minimized within the constraints. This provides a solution, but it is only the beginning. In effect, the problem definition evolves as information is derived from the results. It becomes a learning process as we determine what the physics of the system can deliver in relation to the desirable system characteristics. As with any learning process, an interactive capability is a real attriubute for investigating the many alternatives that will be suggested as learning progresses.

GIS and Multi-criteria evaluation (MCE) for landform geodiversity assessment

NASA Astrophysics Data System (ADS)

Najwer, Alicja; Reynard, Emmanuel; Zwoliński, Zbigniew

2014-05-01

In geomorphology, at the contemporary stage of methodology and methodological development, it is very significant to undertake new research problems, from theoretical and application point of view. As an example of applying geoconservation results in landscape studies and environmental conservation one can refer to the problem of the landform geodiversity. The concept of geodiversity was created relatively recently and, therefore, little progress has been made in its objective assessment and mapping. In order to ensure clarity and coherency, it is recommended that the evaluation process to be rigorous. Multi-criteria evaluation meets these criteria well. The main objective of this presentation is to demonstrate a new methodology for the assessment of the selected natural environment components in response to the definition of geodiversity, as well as visualization of the landforms geodiversity, using the opportunities offered by the geoinformation environment. The study area consists of two peculiar alpine valleys: Illgraben and Derborence, located in the Swiss Alps. Apart from glacial and fluvial landforms, the morphology of these two sites is largely due to the extreme phenomena(rockslides, torrential processes). Both valleys are recognized as geosites of national importance. The basis of the assessment is the selection of the geographical environment features. Firstly, six factor maps were prepared for each area: the landform energy, the landform fragmentation, the contemporary landform preservation, geological settings and hydrographic elements (lakes and streams). Input maps were then standardized and resulted from map algebra operations carried out by multi-criteria evaluation (MCE) with GIS-based Weighted Sum technique. Weights for particular classes were calculated using pair-comparison matrixes method. The final stage of deriving landform geodiversity maps was the reclassification procedure with the use of natural breaks method. The final maps of landform geodiversity were generated with the use of the same methodological algorithm and multiplication of each factor map by its given weight with consistency ratio = 0.07. However, the results that were obtained were radically different. The map of geodiversity for Derborence is characterized by much more significant fragmentation. Areas of low geodiveristy constitute a greater contribution. In the Illgraben site, there is a significant contribution of high and very high geodiversity classes. The obtained maps were reviewed during the field exploration with positive results, which gives a basis to conclude that the methodology used is correct and can be applied for other similar areas. Therefore, it is very important to develop an objective methodology that can be implemented for areas at the local and regional scale, but also giving satisfactory results for areas with a landscape different from the alpine one. The maps of landform geodiversity may be used for environment conservation management, preservation of specific features within the geosite perimeter, spatial planning or tourism management.

A Parameter Estimation Scheme for Multiscale Kalman Smoother (MKS) Algorithm Used in Precipitation Data Fusion

NASA Technical Reports Server (NTRS)

Wang, Shugong; Liang, Xu

2013-01-01

A new approach is presented in this paper to effectively obtain parameter estimations for the Multiscale Kalman Smoother (MKS) algorithm. This new approach has demonstrated promising potentials in deriving better data products based on data of different spatial scales and precisions. Our new approach employs a multi-objective (MO) parameter estimation scheme (called MO scheme hereafter), rather than using the conventional maximum likelihood scheme (called ML scheme) to estimate the MKS parameters. Unlike the ML scheme, the MO scheme is not simply built on strict statistical assumptions related to prediction errors and observation errors, rather, it directly associates the fused data of multiple scales with multiple objective functions in searching best parameter estimations for MKS through optimization. In the MO scheme, objective functions are defined to facilitate consistency among the fused data at multiscales and the input data at their original scales in terms of spatial patterns and magnitudes. The new approach is evaluated through a Monte Carlo experiment and a series of comparison analyses using synthetic precipitation data. Our results show that the MKS fused precipitation performs better using the MO scheme than that using the ML scheme. Particularly, improvements are significant compared to that using the ML scheme for the fused precipitation associated with fine spatial resolutions. This is mainly due to having more criteria and constraints involved in the MO scheme than those included in the ML scheme. The weakness of the original ML scheme that blindly puts more weights onto the data associated with finer resolutions is overcome in our new approach.

Supplier Selection Using Weighted Utility Additive Method

NASA Astrophysics Data System (ADS)

Karande, Prasad; Chakraborty, Shankar

2015-10-01

Supplier selection is a multi-criteria decision-making (MCDM) problem which mainly involves evaluating a number of available suppliers according to a set of common criteria for choosing the best one to meet the organizational needs. For any manufacturing or service organization, selecting the right upstream suppliers is a key success factor that will significantly reduce purchasing cost, increase downstream customer satisfaction and improve competitive ability. The past researchers have attempted to solve the supplier selection problem employing different MCDM techniques which involve active participation of the decision makers in the decision-making process. This paper deals with the application of weighted utility additive (WUTA) method for solving supplier selection problems. The WUTA method, an extension of utility additive approach, is based on ordinal regression and consists of building a piece-wise linear additive decision model from a preference structure using linear programming (LP). It adopts preference disaggregation principle and addresses the decision-making activities through operational models which need implicit preferences in the form of a preorder of reference alternatives or a subset of these alternatives present in the process. The preferential preorder provided by the decision maker is used as a restriction of a LP problem, which has its own objective function, minimization of the sum of the errors associated with the ranking of each alternative. Based on a given reference ranking of alternatives, one or more additive utility functions are derived. Using these utility functions, the weighted utilities for individual criterion values are combined into an overall weighted utility for a given alternative. It is observed that WUTA method, having a sound mathematical background, can provide accurate ranking to the candidate suppliers and choose the best one to fulfill the organizational requirements. Two real time examples are illustrated to prove its applicability and appropriateness in solving supplier selection problems.

Use of nonsteroidal anti-inflammatory drugs and renal failure in nursing home residents-results of the study "Inappropriate Medication in Patients with Renal Insufficiency in Nursing Homes".

PubMed

Dörks, Michael; Herget-Rosenthal, Stefan; Schmiemann, Guido; Hoffmann, Falk

2016-04-01

Use of potentially inappropriate medications may result in increased morbidity, mortality and resource utilisation. Due to polypharmacy and age-related decline in renal function the elderly population is at particular risk. Therefore, the Beers Criteria include use of nonsteroidal anti-inflammatory drugs in chronic renal failure stage 4 and 5 as these drugs may worsen renal function. According to the summary of product characteristics, the nonsteroidal anti-inflammatory drugs ibuprofen and diclofenac are contraindicated in these patients. Objective was to assess the extent of nonsteroidal anti-inflammatory drug use in nursing homes with a focus on residents with severe renal failure. Multi-centre cross-sectional study in 21 German nursing homes. The study population comprised residents for whom at least one serum creatinine value and information about sex were available, so that creatinine clearance rate could be estimated. In all, 685 of 852 residents were included as they fulfilled the abovementioned criteria. Renal failure was severe (estimated creatinine clearance rate < 30 ml/min) in 106 residents (15.5 %). Approximately one-fifth was treated with at least one nonsteroidal anti-inflammatory drug in both the total study population (20.3 %) and that with severe renal failure (20.8 %). With one exception, all residents prescribed nonsteroidal anti-inflammatory drugs with severe renal failure were treated with at least one nonsteroidal anti-inflammatory drug that was contraindicated due to the underlying renal function. Notwithstanding their classification as potentially inappropriate medications and underlying contraindications, use of nonsteroidal anti-inflammatory drugs is common among nursing home residents with severe renal failure.

New integrated and multiscale decision-aiding framework in a context of imperfect information: application to the assessment of torrent checkdams' effectiveness.

NASA Astrophysics Data System (ADS)

Tacnet, Jean-Marc; Carladous, Simon; Dezert, Jean; Batton-Hubert, Mireille

2017-04-01

Mountain natural phenomena (e.g. torrential floods) put people and buildings at risk. Civil engineering protection works such as torrent check-dams are designed to mitigate those natural risks. Protection works act on both causes and effects of phenomena to reduce consequences and therefore risks. For instance, check-dams control sediment production and liquid/solid flow of torrential floods: several series of dams are located in the headwaters of a watershed, each having specific functions. All those works are damaged by time passing and flood impacts. Effectiveness assessment is needed to define, compare or choose strategies for investment and maintenance which are essential issues in risk management process. Decision support tools are expected to analyze at different scales both their technical effectiveness (related to their structural state and functional effects on phenomena such as stopping, braking, guiding, etc.) and their economic efficiency through comparison between benefits and costs. Several methods, often based on expert knowledge, have already been developed to care about decision under risk. But uncertainty has also to be considered, since decisions are indeed often taken in a context of lack of information and knowledge on natural phenomena, heterogeneity of available information and, finally, reliability of sources. First methods derived from classical industrial contexts, such as dependability analysis, are used to formalize expert knowledge used for decision-making. After having defined the concept of effectiveness, dependability analysis are used to identify decision contexts and problems: criteria and indicators are identified in relation with structural or functional features. Then, innovative and multi-scales multi-criteria decision-making methods (MCDMs) and frameworks are proposed to help assessing protection works effectiveness. They combine classical MCDM approaches, belief function, fuzzy sets and possibility theories. Those methods allow to make decisions based on heterogeneous, imprecise and uncertain evaluation of criteria provided by more or less reliable sources in an uncertain context: COWA-ER (Cautious Ordered Weighted Averaging with Evidential Reasoning), Fuzzy-Cautious OWA or ER-MCDA (Evidential Reasoning for Multi Criteria Decision Analysis) are thus applied to several scales of torrent check-dams' effectiveness assessment. Those methods are then improved for a better knowledge representation and final decision. Enhanced methods are then associated together. Finally, individual problems and associated methods are integrated in a generic methodology to move from torrential protective single measure effectiveness assessment to complete protection systems at watershed scale.

Integration of multi-disciplinary geospatial data for delineating agroecosystem uniform management zones.

PubMed

Liu, Huanjun; Huffman, Ted; Liu, Jiangui; Li, Zhe; Daneshfar, Bahram; Zhang, Xinle

2015-01-01

Understanding agricultural ecosystems and their complex interactions with the environment is important for improving agricultural sustainability and environmental protection. Developing the necessary understanding requires approaches that integrate multi-source geospatial data and interdisciplinary relationships at different spatial scales. In order to identify and delineate landscape units representing relatively homogenous biophysical properties and eco-environmental functions at different spatial scales, a hierarchical system of uniform management zones (UMZ) is proposed. The UMZ hierarchy consists of seven levels of units at different spatial scales, namely site-specific, field, local, regional, country, continent, and globe. Relatively few studies have focused on the identification of the two middle levels of units in the hierarchy, namely the local UMZ (LUMZ) and the regional UMZ (RUMZ), which prevents true eco-environmental studies from being carried out across the full range of scales. This study presents a methodology to delineate LUMZ and RUMZ spatial units using land cover, soil, and remote sensing data. A set of objective criteria were defined and applied to evaluate the within-zone homogeneity and between-zone separation of the delineated zones. The approach was applied in a farming and forestry region in southeastern Ontario, Canada, and the methodology was shown to be objective, flexible, and applicable with commonly available spatial data. The hierarchical delineation of UMZs can be used as a tool to organize the spatial structure of agricultural landscapes, to understand spatial relationships between cropping practices and natural resources, and to target areas for application of specific environmental process models and place-based policy interventions.

Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments

PubMed Central

Kadima, Hubert; Granado, Bertrand

2013-01-01

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach. PMID:24319361

Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.

PubMed

Yassa, Sonia; Chelouah, Rachid; Kadima, Hubert; Granado, Bertrand

2013-01-01

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach.

Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

PubMed Central

Hu, Haigen; Xu, Lihong; Wei, Ruihua; Zhu, Bingkun

2011-01-01

This paper investigates the issue of tuning the Proportional Integral and Derivative (PID) controller parameters for a greenhouse climate control system using an Evolutionary Algorithm (EA) based on multiple performance measures such as good static-dynamic performance specifications and the smooth process of control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a simulation experiment. The results show that by tuning the gain parameters the controllers can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Besides, it can be applied to tuning the system with different properties, such as strong interactions among variables, nonlinearities and conflicting performance criteria. The results implicate that it is a quite effective and promising tuning method using multi-objective optimization algorithms in the complex greenhouse production. PMID:22163927

Optimal Technology Investment and Operation in Zero-Net-Energy Buildings with Demand Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stadler , Michael; Siddiqui, Afzal; Marnay, Chris

The US Department of Energy has launched the Zero-Net-Energy (ZNE) Commercial Building Initiative (CBI) in order to develop commercial buildings that produce as much energy as they use. Its objective is to make these buildings marketable by 2025 such that they minimize their energy use through cutting-edge energy-efficient technologies and meet their remaining energy needs through on-site renewable energy generation. We examine how such buildings may be implemented within the context of a cost- or carbon-minimizing microgrid that is able to adopt and operate various technologies, such as photovoltaic (PV) on-site generation, heat exchangers, solar thermal collectors, absorption chillers, andmore » passive / demand-response technologies. We use a mixed-integer linear program (MILP) that has a multi-criteria objective function: the minimization of a weighted average of the building's annual energy costs and carbon / CO2 emissions. The MILP's constraints ensure energy balance and capacity limits. In addition, constraining the building's energy consumed to equal its energy exports enables us to explore how energy sales and demand-response measures may enable compliance with the CBI. Using a nursing home in northern California and New York with existing tariff rates and technology data, we find that a ZNE building requires ample PV capacity installed to ensure electricity sales during the day. This is complemented by investment in energy-efficient combined heat and power equipment, while occasional demand response shaves energy consumption. A large amount of storage is also adopted, which may be impractical. Nevertheless, it shows the nature of the solutions and costs necessary to achieve ZNE. For comparison, we analyze a nursing home facility in New York to examine the effects of a flatter tariff structure and different load profiles. It has trouble reaching ZNE status and its load reductions as well as efficiency measures need to be more effective than those in the CA case. Finally, we illustrate that the multi-criteria frontier that considers costs and carbon emissions in the presence of demand response dominates the one without it.« less

Multi-energy x-ray detectors to improve air-cargo security

NASA Astrophysics Data System (ADS)

Paulus, Caroline; Moulin, Vincent; Perion, Didier; Radisson, Patrick; Verger, Loïck

2017-05-01

X-ray based systems have been used for decades to screen luggage or cargo to detect illicit material. The advent of energy-sensitive photon-counting x-ray detectors mainly based on Cd(Zn)Te semi-conductor technology enables to improve discrimination between materials compared to single or dual energy technology. The presented work is part of the EUROSKY European project to develop a Single European Secure Air-Cargo Space. "Cargo" context implies the presence of relatively heavy objects and with potentially high atomic number. All the study is conducted on simulations with three different detectors: a typical dual energy sandwich detector, a realistic model of the commercial ME100 multi-energy detector marketed by MULTIX, and a ME100 "Cargo": a not yet existing modified multi-energy version of the ME100 more suited to air freight cargo inspection. Firstly, a comparison on simulated measurements shows the performances improvement of the new multi-energy detectors compared to the current dual-energy one. The relative performances are evaluated according to different criteria of separability or contrast-to-noise ratio and the impact of different parameters is studied (influence of channel number, type of materials and tube voltage). Secondly, performances of multi-energy detectors for overlaps processing in a dual-view system is accessed: the case of orthogonal projections has been studied, one giving dimensional values, the other one providing spectral data to assess effective atomic number. A method of overlap correction has been proposed and extended to multi-layer objects case. Therefore, Calibration and processing based on bi-material decomposition have been adapted for this purpose.

Balancing habitat delivery for breeding marsh birds and nonbreeding waterfowl: An integrated waterbird management and monitoring approach at Clarence Cannon National Wildlife Refuge, Missouri

USGS Publications Warehouse

Loges, Brian W.; Lyons, James E.; Tavernia, Brian G.

2017-08-23

The Clarence Cannon National Wildlife Refuge (CCNWR) in the Mississippi River flood plain of eastern Missouri provides high quality emergent marsh and moist-soil habitat benefitting both nesting marsh birds and migrating waterfowl. Staff of CCNWR manipulate water levels and vegetation in the 17 units of the CCNWR to provide conditions favorable to these two important guilds. Although both guilds include focal species at multiple planning levels and complement objectives to provide a diversity of wetland community types and water regimes, additional decision support is needed for choosing how much emergent marsh and moist-soil habitat should be provided through annual management actions.To develop decision guidance for balanced delivery of high-energy waterfowl habitat and breeding marsh bird habitat, two measureable management objectives were identified: nonbreeding Anas Linnaeus (dabbling duck) use-days and Rallus elegans (king rail) occupancy of managed units. Three different composite management actions were identified to achieve these objectives. Each composite management action is a unique combination of growing season water regime and soil disturbance. The three composite management actions are intense moist-soil management (moist-soil), intermediate moist-soil (intermediate), and perennial management, which idles soils disturbance (perennial). The two management objectives and three management options were used in a multi-criteria decision analysis to indicate resource allocations and inform annual decision making. Outcomes of the composite management actions were predicted in two ways and multi-criteria decision analysis was used with each set of predictions. First, outcomes were predicted using expert-elicitation techniques and a panel of subject matter experts. Second, empirical data from the Integrated Waterbird Management and Monitoring Initiative collected between 2010 and 2013 were used; where data were lacking, expert judgment was used. Also, a Bayesian decision model was developed that can be updated with monitoring data in an adaptive management framework.Optimal resource allocations were identified in the form of portfolios of composite management actions for the 17 units in the framework. A constrained optimization (linear programming) was used to maximize an objective function that was based on the sum of dabbling duck and king rail utility. The constraints, which included management costs and a minimum energetic carrying capacity (total moist-soil acres), were applied to balance habitat delivery for dabbling ducks and king rails. Also, the framework was constrained in some cases to apply certain management actions of interest to certain management units; these constraints allowed for a variety of hypothetical Habitat Management Plans, including one based on output from a hydrogeomorphic study of the refuge. The decision analysis thus created numerous refuge-wide scenarios, each representing a unique mix of options (one for each of 17 units) and associated benefits (i.e., outcomes with respect to two management objectives).Prepared in collaboration with the U.S. Fish and Wildlife Service, the decision framework presented here is designed as a decision-aiding tool for CCNWR managers who ultimately make difficult decisions each year with multiple objectives, multiple management units, and the complexity of natural systems. The framework also provides a way to document hypotheses about how the managed system functions. Furthermore, the framework identifies specific monitoring needs and illustrates precisely how monitoring data will be used for decision-aiding and adaptive management.

Multi-criteria evaluation in strategic environmental assessment for waste management plan, a case study: The city of Belgrade

DOE Office of Scientific and Technical Information (OSTI.GOV)

Josimović, Boško, E-mail: bosko@iaus.ac.rs; Marić, Igor; Milijić, Saša

2015-02-15

Highlights: • The paper deals with the specific method of multi-criteria evaluation applied in drafting the SEA for the Belgrade WMP. • MCE of the planning solutions, assessed according to 37 objectives of the SEA and four sets of criteria, was presented in the matrix form. • The results are presented in the form of graphs so as to be easily comprehensible to all the participants in the decision-making process. • The results represent concrete contribution proven in practice. - Abstract: Strategic Environmental Assessment (SEA) is one of the key instruments for implementing sustainable development strategies in planning in general;more » in addition to being used in sectoral planning, it can also be used in other areas such as waste management planning. SEA in waste management planning has become a tool for considering the benefits and consequences of the proposed changes in space, also taking into account the capacity of space to sustain the implementation of the planned activities. In order to envisage both the positive and negative implications of a waste management plan for the elements of sustainable development, an adequate methodological approach to evaluating the potential impacts must be adopted and the evaluation results presented in a simple and clear way, so as to allow planners to make relevant decisions as a precondition for the sustainability of the activities planned in the waste management sector. This paper examines the multi-criteria evaluation method for carrying out an SEA for the Waste Management Plan for the city of Belgrade (BWMP). The method was applied to the evaluation of the impacts of the activities planned in the waste management sector on the basis of the environmental and socioeconomic indicators of sustainability, taking into consideration the intensity, spatial extent, probability and frequency of impact, by means of a specific planning approach and simple and clear presentation of the obtained results.« less

An Intuitionistic Multiplicative ORESTE Method for Patients’ Prioritization of Hospitalization

PubMed Central

Zhang, Cheng; Wu, Xingli; Wu, Di; Luo, Li; Herrera-Viedma, Enrique

2018-01-01

The tension brought about by sickbeds is a common and intractable issue in public hospitals in China due to the large population. Assigning the order of hospitalization of patients is difficult because of complex patient information such as disease type, emergency degree, and severity. It is critical to rank the patients taking full account of various factors. However, most of the evaluation criteria for hospitalization are qualitative, and the classical ranking method cannot derive the detailed relations between patients based on these criteria. Motivated by this, a comprehensive multiple criteria decision making method named the intuitionistic multiplicative ORESTE (organísation, rangement et Synthèse dedonnées relarionnelles, in French) was proposed to handle the problem. The subjective and objective weights of criteria were considered in the proposed method. To do so, first, considering the vagueness of human perceptions towards the alternatives, an intuitionistic multiplicative preference relation model is applied to represent the experts’ preferences over the pairwise alternatives with respect to the predetermined criteria. Then, a correlation coefficient-based weight determining method is developed to derive the objective weights of criteria. This method can overcome the biased results caused by highly-related criteria. Afterwards, we improved the general ranking method, ORESTE, by introducing a new score function which considers both the subjective and objective weights of criteria. An intuitionistic multiplicative ORESTE method was then developed and further highlighted by a case study concerning the patients’ prioritization. PMID:29673212

Model-based object classification using unification grammars and abstract representations

NASA Astrophysics Data System (ADS)

Liburdy, Kathleen A.; Schalkoff, Robert J.

1993-04-01

The design and implementation of a high level computer vision system which performs object classification is described. General object labelling and functional analysis require models of classes which display a wide range of geometric variations. A large representational gap exists between abstract criteria such as `graspable' and current geometric image descriptions. The vision system developed and described in this work addresses this problem and implements solutions based on a fusion of semantics, unification, and formal language theory. Object models are represented using unification grammars, which provide a framework for the integration of structure and semantics. A methodology for the derivation of symbolic image descriptions capable of interacting with the grammar-based models is described and implemented. A unification-based parser developed for this system achieves object classification by determining if the symbolic image description can be unified with the abstract criteria of an object model. Future research directions are indicated.

Multi-registration of software library resources

DOEpatents

Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian E [Rochester, MN

2011-04-05

Data communications, including issuing, by an application program to a high level data communications library, a request for initialization of a data communications service; issuing to a low level data communications library a request for registration of data communications functions; registering the data communications functions, including instantiating a factory object for each of the one or more data communications functions; issuing by the application program an instruction to execute a designated data communications function; issuing, to the low level data communications library, an instruction to execute the designated data communications function, including passing to the low level data communications library a call parameter that identifies a factory object; creating with the identified factory object the data communications object that implements the data communications function according to the protocol; and executing by the low level data communications library the designated data communications function.

Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi

PubMed Central

Montenegro, Diego; da Cunha, Ana Paula; Ladeia-Andrade, Simone; Vera, Mauricio; Pedroso, Marcel; Junqueira, Angela

2017-01-01

BACKGROUND Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per year on average. OBJECTIVES To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area undergoing domiciliary vector interruption of T. cruzi in Colombia. METHODS Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive assistance (GAIA) methods] and spatial statistics were performed on data from a socio-environmental questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and indicators of five determinants of the CD vector pathway were summarily defined, including: (1) house indicator (HI); (2) triatominae indicator (TI); (3) host/reservoir indicator (Ho/RoI); (4) ecotope indicator (EI); and (5) socio-cultural indicator (S-CI). FINDINGS Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T. cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors’ setting (border areas) on local values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector. CONCLUSIONS The study model proposed here is flexible and can be adapted to various eco-epidemiological profiles and is suitable for focusing anti-T. cruzi serological surveillance programs in vulnerable human populations. PMID:28953999

Comparisons of interdisciplinary ballast water treatment systems and operational experiences from ships.

PubMed

Bakalar, Goran

2016-01-01

There are high functioning and low functioning ballast water treatment systems on board ships. In this study, five systems were analysed so as to methodically examine the operational difficulties for ship crew members while giving important consideration to sustainable environment practices. Multi-criteria analysis, a questionnaire, survey and interviews were used as the research method so as to ascertain and corroborate existing problems on board ships, and the reliability of the systems was calculated. The co-insistency, maintenance and the efficiency of the systems, were shown as being the major problem as there are no systems for tracking ship ballast operations from land. The treatment system that used oxidants was, through multi criteria analysis, evaluated as being the best and was ranked first. However, the survey results showed that the ship's crew had serious problems with this system which difficult to solve during the ship's operations with cargo. The deoxygenation system was the most appropriate according to ballast water treatment criteria in the port or at sea. The treatment system which used electrolysis with oxidant was better in terms of efficacy and the treatment system electrolysis with ultra violet light was better in terms of the criterion environment pollution footprint. During further research, it was shown that 7 % of the surveyed crew members had major problems with operating ballast water treatment systems, including the system which was ranked first through multi criteria analysis. They by-passed these systems while continuing to ballast or de-ballast. It was calculated that of the total time needed for the ballast water treatment system operation, 9 % of this time was used for repairs or maintenance of the systems. Some examples are changing a used UV bulb, cleaning the filter or controlling the amount of oxidant which would be discharged into the sea. A conclusion was made and solution was suggested. The study results emphasised taking action in the interest of protecting the natural world, with particular attention being given to environmental protection to support human life.

Hierarchical image feature extraction by an irregular pyramid of polygonal partitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skurikhin, Alexei N

2008-01-01

We present an algorithmic framework for hierarchical image segmentation and feature extraction. We build a successive fine-to-coarse hierarchy of irregular polygonal partitions of the original image. This multiscale hierarchy forms the basis for object-oriented image analysis. The framework incorporates the Gestalt principles of visual perception, such as proximity and closure, and exploits spectral and textural similarities of polygonal partitions, while iteratively grouping them until dissimilarity criteria are exceeded. Seed polygons are built upon a triangular mesh composed of irregular sized triangles, whose spatial arrangement is adapted to the image content. This is achieved by building the triangular mesh on themore » top of detected spectral discontinuities (such as edges), which form a network of constraints for the Delaunay triangulation. The image is then represented as a spatial network in the form of a graph with vertices corresponding to the polygonal partitions and edges reflecting their relations. The iterative agglomeration of partitions into object-oriented segments is formulated as Minimum Spanning Tree (MST) construction. An important characteristic of the approach is that the agglomeration of polygonal partitions is constrained by the detected edges; thus the shapes of agglomerated partitions are more likely to correspond to the outlines of real-world objects. The constructed partitions and their spatial relations are characterized using spectral, textural and structural features based on proximity graphs. The framework allows searching for object-oriented features of interest across multiple levels of details of the built hierarchy and can be generalized to the multi-criteria MST to account for multiple criteria important for an application.« less

The Importance of Behavioral Thresholds and Objective Functions in Contaminant Transport Uncertainty Analysis

NASA Astrophysics Data System (ADS)

Sykes, J. F.; Kang, M.; Thomson, N. R.

2007-12-01

The TCE release from The Lockformer Company in Lisle Illinois resulted in a plume in a confined aquifer that is more than 4 km long and impacted more than 300 residential wells. Many of the wells are on the fringe of the plume and have concentrations that did not exceed 5 ppb. The settlement for the Chapter 11 bankruptcy protection of Lockformer involved the establishment of a trust fund that compensates individuals with cancers with payments being based on cancer type, estimated TCE concentration in the well and the duration of exposure to TCE. The estimation of early arrival times and hence low likelihood events is critical in the determination of the eligibility of an individual for compensation. Thus, an emphasis must be placed on the accuracy of the leading tail region in the likelihood distribution of possible arrival times at a well. The estimation of TCE arrival time, using a three-dimensional analytical solution, involved parameter estimation and uncertainty analysis. Parameters in the model included TCE source parameters, groundwater velocities, dispersivities and the TCE decay coefficient for both the confining layer and the bedrock aquifer. Numerous objective functions, which include the well-known L2-estimator, robust estimators (L1-estimators and M-estimators), penalty functions, and dead zones, were incorporated in the parameter estimation process to treat insufficiencies in both the model and observational data due to errors, biases, and limitations. The concept of equifinality was adopted and multiple maximum likelihood parameter sets were accepted if pre-defined physical criteria were met. The criteria ensured that a valid solution predicted TCE concentrations for all TCE impacted areas. Monte Carlo samples are found to be inadequate for uncertainty analysis of this case study due to its inability to find parameter sets that meet the predefined physical criteria. Successful results are achieved using a Dynamically-Dimensioned Search sampling methodology that inherently accounts for parameter correlations and does not require assumptions regarding parameter distributions. For uncertainty analysis, multiple parameter sets were obtained using a modified Cauchy's M-estimator. Penalty functions had to be incorporated into the objective function definitions to generate a sufficient number of acceptable parameter sets. The combined effect of optimization and the application of the physical criteria perform the function of behavioral thresholds by reducing anomalies and by removing parameter sets with high objective function values. The factors that are important to the creation of an uncertainty envelope for TCE arrival at wells are outlined in the work. In general, greater uncertainty appears to be present at the tails of the distribution. For a refinement of the uncertainty envelopes, the application of additional physical criteria or behavioral thresholds is recommended.

[The physiological classification of human thermal states under high environmental temperatures].

PubMed

Bobrov, A F; Kuznets, E I

1995-01-01

The paper deals with the physiological classification of human thermal states in a hot environment. A review of the basic systems of classifications of thermal states is given, their main drawbacks are discussed. On the basis of human functional state research in a broad range of environmental temperatures the system of evaluation and classification of human thermal states is proposed. New integral one-dimensional multi-parametric criteria for evaluation are used. For the development of these criteria methods of factor, cluster and canonical correlation analyses are applied. Stochastic nomograms capable of identification of human thermal state for different intensity of influence are given. In this case evaluation of intensity is estimated according to one-dimensional criteria taking into account environmental temperature, physical load and time of man's staying in overheating conditions.

Towards a new definition of return-to-work outcomes in common mental disorders from a multi-stakeholder perspective.

PubMed

Hees, Hiske L; Nieuwenhuijsen, Karen; Koeter, Maarten W J; Bültmann, Ute; Schene, Aart H

2012-01-01

To examine the perspectives of key stakeholders involved in the return-to-work (RTW) process regarding the definition of successful RTW outcome after sickness absence related to common mental disorders (CMD's). A mixed-method design was used: First, we used qualitative methods (focus groups, interviews) to identify a broad range of criteria important for the definition of successful RTW (N = 57). Criteria were grouped into content-related clusters. Second, we used a quantitative approach (online questionnaire) to identify, among a larger stakeholder sample (N = 178), the clusters and criteria most important for successful RTW. A total of 11 clusters, consisting of 52 unique criteria, were identified. In defining successful RTW, supervisors and occupational physicians regarded "Sustainability" and "At-work functioning" most important, while employees regarded "Sustainability," "Job satisfaction," "Work-home balance," and "Mental Functioning" most important. Despite agreement on the importance of certain criteria, considerable differences among stakeholders were observed. Key stakeholders vary in the aspects and criteria they regard as important when defining successful RTW after CMD-related sickness absence. Current definitions of RTW outcomes used in scientific research may not accurately reflect these key stakeholder perspectives. Future studies should be more aware of the perspective from which they aim to evaluate the effectiveness of a RTW intervention, and define their RTW outcomes accordingly.

Comparing the Certification Criteria for CCHIT-Certified Ambulatory EHR with the SNUBH's EHR Functionalities

PubMed Central

Heo, Eun Young; Hwang, Hee; Kim, Eun Hye; Cho, Eun Young; Lee, Kee Hyuck; Kim, Tae Hun; Kim, Ki Dong; Baek, Rong Min

2012-01-01

Objectives This study aims to investigate the suitability of electronic health record (EHR) systems in Korea for global certification and to propose functions for future global systems by comparing and analyzing the certification criteria for Certification Commission for Health Information Technology (CCHIT) Certified Ambulatory EHR with BESTCare, which is the EHR system at Seoul National University Bundang hospital. Methods Domain expert groups were formed to analyze the inclusion of BESTCare functions and the types of differences for each of the CCHIT Certified 2011 Ambulatory EHR Certification Criteria. The types of differences were divided into differences in functions (F), differences in business processes (B), and differences in government policies (P). Results Generally, the criteria that showed differences in functions pertained to the connection between the diagnosis/problem list and order, the alert and warning functions for medication-diagnosis interactions, and the reminder/instruction/notification messages related to the patient's immunization status; these absent functions were enhanced clinical decision support system (CDSS) functions related to patient safety and healthcare quality. Differences in government policies were found in the pharmacy's electronic prescription functions, while differences in business processes were found in the functions constrained by the local workflow or internal policy, which require some customization. Conclusions Functions that differed between the CCHIT certification criteria and the BESTCare system in this study should be considered when developing a global EHR system. Such a system will need to be easily customizable to adapt to various government policies and local business processes. These functions should be considered when developing a global EHR system certified by CCHIT in the future. PMID:22509474

Reducing salt in food; setting product-specific criteria aiming at a salt intake of 5 g per day

PubMed Central

Dötsch-Klerk, M; PMM Goossens, W; Meijer, G W; van het Hof, K H

2015-01-01

Background/Objectives: There is an increasing public health concern regarding high salt intake, which is generally between 9 and 12 g per day, and much higher than the 5 g recommended by World Health Organization. Several relevant sectors of the food industry are engaged in salt reduction, but it is a challenge to reduce salt in products without compromising on taste, shelf-life or expense for consumers. The objective was to develop globally applicable salt reduction criteria as guidance for product reformulation. Subjects/Methods: Two sets of product group-specific sodium criteria were developed to reduce salt levels in foods to help consumers reduce their intake towards an interim intake goal of 6 g/day, and—on the longer term—5 g/day. Data modelling using survey data from the United States, United Kingdom and Netherlands was performed to assess the potential impact on population salt intake of cross-industry food product reformulation towards these criteria. Results: Modelling with 6 and 5 g/day criteria resulted in estimated reductions in population salt intake of 25 and 30% for the three countries, respectively, the latter representing an absolute decrease in the median salt intake of 1.8–2.2 g/day. Conclusions: The sodium criteria described in this paper can serve as guidance for salt reduction in foods. However, to enable achieving an intake of 5 g/day, salt reduction should not be limited to product reformulation. A multi-stakeholder approach is needed to make consumers aware of the need to reduce their salt intake. Nevertheless, dietary impact modelling shows that product reformulation by food industry has the potential to contribute substantially to salt-intake reduction. PMID:25690867

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Z; Folkert, M; Wang, J

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidentialmore » reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.« less

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

PubMed

Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

2016-01-01

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation

PubMed Central

Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

2016-01-01

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality. PMID:26954783

Nonlinear bioheat transfer models and multi-objective numerical optimization of the cryosurgery operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kudryashov, Nikolay A.; Shilnikov, Kirill E.

Numerical computation of the three dimensional problem of the freezing interface propagation during the cryosurgery coupled with the multi-objective optimization methods is used in order to improve the efficiency and safety of the cryosurgery operations performing. Prostate cancer treatment and cutaneous cryosurgery are considered. The heat transfer in soft tissue during the thermal exposure to low temperature is described by the Pennes bioheat model and is coupled with an enthalpy method for blurred phase change computations. The finite volume method combined with the control volume approximation of the heat fluxes is applied for the cryosurgery numerical modeling on the tumormore » tissue of a quite arbitrary shape. The flux relaxation approach is used for the stability improvement of the explicit finite difference schemes. The method of the additional heating elements mounting is studied as an approach to control the cellular necrosis front propagation. Whereas the undestucted tumor tissue and destucted healthy tissue volumes are considered as objective functions, the locations of additional heating elements in cutaneous cryosurgery and cryotips in prostate cancer cryotreatment are considered as objective variables in multi-objective problem. The quasi-gradient method is proposed for the searching of the Pareto front segments as the multi-objective optimization problem solutions.« less

Operationalizing the Diagnostic Criteria for Mild Cognitive Impairment: The Salience of Objective Measures in Predicting Incident Dementia.

PubMed

Brodaty, Henry; Aerts, Liesbeth; Crawford, John D; Heffernan, Megan; Kochan, Nicole A; Reppermund, Simone; Kang, Kristan; Maston, Kate; Draper, Brian; Trollor, Julian N; Sachdev, Perminder S

2017-05-01

Mild cognitive impairment (MCI) is considered an intermediate stage between normal aging and dementia. It is diagnosed in the presence of subjective cognitive decline and objective cognitive impairment without significant functional impairment, although there are no standard operationalizations for each of these criteria. The objective of this study is to determine which operationalization of the MCI criteria is most accurate at predicting dementia. Six-year longitudinal study, part of the Sydney Memory and Ageing Study. Community-based. 873 community-dwelling dementia-free adults between 70 and 90 years of age. Persons from a non-English speaking background were excluded. Seven different operationalizations for subjective cognitive decline and eight measures of objective cognitive impairment (resulting in 56 different MCI operational algorithms) were applied. The accuracy of each algorithm to predict progression to dementia over 6 years was examined for 618 individuals. Baseline MCI prevalence varied between 0.4% and 30.2% and dementia conversion between 15.9% and 61.9% across different algorithms. The predictive accuracy for progression to dementia was poor. The highest accuracy was achieved based on objective cognitive impairment alone. Inclusion of subjective cognitive decline or mild functional impairment did not improve dementia prediction accuracy. Not MCI, but objective cognitive impairment alone, is the best predictor for progression to dementia in a community sample. Nevertheless, clinical assessment procedures need to be refined to improve the identification of pre-dementia individuals. Copyright © 2016 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Ranking Schools' Academic Performance Using a Fuzzy VIKOR

NASA Astrophysics Data System (ADS)

Musani, Suhaina; Aziz Jemain, Abdul

2015-06-01

Determination rank is structuring alternatives in order of priority. It is based on the criteria determined for each alternative involved. Evaluation criteria are performed and then a composite index composed of each alternative for the purpose of arranging in order of preference alternatives. This practice is known as multiple criteria decision making (MCDM). There are several common approaches to MCDM, one of the practice is known as VIKOR (Multi-criteria Optimization and Compromise Solution). The objective of this study is to develop a rational method for school ranking based on linguistic information of a criterion. The school represents an alternative, while the results for a number of subjects as the criterion. The results of the examination for a course, is given according to the student percentage of each grade. Five grades of excellence, honours, average, pass and fail is used to indicate a level of achievement in linguistics. Linguistic variables are transformed to fuzzy numbers to form a composite index of school performance. Results showed that fuzzy set theory can solve the limitations of using MCDM when there is uncertainty problems exist in the data.

r.randomwalk v1.0, a multi-functional conceptual tool for mass movement routing

NASA Astrophysics Data System (ADS)

Mergili, M.; Krenn, J.; Chu, H.-J.

2015-09-01

We introduce r.randomwalk, a flexible and multi-functional open source tool for backward- and forward-analyses of mass movement propagation. r.randomwalk builds on GRASS GIS, the R software for statistical computing and the programming languages Python and C. Using constrained random walks, mass points are routed from defined release pixels of one to many mass movements through a digital elevation model until a defined break criterion is reached. Compared to existing tools, the major innovative features of r.randomwalk are: (i) multiple break criteria can be combined to compute an impact indicator score, (ii) the uncertainties of break criteria can be included by performing multiple parallel computations with randomized parameter settings, resulting in an impact indicator index in the range 0-1, (iii) built-in functions for validation and visualization of the results are provided, (iv) observed landslides can be back-analyzed to derive the density distribution of the observed angles of reach. This distribution can be employed to compute impact probabilities for each pixel. Further, impact indicator scores and probabilities can be combined with release indicator scores or probabilities, and with exposure indicator scores. We demonstrate the key functionalities of r.randomwalk (i) for a single event, the Acheron Rock Avalanche in New Zealand, (ii) for landslides in a 61.5 km2 study area in the Kao Ping Watershed, Taiwan; and (iii) for lake outburst floods in a 2106 km2 area in the Gunt Valley, Tajikistan.

r.randomwalk v1, a multi-functional conceptual tool for mass movement routing

NASA Astrophysics Data System (ADS)

Mergili, M.; Krenn, J.; Chu, H.-J.

2015-12-01

We introduce r.randomwalk, a flexible and multi-functional open-source tool for backward and forward analyses of mass movement propagation. r.randomwalk builds on GRASS GIS (Geographic Resources Analysis Support System - Geographic Information System), the R software for statistical computing and the programming languages Python and C. Using constrained random walks, mass points are routed from defined release pixels of one to many mass movements through a digital elevation model until a defined break criterion is reached. Compared to existing tools, the major innovative features of r.randomwalk are (i) multiple break criteria can be combined to compute an impact indicator score; (ii) the uncertainties of break criteria can be included by performing multiple parallel computations with randomized parameter sets, resulting in an impact indicator index in the range 0-1; (iii) built-in functions for validation and visualization of the results are provided; (iv) observed landslides can be back analysed to derive the density distribution of the observed angles of reach. This distribution can be employed to compute impact probabilities for each pixel. Further, impact indicator scores and probabilities can be combined with release indicator scores or probabilities, and with exposure indicator scores. We demonstrate the key functionalities of r.randomwalk for (i) a single event, the Acheron rock avalanche in New Zealand; (ii) landslides in a 61.5 km2 study area in the Kao Ping Watershed, Taiwan; and (iii) lake outburst floods in a 2106 km2 area in the Gunt Valley, Tajikistan.

Optimization of autoregressive, exogenous inputs-based typhoon inundation forecasting models using a multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Ouyang, Huei-Tau

2017-07-01

Three types of model for forecasting inundation levels during typhoons were optimized: the linear autoregressive model with exogenous inputs (LARX), the nonlinear autoregressive model with exogenous inputs with wavelet function (NLARX-W) and the nonlinear autoregressive model with exogenous inputs with sigmoid function (NLARX-S). The forecast performance was evaluated by three indices: coefficient of efficiency, error in peak water level and relative time shift. Historical typhoon data were used to establish water-level forecasting models that satisfy all three objectives. A multi-objective genetic algorithm was employed to search for the Pareto-optimal model set that satisfies all three objectives and select the ideal models for the three indices. Findings showed that the optimized nonlinear models (NLARX-W and NLARX-S) outperformed the linear model (LARX). Among the nonlinear models, the optimized NLARX-W model achieved a more balanced performance on the three indices than the NLARX-S models and is recommended for inundation forecasting during typhoons.

Multi-sensor image fusion algorithm based on multi-objective particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Xie, Xia-zhu; Xu, Ya-wei

2017-11-01

On the basis of DT-CWT (Dual-Tree Complex Wavelet Transform - DT-CWT) theory, an approach based on MOPSO (Multi-objective Particle Swarm Optimization Algorithm) was proposed to objectively choose the fused weights of low frequency sub-bands. High and low frequency sub-bands were produced by DT-CWT. Absolute value of coefficients was adopted as fusion rule to fuse high frequency sub-bands. Fusion weights in low frequency sub-bands were used as particles in MOPSO. Spatial Frequency and Average Gradient were adopted as two kinds of fitness functions in MOPSO. The experimental result shows that the proposed approach performances better than Average Fusion and fusion methods based on local variance and local energy respectively in brightness, clarity and quantitative evaluation which includes Entropy, Spatial Frequency, Average Gradient and QAB/F.

NARMAX model identification of a palm oil biodiesel engine using multi-objective optimization differential evolution

NASA Astrophysics Data System (ADS)

Mansor, Zakwan; Zakaria, Mohd Zakimi; Nor, Azuwir Mohd; Saad, Mohd Sazli; Ahmad, Robiah; Jamaluddin, Hishamuddin

2017-09-01

This paper presents the black-box modelling of palm oil biodiesel engine (POB) using multi-objective optimization differential evolution (MOODE) algorithm. Two objective functions are considered in the algorithm for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. The mathematical model used in this study to represent the POB system is nonlinear auto-regressive moving average with exogenous input (NARMAX) model. Finally, model validity tests are applied in order to validate the possible models that was obtained from MOODE algorithm and lead to select an optimal model.

Developing a multi-criteria approach for drug reimbursement decision making: an initial step forward.

PubMed

Dionne, Francois; Mitton, Craig; Dempster, Bill; Lynd, Larry D

2015-01-01

Coverage decisions for a new drug revolve around the balance between perceived value and price. But what is the perceived value of a new drug? Traditionally, the assessment of such value has largely revolved around the estimation of cost-effectiveness. However, very few will argue that the cost-effectiveness ratio presents a fulsome picture of 'value'. Multi-criteria decision analysis (MCDA) has been advocated as an alternative to cost-effectiveness analysis and it has been argued that it better reflects real world decision-making. The objective of this project was to address the issue of the lack of a satisfactory methodology to measure value for drugs by developing a framework to operationalize an MCDA approach incorporating societal values as they pertain to the value of drugs. Two workshops were held, one in Toronto in conjunction with the CAPT annual conference, and one in Ottawa, as part of the annual CADTH Symposium. Notes were taken at both workshops and the data collected was analyzed using a grounded theory approach. The intent was to reflect, as accurately as possible, what was said at the workshops, without normative judgement. Results to date are a set of guiding principles and criteria. There are currently ten criteria: Comparative effectiveness, Adoption feasibility, Risks of adverse events, Patient autonomy, Societal benefit, Equity, Strength of evidence, Incidence/prevalence/severity of condition, Innovation, and Disease prevention/ health promotion. Much progress has been made and it is now time to share the results. Feedback will determine the final shape of the framework proposed.

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

Quantifying ecosystem service trade-offs: the case of an urban floodplain in Vienna, Austria.

PubMed

Sanon, Samai; Hein, Thomas; Douven, Wim; Winkler, Peter

2012-11-30

Wetland ecosystems provide multiple functions and services for the well-being of humans. In urban environments, planning and decision making about wetland restoration inevitably involves conflicting objectives, trade-offs, uncertainties and conflicting value judgments. This study applied trade-off and multi criteria decision analysis to analyze and quantify the explicit trade-offs between the stakeholder's objectives related to management options for the restoration of an urban floodplain, the Lobau, in Vienna, Austria. The Lobau has been disconnected from the main channel of the Danube River through flood protection schemes 130 years ago that have reduced the hydraulic exchange processes. Urban expansion has also changed the adjacent areas and led to increased numbers of visitors, which hampers the maximum potential for ecosystem development and exerts additional pressure on the sensitive habitats in the national park area. The study showed that increased hydraulic connectivity would benefit several stakeholders that preferred the ecological development of the floodplain habitats. However, multiple uses including fishery, agriculture and recreation, exploring the maximum potential in line with national park regulations, were also possible under the increased hydraulic connectivity options. The largest trade-offs were quantified to be at 0.50 score between the ecological condition of the aquatic habitats and the drinking water production and 0.49 score between the ecological condition of the terrestrial habitats and the drinking water production. At this point, the drinking water production was traded-off with 0.40 score, while the ecological condition of the aquatic habitats and the ecological condition of the terrestrial habitats were traded off with 0.30 and 0.23 score, respectively. The majority of the stakeholders involved preferred the management options that increased the hydraulic connectivity compared with the current situation which was not preferred by any stakeholders. These findings highlight the need for targeted restoration measures. By that, it is recommended that additional measures to ensure reliable drinking water production should be developed, if the higher connectivity options would be implemented. In the next step it is recommended to include cost and flood risk criteria in the decision matrix for more specific developed measures. The research showed that pair-wise trade-off figures provided a useful means to elaborate and quantify the real trade-offs. Finally, the research also showed that the use of multi criteria decision analyses should be based on a participatory approach, in which the process of arriving at the final ranking should be equal or more important than the outcome of the ranking itself. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multiple Types of Memory and Everyday Functional Assessment in Older Adults

PubMed Central

Beaver, Jenna

2017-01-01

Abstract Objective Current proxy measures for assessing everyday functioning (e.g., questionnaires, performance-based measures, and direct observation) show discrepancies in their rating of functional status. The present study investigated the relationship between multiple proxy measures of functional status and content memory (i.e., memory for information), temporal order memory, and prospective memory in an older adult sample. Method A total of 197 community-dwelling older adults who did (n = 45) or did not meet (n = 152) criteria for mild cognitive impairment (MCI), completed six different assessments of functional status (two questionnaires, two performance-based tasks, and two direct observation tasks) as well as experimental measures of content memory, prospective memory, and temporal order memory. Results After controlling for demographics and content memory, the temporal order and prospective memory measures explained a significant amount of variance in all proxy functional status measures. When all variables were entered into the regression analyses, content memory and prospective memory were found to be significant predictors of all measures of functional status, whereas temporal order memory was a significant predictor for the questionnaire and direct observation measures, but not performance-based measures. Conclusion The results suggest that direct observation and questionnaire measures may be able to capture components of everyday functioning that require context and temporal sequencing abilities, such as multi-tasking, that are not as well captured in many current laboratory performance-based measures of functional status. Future research should aim to inform the development and use of maximally effective and valid proxy measures of functional ability. PMID:28334170

Multi-objective aerodynamic shape optimization of small livestock trailers

NASA Astrophysics Data System (ADS)

Gilkeson, C. A.; Toropov, V. V.; Thompson, H. M.; Wilson, M. C. T.; Foxley, N. A.; Gaskell, P. H.

2013-11-01

This article presents a formal optimization study of the design of small livestock trailers, within which the majority of animals are transported to market in the UK. The benefits of employing a headboard fairing to reduce aerodynamic drag without compromising the ventilation of the animals' microclimate are investigated using a multi-stage process involving computational fluid dynamics (CFD), optimal Latin hypercube (OLH) design of experiments (DoE) and moving least squares (MLS) metamodels. Fairings are parameterized in terms of three design variables and CFD solutions are obtained at 50 permutations of design variables. Both global and local search methods are employed to locate the global minimum from metamodels of the objective functions and a Pareto front is generated. The importance of carefully selecting an objective function is demonstrated and optimal fairing designs, offering drag reductions in excess of 5% without compromising animal ventilation, are presented.

Products recognition on shop-racks from local scale-invariant features

NASA Astrophysics Data System (ADS)

Zawistowski, Jacek; Kurzejamski, Grzegorz; Garbat, Piotr; Naruniec, Jacek

2016-04-01

This paper presents a system designed for the multi-object detection purposes and adjusted for the application of product search on the market shelves. System uses well known binary keypoint detection algorithms for finding characteristic points in the image. One of the main idea is object recognition based on Implicit Shape Model method. Authors of the article proposed many improvements of the algorithm. Originally fiducial points are matched with a very simple function. This leads to the limitations in the number of objects parts being success- fully separated, while various methods of classification may be validated in order to achieve higher performance. Such an extension implies research on training procedure able to deal with many objects categories. Proposed solution opens a new possibilities for many algorithms demanding fast and robust multi-object recognition.

Resource allocation in road infrastructure using ANP priorities with ZOGP formulation-A case study

NASA Astrophysics Data System (ADS)

Alias, Suriana; Adna, Norfarziah; Soid, Siti Khuzaimah; Kardri, Mahani

2013-09-01

Road Infrastructure (RI) project evaluation and selection is concern with the allocation of scarce organizational resources. In this paper, it is suggest an improved RI project selection methodology which reflects interdependencies among evaluation criteria and candidate projects. Fuzzy Delphi Method (FDM) is use to evoking expert group opinion and also to determine a degree of interdependences relationship between the alternative projects. In order to provide a systematic approach to set priorities among multi-criteria and trade-off among objectives, Analytic Network Process (ANP) is suggested to be applied prior to Zero-One Goal Programming (ZOGP) formulation. Specifically, this paper demonstrated how to combined FDM and ANP with ZOGP through a real-world RI empirical example on an ongoing decision-making project in Johor, Malaysia.

Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

2016-08-01

Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of optical see-through head-mounted displays for surgical interventions with object-anchored 2D-display

PubMed Central

Barthel, Alexander; Johnson, Alex; Osgood, Greg; Kazanzides, Peter; Navab, Nassir; Fuerst, Bernhard

2018-01-01

Purpose Optical see-through head-mounted displays (OST-HMD) feature an unhindered and instantaneous view of the surgery site and can enable a mixed reality experience for surgeons during procedures. In this paper, we present a systematic approach to identify the criteria for evaluation of OST-HMD technologies for specific clinical scenarios, which benefit from using an object-anchored 2D-display visualizing medical information. Methods Criteria for evaluating the performance of OST-HMDs for visualization of medical information and its usage are identified and proposed. These include text readability, contrast perception, task load, frame rate, and system lag. We choose to compare three commercially available OST-HMDs, which are representatives of currently available head-mounted display technologies. A multi-user study and an offline experiment are conducted to evaluate their performance. Results Statistical analysis demonstrates that Microsoft HoloLens performs best among the three tested OST-HMDs, in terms of contrast perception, task load, and frame rate, while ODG R-7 offers similar text readability. The integration of indoor localization and fiducial tracking on the HoloLens provides significantly less system lag in a relatively motionless scenario. Conclusions With ever more OST-HMDs appearing on the market, the proposed criteria could be used in the evaluation of their suitability for mixed reality surgical intervention. Currently, Microsoft HoloLens may be more suitable than ODG R-7 and Epson Moverio BT-200 for clinical usability in terms of the evaluated criteria. To the best of our knowledge, this is the first paper that presents a methodology and conducts experiments to evaluate and compare OST-HMDs for their use as object-anchored 2D-display during interventions. PMID:28343301

Comparison of optical see-through head-mounted displays for surgical interventions with object-anchored 2D-display.

PubMed

Qian, Long; Barthel, Alexander; Johnson, Alex; Osgood, Greg; Kazanzides, Peter; Navab, Nassir; Fuerst, Bernhard

2017-06-01

Optical see-through head-mounted displays (OST-HMD) feature an unhindered and instantaneous view of the surgery site and can enable a mixed reality experience for surgeons during procedures. In this paper, we present a systematic approach to identify the criteria for evaluation of OST-HMD technologies for specific clinical scenarios, which benefit from using an object-anchored 2D-display visualizing medical information. Criteria for evaluating the performance of OST-HMDs for visualization of medical information and its usage are identified and proposed. These include text readability, contrast perception, task load, frame rate, and system lag. We choose to compare three commercially available OST-HMDs, which are representatives of currently available head-mounted display technologies. A multi-user study and an offline experiment are conducted to evaluate their performance. Statistical analysis demonstrates that Microsoft HoloLens performs best among the three tested OST-HMDs, in terms of contrast perception, task load, and frame rate, while ODG R-7 offers similar text readability. The integration of indoor localization and fiducial tracking on the HoloLens provides significantly less system lag in a relatively motionless scenario. With ever more OST-HMDs appearing on the market, the proposed criteria could be used in the evaluation of their suitability for mixed reality surgical intervention. Currently, Microsoft HoloLens may be more suitable than ODG R-7 and Epson Moverio BT-200 for clinical usability in terms of the evaluated criteria. To the best of our knowledge, this is the first paper that presents a methodology and conducts experiments to evaluate and compare OST-HMDs for their use as object-anchored 2D-display during interventions.

What is in a name? Comparing diagnostic criteria for chronic fatigue syndrome with or without fibromyalgia.

PubMed

Meeus, Mira; Ickmans, Kelly; Struyf, Filip; Kos, Daphne; Lambrecht, Luc; Willekens, Barbara; Cras, Patrick; Nijs, Jo

2016-01-01

The current study had two objectives. (1) to compare objective and self-report measures in patients with chronic fatigue syndrome (CFS) according to the 1994 Center for Disease Control (CDC) criteria, patients with multiple sclerosis (MS), and healthy controls, and (2) to contrast CFS patients who only fulfill CDC criteria to those who also fulfill the criteria for myalgic encephalomyelitis (ME), the 2003 Canadian criteria for ME/CFS, or the comorbid diagnosis of fibromyalgia (FM). One hundred six participants (48 CFS patients diagnosed following the 1994 CDC criteria, 19 MS patients, and 39 healthy controls) completed questionnaires assessing symptom severity, quality of life, daily functioning, and psychological factors. Objective measures consisted of activity monitoring, evaluation of maximal voluntary contraction and muscle recovery, and cognitive performance. CFS patients were screened whether they also fulfilled ME criteria, the Canadian criteria, and the diagnosis of FM. CFS patients scored higher on symptom severity, lower on quality of life, and higher on depression and kinesiophobia and worse on MVC, muscle recovery, and cognitive performance compared to the MS patients and the healthy subjects. Daily activity levels were also lower compared to healthy subjects. Only one difference was found between those fulfilling the ME criteria and those who did not regarding the degree of kinesiophobia (lower in ME), while comorbidity for FM significantly increased the symptom burden. CFS patients report more severe symptoms and are more disabled compared to MS patients and healthy controls. Based on the present study, fulfillment of the ME or Canadian criteria did not seem to give a clinically different picture, whereas a diagnosis of comorbid FM selected symptomatically worse and more disabled patients.

Piecewise convexity of artificial neural networks.

PubMed

Rister, Blaine; Rubin, Daniel L

2017-10-01

Although artificial neural networks have shown great promise in applications including computer vision and speech recognition, there remains considerable practical and theoretical difficulty in optimizing their parameters. The seemingly unreasonable success of gradient descent methods in minimizing these non-convex functions remains poorly understood. In this work we offer some theoretical guarantees for networks with piecewise affine activation functions, which have in recent years become the norm. We prove three main results. First, that the network is piecewise convex as a function of the input data. Second, that the network, considered as a function of the parameters in a single layer, all others held constant, is again piecewise convex. Third, that the network as a function of all its parameters is piecewise multi-convex, a generalization of biconvexity. From here we characterize the local minima and stationary points of the training objective, showing that they minimize the objective on certain subsets of the parameter space. We then analyze the performance of two optimization algorithms on multi-convex problems: gradient descent, and a method which repeatedly solves a number of convex sub-problems. We prove necessary convergence conditions for the first algorithm and both necessary and sufficient conditions for the second, after introducing regularization to the objective. Finally, we remark on the remaining difficulty of the global optimization problem. Under the squared error objective, we show that by varying the training data, a single rectifier neuron admits local minima arbitrarily far apart, both in objective value and parameter space. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-Material Tissue Engineering Scaffold with Hierarchical Pore Architecture.

PubMed

Morgan, Kathy Ye; Sklaviadis, Demetra; Tochka, Zachary L; Fischer, Kristin M; Hearon, Keith; Morgan, Thomas D; Langer, Robert; Freed, Lisa E

2016-08-23

Multi-material polymer scaffolds with multiscale pore architectures were characterized and tested with vascular and heart cells as part of a platform for replacing damaged heart muscle. Vascular and muscle scaffolds were constructed from a new material, poly(limonene thioether) (PLT32i), which met the design criteria of slow biodegradability, elastomeric mechanical properties, and facile processing. The vascular-parenchymal interface was a poly(glycerol sebacate) (PGS) porous membrane that met different criteria of rapid biodegradability, high oxygen permeance, and high porosity. A hierarchical architecture of primary (macroscale) and secondary (microscale) pores was created by casting the PLT32i prepolymer onto sintered spheres of poly(methyl methacrylate) (PMMA) within precisely patterned molds followed by photocuring, de-molding, and leaching out the PMMA. Pre-fabricated polymer templates were cellularized, assembled, and perfused in order to engineer spatially organized, contractile heart tissue. Structural and functional analyses showed that the primary pores guided heart cell alignment and enabled robust perfusion while the secondary pores increased heart cell retention and reduced polymer volume fraction.

The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

NASA Astrophysics Data System (ADS)

Jaini, Nor I.; Utyuzhnikov, Sergei V.

2017-08-01

Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

Pareto-Optimal Multi-objective Inversion of Geophysical Data

NASA Astrophysics Data System (ADS)

Schnaidt, Sebastian; Conway, Dennis; Krieger, Lars; Heinson, Graham

2018-01-01

In the process of modelling geophysical properties, jointly inverting different data sets can greatly improve model results, provided that the data sets are compatible, i.e., sensitive to similar features. Such a joint inversion requires a relationship between the different data sets, which can either be analytic or structural. Classically, the joint problem is expressed as a scalar objective function that combines the misfit functions of multiple data sets and a joint term which accounts for the assumed connection between the data sets. This approach suffers from two major disadvantages: first, it can be difficult to assess the compatibility of the data sets and second, the aggregation of misfit terms introduces a weighting of the data sets. We present a pareto-optimal multi-objective joint inversion approach based on an existing genetic algorithm. The algorithm treats each data set as a separate objective, avoiding forced weighting and generating curves of the trade-off between the different objectives. These curves are analysed by their shape and evolution to evaluate data set compatibility. Furthermore, the statistical analysis of the generated solution population provides valuable estimates of model uncertainty.

Systematic assessment of benefits and risks: study protocol for a multi-criteria decision analysis using the Analytic Hierarchy Process for comparative effectiveness research

PubMed Central

Singh, Sonal

2013-01-01

Background: Regulatory decision-making involves assessment of risks and benefits of medications at the time of approval or when relevant safety concerns arise with a medication. The Analytic Hierarchy Process (AHP) facilitates decision-making in complex situations involving tradeoffs by considering risks and benefits of alternatives. The AHP allows a more structured method of synthesizing and understanding evidence in the context of importance assigned to outcomes. Our objective is to evaluate the use of an AHP in a simulated committee setting selecting oral medications for type 2 diabetes.  Methods: This study protocol describes the AHP in five sequential steps using a small group of diabetes experts representing various clinical disciplines. The first step will involve defining the goal of the decision and developing the AHP model. In the next step, we will collect information about how well alternatives are expected to fulfill the decision criteria. In the third step, we will compare the ability of the alternatives to fulfill the criteria and judge the importance of eight criteria relative to the decision goal of the optimal medication choice for type 2 diabetes. We will use pairwise comparisons to sequentially compare the pairs of alternative options regarding their ability to fulfill the criteria. In the fourth step, the scales created in the third step will be combined to create a summary score indicating how well the alternatives met the decision goal. The resulting scores will be expressed as percentages and will indicate the alternative medications' relative abilities to fulfill the decision goal. The fifth step will consist of sensitivity analyses to explore the effects of changing the estimates. We will also conduct a cognitive interview and process evaluation.  Discussion: Multi-criteria decision analysis using the AHP will aid, support and enhance the ability of decision makers to make evidence-based informed decisions consistent with their values and preferences. PMID:24555077

Systematic assessment of benefits and risks: study protocol for a multi-criteria decision analysis using the Analytic Hierarchy Process for comparative effectiveness research.

PubMed

Maruthur, Nisa M; Joy, Susan; Dolan, James; Segal, Jodi B; Shihab, Hasan M; Singh, Sonal

2013-01-01

Regulatory decision-making involves assessment of risks and benefits of medications at the time of approval or when relevant safety concerns arise with a medication. The Analytic Hierarchy Process (AHP) facilitates decision-making in complex situations involving tradeoffs by considering risks and benefits of alternatives. The AHP allows a more structured method of synthesizing and understanding evidence in the context of importance assigned to outcomes. Our objective is to evaluate the use of an AHP in a simulated committee setting selecting oral medications for type 2 diabetes.  This study protocol describes the AHP in five sequential steps using a small group of diabetes experts representing various clinical disciplines. The first step will involve defining the goal of the decision and developing the AHP model. In the next step, we will collect information about how well alternatives are expected to fulfill the decision criteria. In the third step, we will compare the ability of the alternatives to fulfill the criteria and judge the importance of eight criteria relative to the decision goal of the optimal medication choice for type 2 diabetes. We will use pairwise comparisons to sequentially compare the pairs of alternative options regarding their ability to fulfill the criteria. In the fourth step, the scales created in the third step will be combined to create a summary score indicating how well the alternatives met the decision goal. The resulting scores will be expressed as percentages and will indicate the alternative medications' relative abilities to fulfill the decision goal. The fifth step will consist of sensitivity analyses to explore the effects of changing the estimates. We will also conduct a cognitive interview and process evaluation.  Multi-criteria decision analysis using the AHP will aid, support and enhance the ability of decision makers to make evidence-based informed decisions consistent with their values and preferences.

Multi-Criteria Decision Analysis for Assessment and Appraisal of Orphan Drugs.

PubMed

Iskrov, Georgi; Miteva-Katrandzhieva, Tsonka; Stefanov, Rumen

2016-01-01

Limited resources and expanding expectations push all countries and types of health systems to adopt new approaches in priority setting and resources allocation. Despite best efforts, it is difficult to reconcile all competing interests, and trade-offs are inevitable. This is why multi-criteria decision analysis (MCDA) has played a major role in recent uptake of value-based reimbursement. MCDA framework enables exploration of stakeholders' preferences, as well as explicit organization of broad range of criteria on which real-world decisions are made. Assessment and appraisal of orphan drugs tend to be one of the most complicated health technology assessment (HTA) tasks. Access to market approved orphan therapies remains an issue. Early constructive dialog among rare disease stakeholders and elaboration of orphan drug-tailored decision support tools could set the scene for ongoing accumulation of evidence, as well as for proper reimbursement decision-making. The objective of this study was to create an MCDA value measurement model to assess and appraise orphan drugs. This was achieved by exploring the preferences on decision criteria's weights and performance scores through a stakeholder-representative survey and a focus group discussion that were both organized in Bulgaria. Decision criteria that describe the health technology's characteristics were unanimously agreed as the most important group of reimbursement considerations. This outcome, combined with the high individual weight of disease severity and disease burden criteria, underlined some of the fundamental principles of health care - equity and fairness. Our study proved that strength of evidence may be a key criterion in orphan drug assessment and appraisal. Evidence is used not only to shape reimbursement decision-making but also to lend legitimacy to policies pursued. The need for real-world data on orphan drugs was largely stressed. Improved knowledge on MCDA feasibility and integration to HTA is of paramount importance, as progress in medicine and innovative health technologies should correspond to patient, health-care system, and societal values.

Robustness analysis of a green chemistry-based model for the ...

EPA Pesticide Factsheets

This paper proposes a robustness analysis based on Multiple Criteria Decision Aiding (MCDA). The ensuing model was used to assess the implementation of green chemistry principles in the synthesis of silver nanoparticles. Its recommendations were also compared to an earlier developed model for the same purpose to investigate concordance between the models and potential decision support synergies. A three-phase procedure was adopted to achieve the research objectives. Firstly, an ordinal ranking of the evaluation criteria used to characterize the implementation of green chemistry principles was identified through relative ranking analysis. Secondly, a structured selection process for an MCDA classification method was conducted, which ensued in the identification of Stochastic Multi-Criteria Acceptability Analysis (SMAA). Lastly, the agreement of the classifications by the two MCDA models and the resulting synergistic role of decision recommendations were studied. This comparison showed that the results of the two models agree between 76% and 93% of the simulation set-ups and it confirmed that different MCDA models provide a more inclusive and transparent set of recommendations. This integrative research confirmed the beneficial complementary use of MCDA methods to aid responsible development of nanosynthesis, by accounting for multiple objectives and helping communication of complex information in a comprehensive and traceable format, suitable for stakeholders and

Review of Multi-Criteria Decision Aid for Integrated Sustainability Assessment of Urban Water Systems - MCEARD

EPA Science Inventory

Integrated sustainability assessment is part of a new paradigm for urban water decision making. Multi-criteria decision aid (MCDA) is an integrative framework used in urban water sustainability assessment, which has a particular focus on utilising stakeholder participation. Here ...

Gamers' insights into the phenomenology of normal gaming and game "addiction": A mixed methods study.

PubMed

Colder Carras, Michelle; Porter, Anne Marie; Van Rooij, Antonius J; King, Daniel; Lange, Amanda; Carras, Matthew; Labrique, Alain

2018-02-01

In response to calls for further research into the phenomenology of Internet gaming disorder (IGD), we used a community-engaged consensus development approach to evaluate how members of the "gamer culture" describe problematic gaming and the relationship of these descriptions to the proposed IGD criteria. Two focus groups of gamers were recruited at a video game convention. Participants were asked to submit suggestions for signs of game "addiction". Participants discussed and ranked the criteria in order of conceptual importance. The rankings were analyzed quantitatively, and then a multidisciplinary team compared the ranked criteria to the DSM-5 IGD proposed criteria. The strongest agreement between participants' rankings and IGD symptomatology was found for harms/functional impairment due to gaming, continued use despite problems, unsuccessful attempts to control gaming, and loss of interest in previous hobbies and entertainment. There was less support for other IGD criteria. Participants also offered new content domains. These findings suggest that collaborative knowledge-building approaches may help researchers and policymakers understand the characteristics and processes specific to problematic video game play and improve content validity of IGD criteria. Future efforts may benefit from multi-stakeholder approaches to refine IGD criteria and inform theory, measurement and intervention.

A Bayesian alternative for multi-objective ecohydrological model specification

NASA Astrophysics Data System (ADS)

Tang, Yating; Marshall, Lucy; Sharma, Ashish; Ajami, Hoori

2018-01-01

Recent studies have identified the importance of vegetation processes in terrestrial hydrologic systems. Process-based ecohydrological models combine hydrological, physical, biochemical and ecological processes of the catchments, and as such are generally more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov chain Monte Carlo (MCMC) techniques. The Bayesian approach offers an appealing alternative to traditional multi-objective hydrologic model calibrations by defining proper prior distributions that can be considered analogous to the ad-hoc weighting often prescribed in multi-objective calibration. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological modeling framework based on a traditional Pareto-based model calibration technique. In our study, a Pareto-based multi-objective optimization and a formal Bayesian framework are implemented in a conceptual ecohydrological model that combines a hydrological model (HYMOD) and a modified Bucket Grassland Model (BGM). Simulations focused on one objective (streamflow/LAI) and multiple objectives (streamflow and LAI) with different emphasis defined via the prior distribution of the model error parameters. Results show more reliable outputs for both predicted streamflow and LAI using Bayesian multi-objective calibration with specified prior distributions for error parameters based on results from the Pareto front in the ecohydrological modeling. The methodology implemented here provides insight into the usefulness of multiobjective Bayesian calibration for ecohydrologic systems and the importance of appropriate prior distributions in such approaches.

A Bayesian Alternative for Multi-objective Ecohydrological Model Specification

NASA Astrophysics Data System (ADS)

Tang, Y.; Marshall, L. A.; Sharma, A.; Ajami, H.

2015-12-01

Process-based ecohydrological models combine the study of hydrological, physical, biogeochemical and ecological processes of the catchments, which are usually more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov Chain Monte Carlo (MCMC) techniques. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological framework. In our study, a formal Bayesian approach is implemented in an ecohydrological model which combines a hydrological model (HyMOD) and a dynamic vegetation model (DVM). Simulations focused on one objective likelihood (Streamflow/LAI) and multi-objective likelihoods (Streamflow and LAI) with different weights are compared. Uniform, weakly informative and strongly informative prior distributions are used in different simulations. The Kullback-leibler divergence (KLD) is used to measure the dis(similarity) between different priors and corresponding posterior distributions to examine the parameter sensitivity. Results show that different prior distributions can strongly influence posterior distributions for parameters, especially when the available data is limited or parameters are insensitive to the available data. We demonstrate differences in optimized parameters and uncertainty limits in different cases based on multi-objective likelihoods vs. single objective likelihoods. We also demonstrate the importance of appropriately defining the weights of objectives in multi-objective calibration according to different data types.

Optimization of response surface and neural network models in conjugation with desirability function for estimation of nutritional needs of methionine, lysine, and threonine in broiler chickens.

PubMed

Mehri, Mehran

2014-07-01

The optimization algorithm of a model may have significant effects on the final optimal values of nutrient requirements in poultry enterprises. In poultry nutrition, the optimal values of dietary essential nutrients are very important for feed formulation to optimize profit through minimizing feed cost and maximizing bird performance. This study was conducted to introduce a novel multi-objective algorithm, desirability function, for optimization the bird response models based on response surface methodology (RSM) and artificial neural network (ANN). The growth databases on the central composite design (CCD) were used to construct the RSM and ANN models and optimal values for 3 essential amino acids including lysine, methionine, and threonine in broiler chicks have been reevaluated using the desirable function in both analytical approaches from 3 to 16 d of age. Multi-objective optimization results showed that the most desirable function was obtained for ANN-based model (D = 0.99) where the optimal levels of digestible lysine (dLys), digestible methionine (dMet), and digestible threonine (dThr) for maximum desirability were 13.2, 5.0, and 8.3 g/kg of diet, respectively. However, the optimal levels of dLys, dMet, and dThr in the RSM-based model were estimated at 11.2, 5.4, and 7.6 g/kg of diet, respectively. This research documented that the application of ANN in the broiler chicken model along with a multi-objective optimization algorithm such as desirability function could be a useful tool for optimization of dietary amino acids in fractional factorial experiments, in which the use of the global desirability function may be able to overcome the underestimations of dietary amino acids resulting from the RSM model. © 2014 Poultry Science Association Inc.

Assessment, design and control strategy development of a fuel cell hybrid electric vehicle for CSU's EcoCAR

NASA Astrophysics Data System (ADS)

Fox, Matthew D.

Advanced automotive technology assessment and powertrain design are increasingly performed through modeling, simulation, and optimization. But technology assessments usually target many competing criteria making any individual optimization challenging and arbitrary. Further, independent design simulations and optimizations take considerable time to execute, and design constraints and objectives change throughout the design process. Changes in design considerations usually require re-processing of simulations and more time. In this thesis, these challenges are confronted through CSU's participation in the EcoCAR2 hybrid vehicle design competition. The complexity of the competition's design objectives leveraged development of a decision support system tool to aid in multi-criteria decision making across technologies and to perform powertrain optimization. To make the decision support system interactive, and bypass the problem of long simulation times, a new approach was taken. The result of this research is CSU's architecture selection and component sizing, which optimizes a composite objective function representing the competition score. The selected architecture is an electric vehicle with an onboard range extending hydrogen fuel cell system. The vehicle has a 145kW traction motor, 18.9kWh of lithium ion battery, a 15kW fuel cell system, and 5kg of hydrogen storage capacity. Finally, a control strategy was developed that improves the vehicles performance throughout the driving range under variable driving conditions. In conclusion, the design process used in this research is reviewed and evaluated against other common design methodologies. I conclude, through the highlighted case studies, that the approach is more comprehensive than other popular design methodologies and is likely to lead to a higher quality product. The upfront modeling work and decision support system formulation will pay off in superior and timely knowledge transfer and more informed design decisions. The hypothesis is supported by the three case studies examined in this thesis.

Multi-channel distributed coordinated function over single radio in wireless sensor networks.

PubMed

Campbell, Carlene E-A; Loo, Kok-Keong Jonathan; Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

2011-01-01

Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band.

Multi-Channel Distributed Coordinated Function over Single Radio in Wireless Sensor Networks

PubMed Central

Campbell, Carlene E.-A.; Loo, Kok-Keong (Jonathan); Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

2011-01-01

Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band. PMID:22346614

Non-contact radio frequency shielding and wave guiding by multi-folded transformation optics method

PubMed Central

Madni, Hamza Ahmad; Zheng, Bin; Yang, Yihao; Wang, Huaping; Zhang, Xianmin; Yin, Wenyan; Li, Erping; Chen, Hongsheng

2016-01-01

Compared with conventional radio frequency (RF) shielding methods in which the conductive coating material encloses the circuits design and the leakage problem occurs due to the gap in such conductive material, non-contact RF shielding at a distance is very promising but still impossible to achieve so far. In this paper, a multi-folded transformation optics method is proposed to design a non-contact device for RF shielding. This “open-shielded” device can shield any object at a distance from the electromagnetic waves at the operating frequency, while the object is still physically open to the outer space. Based on this, an open-carpet cloak is proposed and the functionality of the open-carpet cloak is demonstrated. Furthermore, we investigate a scheme of non-contact wave guiding to remotely control the propagation of surface waves over any obstacles. The flexibilities of such multi-folded transformation optics method demonstrate the powerfulness of the method in the design of novel remote devices with impressive new functionalities. PMID:27841358

A multi-objective optimization approach for the selection of working fluids of geothermal facilities: Economic, environmental and social aspects.

PubMed

Martínez-Gomez, Juan; Peña-Lamas, Javier; Martín, Mariano; Ponce-Ortega, José María

2017-12-01

The selection of the working fluid for Organic Rankine Cycles has traditionally been addressed from systematic heuristic methods, which perform a characterization and prior selection considering mainly one objective, thus avoiding a selection considering simultaneously the objectives related to sustainability and safety. The objective of this work is to propose a methodology for the optimal selection of the working fluid for Organic Rankine Cycles. The model is presented as a multi-objective approach, which simultaneously considers the economic, environmental and safety aspects. The economic objective function considers the profit obtained by selling the energy produced. Safety was evaluated in terms of individual risk for each of the components of the Organic Rankine Cycles and it was formulated as a function of the operating conditions and hazardous properties of each working fluid. The environmental function is based on carbon dioxide emissions, considering carbon dioxide mitigation, emission due to the use of cooling water as well emissions due material release. The methodology was applied to the case of geothermal facilities to select the optimal working fluid although it can be extended to waste heat recovery. The results show that the hydrocarbons represent better solutions, thus among a list of 24 working fluids, toluene is selected as the best fluid. Copyright © 2017 Elsevier Ltd. All rights reserved.

Non-monetary valuation using Multi-Criteria Decision Analysis: Sensitivity of additive aggregation methods to scaling and compensation assumptions

EPA Science Inventory

Analytical methods for Multi-Criteria Decision Analysis (MCDA) support the non-monetary valuation of ecosystem services for environmental decision making. Many published case studies transform ecosystem service outcomes into a common metric and aggregate the outcomes to set land ...

DATA COLLECTION MANAGER MODULE OF REGION III'S MULTI-CRITERIA INTEGRATED RESOURCE ASSESSMENT (MIRA) ENVIRONMENTAL DECISION MAKING APPROACH

EPA Science Inventory

This proposal pertains to the on-going development of the Data Collection Manager (DCM) module, which is one of three modules that compose MIRA, Multi-criteria Integrated Resource Assessment. MIRA is Region III's newly conceived and continually developing decision support approac...

Comorbidities in Spondyloarthritis associate with poor function, work disability and quality of life: Results from the ASAS-COMOSPA study.

PubMed

Nikiphorou, E; Ramiro, S; van der Heijde, D; Norton, S; Moltó, A; Dougados, M; van den Bosch, F; Landewé, R

2017-11-10

Comorbidities add to the burden of disease and its complexity, and may prevent the achievement of treat-to-target goals. The objective of this study was to study the relationship between comorbidities and key disease outcomes in Spondyloarthritis, namely function, work ability and quality of life. Patients from the multi-national (22 countries), cross-sectional ASAS-COMOSPA study were included in the analysis provided they fulfilled the ASAS criteria. Data on comorbidities based on both self- and physician-report were collected through questionnaires and were subsequently used to compute the Rheumatic Disease Comorbidity Index (RDCI). Univariable and multivariable (adjusted for relevant confounders) multilevel (with country as a random effect) linear or logistic (as appropriate) regression analyses were conducted to investigate the relationship between the RDCI and: (1) functional ability; (2) work ability; (3) quality of life. In total, 3370 of 3984 (85%) patients recruited fulfilled the ASAS criteria: 66% were male, mean (SD) age was 43 (14) years, mean (SD) disease duration was 8.4 (9.5) years and mean (SD) RDCI was 0.7 (1.1). At least one comorbidity was reported in 51% of patients; 9% had ≥3 comorbidities. RDCI was independently associated with higher BASFI (β=0.37;95%CI [0.30,0.43]); lower EuroQol five dimensions questionnaire (EQ5D:β=-0.03; [-0.04,-0.02]); less work employment (OR=0.83; [0.76,0.91]); higher absenteeism (β=1.18; [1.04,1.34]) and higher presenteeism (β=1.42; [1.26,1.61]). Comorbidities in SpA adversely influence physical function, work ability and quality of life and are important to take into account in daily clinical practice. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

B-spline parameterization of the dielectric function and information criteria: the craft of non-overfitting

NASA Astrophysics Data System (ADS)

Likhachev, Dmitriy V.

2017-06-01

Johs and Hale developed the Kramers-Kronig consistent B-spline formulation for the dielectric function modeling in spectroscopic ellipsometry data analysis. In this article we use popular Akaike, corrected Akaike and Bayesian Information Criteria (AIC, AICc and BIC, respectively) to determine an optimal number of knots for B-spline model. These criteria allow finding a compromise between under- and overfitting of experimental data since they penalize for increasing number of knots and select representation which achieves the best fit with minimal number of knots. Proposed approach provides objective and practical guidance, as opposite to empirically driven or "gut feeling" decisions, for selecting the right number of knots for B-spline models in spectroscopic ellipsometry. AIC, AICc and BIC selection criteria work remarkably well as we demonstrated in several real-data applications. This approach formalizes selection of the optimal knot number and may be useful in practical perspective of spectroscopic ellipsometry data analysis.

Multi-objective spatial tools to inform maritime spatial planning in the Adriatic Sea.

PubMed

Depellegrin, Daniel; Menegon, Stefano; Farella, Giulio; Ghezzo, Michol; Gissi, Elena; Sarretta, Alessandro; Venier, Chiara; Barbanti, Andrea

2017-12-31

This research presents a set of multi-objective spatial tools for sea planning and environmental management in the Adriatic Sea Basin. The tools address four objectives: 1) assessment of cumulative impacts from anthropogenic sea uses on environmental components of marine areas; 2) analysis of sea use conflicts; 3) 3-D hydrodynamic modelling of nutrient dispersion (nitrogen and phosphorus) from riverine sources in the Adriatic Sea Basin and 4) marine ecosystem services capacity assessment from seabed habitats based on an ES matrix approach. Geospatial modelling results were illustrated, analysed and compared on country level and for three biogeographic subdivisions, Northern-Central-Southern Adriatic Sea. The paper discusses model results for their spatial implications, relevance for sea planning, limitations and concludes with an outlook towards the need for more integrated, multi-functional tools development for sea planning. Copyright © 2017. Published by Elsevier B.V.

A master-slave parallel hybrid multi-objective evolutionary algorithm for groundwater remediation design under general hydrogeological conditions

NASA Astrophysics Data System (ADS)

Wu, J.; Yang, Y.; Luo, Q.; Wu, J.

2012-12-01

This study presents a new hybrid multi-objective evolutionary algorithm, the niched Pareto tabu search combined with a genetic algorithm (NPTSGA), whereby the global search ability of niched Pareto tabu search (NPTS) is improved by the diversification of candidate solutions arose from the evolving nondominated sorting genetic algorithm II (NSGA-II) population. Also, the NPTSGA coupled with the commonly used groundwater flow and transport codes, MODFLOW and MT3DMS, is developed for multi-objective optimal design of groundwater remediation systems. The proposed methodology is then applied to a large-scale field groundwater remediation system for cleanup of large trichloroethylene (TCE) plume at the Massachusetts Military Reservation (MMR) in Cape Cod, Massachusetts. Furthermore, a master-slave (MS) parallelization scheme based on the Message Passing Interface (MPI) is incorporated into the NPTSGA to implement objective function evaluations in distributed processor environment, which can greatly improve the efficiency of the NPTSGA in finding Pareto-optimal solutions to the real-world application. This study shows that the MS parallel NPTSGA in comparison with the original NPTS and NSGA-II can balance the tradeoff between diversity and optimality of solutions during the search process and is an efficient and effective tool for optimizing the multi-objective design of groundwater remediation systems under complicated hydrogeologic conditions.

Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.

PubMed

Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

2016-01-01

Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.

Multi-resonant electromagnetic shunt in base isolation for vibration damping and energy harvesting

NASA Astrophysics Data System (ADS)

Pei, Yalu; Liu, Yilun; Zuo, Lei

2018-06-01

This paper investigates multi-resonant electromagnetic shunts applied to base isolation for dual-function vibration damping and energy harvesting. Two multi-mode shunt circuit configurations, namely parallel and series, are proposed and optimized based on the H2 criteria. The root-mean-square (RMS) value of the relative displacement between the base and the primary structure is minimized. Practically, this will improve the safety of base-isolated buildings subjected the broad bandwidth ground acceleration. Case studies of a base-isolated building are conducted in both the frequency and time domains to investigate the effectiveness of multi-resonant electromagnetic shunts under recorded earthquake signals. It shows that both multi-mode shunt circuits outperform traditional single mode shunt circuits by suppressing the first and the second vibration modes simultaneously. Moreover, for the same stiffness ratio, the parallel shunt circuit is more effective at harvesting energy and suppressing vibration, and can more robustly handle parameter mistuning than the series shunt circuit. Furthermore, this paper discusses experimental validation of the effectiveness of multi-resonant electromagnetic shunts for vibration damping and energy harvesting on a scaled-down base isolation system.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments.

PubMed

Wu, Paul P-Y; Campbell, Duncan; Merz, Torsten

2011-06-01

This paper presents Multi-Step A∗ (MSA∗), a search algorithm based on A∗ for multi-objective 4-D vehicle motion planning (three spatial and one time dimensions). The research is principally motivated by the need for offline and online motion planning for autonomous unmanned aerial vehicles (UAVs). For UAVs operating in large dynamic uncertain 4-D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and a grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles, and the rules of the air. It is shown that MSA∗ finds a cost optimal solution using variable length, angle, and velocity trajectory segments. These segments are approximated with a grid-based cell sequence that provides an inherent tolerance to uncertainty. The computational efficiency is achieved by using variable successor operators to create a multiresolution memory-efficient lattice sampling structure. The simulation studies on the UAV flight planning problem show that MSA∗ meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of a vector neighborhood-based A∗.

ELTs adaptive optics for multi-objects 3D spectroscopy: key parameters and design rules

NASA Astrophysics Data System (ADS)

Neichel, B.; Conan, J.-M.; Fusco, T.; Gendron, E.; Puech, M.; Rousset, G.; Hammer, F.

2006-06-01

In the last few years, new Adaptive Optics [AO] techniques have emerged to answer new astronomical challenges: Ground-Layer AO [GLAO] and Multi-Conjugate AO [MCAO] to access a wider Field of View [FoV], Multi-Object AO [MOAO] for the simultaneous observation of several faint galaxies, eXtreme AO [XAO] for the detection of faint companions. In this paper, we focus our study to one of these applications : high red-shift galaxy observations using MOAO techniques in the framework of Extremely Large Telescopes [ELTs]. We present the high-level specifications of a dedicated instrument. We choose to describe the scientific requirements with the following criteria : 40% of Ensquared Energy [EE] in H band (1.65μm) and in an aperture size from 25 to 150 mas. Considering these specifications we investigate different AO solutions thanks to Fourier based simulations. Sky Coverage [SC] is computed for Natural and Laser Guide Stars [NGS, LGS] systems. We show that specifications are met for NGS-based systems at the cost of an extremely low SC. For the LGS approach, the option of low order correction with a faint NGS is discussed. We demonstrate that, this last solution allows the scientific requirements to be met together with a quasi full SC.

Mapping Infected Area after a Flash-Flooding Storm Using Multi Criteria Analysis and Spectral Indices

NASA Astrophysics Data System (ADS)

Al-Akad, S.; Akensous, Y.; Hakdaoui, M.

2017-11-01

This research article is summarize the applications of remote sensing and GIS to study the urban floods risk in Al Mukalla. Satellite acquisition of a flood event on October 2015 in Al Mukalla (Yemen) by using flood risk mapping techniques illustrate the potential risk present in this city. Satellite images (The Landsat and DEM images data were atmospherically corrected, radiometric corrected, and geometric and topographic distortions rectified.) are used for flood risk mapping to afford a hazard (vulnerability) map. This map is provided by applying image-processing techniques and using geographic information system (GIS) environment also the application of NDVI, NDWI index, and a method to estimate the flood-hazard areas. Four factors were considered in order to estimate the spatial distribution of the hazardous areas: flow accumulation, slope, land use, geology and elevation. The multi-criteria analysis, allowing to deal with vulnerability to flooding, as well as mapping areas at the risk of flooding of the city Al Mukalla. The main object of this research is to provide a simple and rapid method to reduce and manage the risks caused by flood in Yemen by take as example the city of Al Mukalla.

Multi-criteria Decision Support System (DSS) for optimal locations of Soil Aquifer Treatment (SAT) facilities.

PubMed

Tsangaratos, P; Kallioras, A; Pizpikis, Th; Vasileiou, E; Ilia, I; Pliakas, F

2017-12-15

Managed Aquifer Recharge is a wide-spread well-established groundwater engineering method which is largely seen as sound and sustainable solution to water scarcity hydrologically sensitive areas, such as the Circum Mediterranean. The process of site selection for the installation of a MAR facility is of paramount importance for the feasibility and effectiveness of the project itself, especially when the facility will include the use of waters of impaired quality as a recharge source, as in the case of Soil-Aquifer-Treatment systems. The main objective of this study is to present the developed framework of a multi-criteria Decision Support System (DSS) that integrates within a dynamic platform the main groundwater engineering parameters associated with MAR applications together with the general geographical features which determine the effectiveness of such a project. The proposed system will provide an advanced coupled DSS-GIS tool capable of handling local MAR-related issues -such as hydrogeology, topography, soil, climate etc., and spatially distributed variables -such as societal, economic, administrative, legislative etc., with special reference to Soil-Aquifer-Treatment technologies. Copyright © 2017 Elsevier B.V. All rights reserved.

WCSC environmental process improvement study and demonstration program

NASA Technical Reports Server (NTRS)

Pawlick, Joseph F., Jr.; Severo, Orlando C.

1993-01-01

CSTAR's objective to develop commercial infrastructure is multi-faceted and includes diverse elements of the orbital and suborbital missions. Goals to this eight-month project with the WCSC are aimed at simplifying the environmental assessment, approval, and licensing process for commercial users. Included in this overarching set of goals are two specific processes: (1) air pollution control, and (2) the environmental assessment mechanism. Resolution of the potentially user unfriendly aspects of these environmentally sensitive criteria are readily transferable to other ranges where commercial space activity will be supported.

An Interactive Strategy for Solving Multi-Criteria Decision Making of Sustainable Land Revitalization Planning Problem

NASA Astrophysics Data System (ADS)

Mayasari, Ruth; Mawengkang, Herman; Gomar Purba, Ronal

2018-02-01

Land revitalization refers to comprehensive renovation of farmland, waterways, roads, forest or villages to improve the quality of plantation, raise the productivity of the plantation area and improve agricultural production conditions and the environment. The objective of sustainable land revitalization planning is to facilitate environmentally, socially, and economically viable land use. Therefore it is reasonable to use participatory approach to fullfil the plan. This paper addresses a multicriteria decision aid to model such planning problem, then we develop an interactive approach for solving the problem.

Multi-physics optimization of three-dimensional microvascular polymeric components

NASA Astrophysics Data System (ADS)

Aragón, Alejandro M.; Saksena, Rajat; Kozola, Brian D.; Geubelle, Philippe H.; Christensen, Kenneth T.; White, Scott R.

2013-01-01

This work discusses the computational design of microvascular polymeric materials, which aim at mimicking the behavior found in some living organisms that contain a vascular system. The optimization of the topology of the embedded three-dimensional microvascular network is carried out by coupling a multi-objective constrained genetic algorithm with a finite-element based physics solver, the latter validated through experiments. The optimization is carried out on multiple conflicting objective functions, namely the void volume fraction left by the network, the energy required to drive the fluid through the network and the maximum temperature when the material is subjected to thermal loads. The methodology presented in this work results in a viable alternative for the multi-physics optimization of these materials for active-cooling applications.

Earthquake Vulnerability Assessment for Hospital Buildings Using a Gis-Based Group Multi Criteria Decision Making Approach: a Case Study of Tehran, Iran

NASA Astrophysics Data System (ADS)

Delavar, M. R.; Moradi, M.; Moshiri, B.

2015-12-01

Nowadays, urban areas are threatened by a number of natural hazards such as flood, landslide and earthquake. They can cause huge damages to buildings and human beings which necessitates disaster mitigation and preparation. One of the most important steps in disaster management is to understand all impacts and effects of disaster on urban facilities. Given that hospitals take care of vulnerable people reaction of hospital buildings against earthquake is vital. In this research, the vulnerability of hospital buildings against earthquake is analysed. The vulnerability of buildings is related to a number of criteria including age of building, number of floors, the quality of materials and intensity of the earthquake. Therefore, the problem of seismic vulnerability assessment is a multi-criteria assessment problem and multi criteria decision making methods can be used to address the problem. In this paper a group multi criteria decision making model is applied because using only one expert's judgments can cause biased vulnerability maps. Sugeno integral which is able to take into account the interaction among criteria is employed to assess the vulnerability degree of buildings. Fuzzy capacities which are similar to layer weights in weighted linear averaging operator are calculated using particle swarm optimization. Then, calculated fuzzy capacities are included into the model to compute a vulnerability degree for each hospital.

Multitime correlation functions in nonclassical stochastic processes

NASA Astrophysics Data System (ADS)

Krumm, F.; Sperling, J.; Vogel, W.

2016-06-01

A general method is introduced for verifying multitime quantum correlations through the characteristic function of the time-dependent P functional that generalizes the Glauber-Sudarshan P function. Quantum correlation criteria are derived which identify quantum effects for an arbitrary number of points in time. The Magnus expansion is used to visualize the impact of the required time ordering, which becomes crucial in situations when the interaction problem is explicitly time dependent. We show that the latter affects the multi-time-characteristic function and, therefore, the temporal evolution of the nonclassicality. As an example, we apply our technique to an optical parametric process with a frequency mismatch. The resulting two-time-characteristic function yields full insight into the two-time quantum correlation properties of such a system.

Graphical representation of robot grasping quality measures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Varma, V.; Tasch, U.

1993-11-01

When an object is held by a multi-fingered hand, the values of the contact forces can be multivalued. An objective function, when used in conjunction with the frictional and geometric constraints of the grasp, can however, give a unique set of finger force values. The selection of the objective function in determining the finger forces is dependent on the type of grasp required, the material properties of the object, and the limitations of the robot fingers. In this paper several optimization functions are studied and their merits highlighted. A graphical representation of the finger force values and the objective functionmore » is introduced that enable one in selecting and comparing various grasping configurations. The impending motion of the object at different torque and finger force values are determined by observing the normalized coefficient of friction plots.« less

American Pancreatic Association Practice Guidelines in Chronic Pancreatitis: Evidence-Based Report on Diagnostic Guidelines

PubMed Central

Conwell, Darwin L.; Lee, Linda S.; Yadav, Dhiraj; Longnecker, Daniel S.; Miller, Frank H.; Mortele, Koenraad J.; Levy, Michael J.; Kwon, Richard; Lieb, John G.; Stevens, Tyler; Toskes, Philip P.; Gardner, Timothy B.; Gelrud, Andres; Wu, Bechien U.; Forsmark, Christopher E.; Vege, Santhi S.

2016-01-01

The diagnosis of chronic pancreatitis remains challenging in early stages of the disease. This report defines the diagnostic criteria useful in the assessment of patients with suspected and established chronic pancreatitis. All current diagnostic procedures are reviewed and evidence based statements are provided about their utility and limitations. Diagnostic criteria for chronic pancreatitis are classified as definitive, probable or insufficient evidence. A diagnostic (STEP-wise; S-survey, T-tomography, E-endoscopy and P-pancreas function testing) algorithm is proposed that proceeds from a non-invasive to a more invasive approach. This algorithm maximizes specificity (low false positive rate) in subjects with chronic abdominal pain and equivocal imaging changes. Futhermore, a nomenclature is suggested to further characterize patients with established chronic pancreatitis based on TIGAR-O (T-toxic, I-idiopathic, G-genetic, A- autoimmune, R-recurrent and O-obstructive) etiology, gland morphology (Cambridge criteria) and physiologic state (exocrine, endocrine function) for uniformity across future multi-center research collaborations. This guideline will serve as a baseline manuscript that will be modified as new evidence becomes available and our knowledge of chronic pancreatitis improves. PMID:25333398

A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

NASA Astrophysics Data System (ADS)

Yondo, Raul; Andrés, Esther; Valero, Eusebio

2018-01-01

Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-order) aerodynamic models or flight testing are some of the fundamental but complex steps in the various design phases of recent civil transport aircrafts. Current aircraft aerodynamic designs have increase in complexity (multidisciplinary, multi-objective or multi-fidelity) and need to address the challenges posed by the nonlinearity of the objective functions and constraints, uncertainty quantification in aerodynamic problems or the restrained computational budgets. With the aim to reduce the computational burden and generate low-cost but accurate models that mimic those full order models at different values of the design variables, Recent progresses have witnessed the introduction, in real-time and many-query analyses, of surrogate-based approaches as rapid and cheaper to simulate models. In this paper, a comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimensionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria. Benefits, drawbacks and comparative discussions in applying those methods are described. Furthermore, the paper familiarizes the readers with surrogate models that have been successfully applied to the general field of fluid dynamics, but not yet in the aerospace industry. Additionally, the review revisits the most popular sampling strategies used in conducting physical and simulation-based experiments in aircraft aerodynamic design. Attractive or smart designs infrequently used in the field and discussions on advanced sampling methodologies are presented, to give a glance on the various efficient possibilities to a priori sample the parameter space. Closing remarks foster on future perspectives, challenges and shortcomings associated with the use of surrogate models by aircraft industrial aerodynamicists, despite their increased interest among the research communities.

Case study comparison of functional vs. organic stability approaches for assessing threat potential at closed landfills in the USA.

PubMed

O'Donnell, Sean T; Caldwell, Michael D; Barlaz, Morton A; Morris, Jeremy W F

2018-05-01

Municipal solid waste (MSW) landfills in the USA are regulated under Subtitle D of the Resource Conservation and Recovery Act (RCRA), which includes the requirement to protect human health and the environment (HHE) during the post-closure care (PCC) period. Several approaches have been published for assessment of potential threats to HHE. These approaches can be broadly divided into organic stabilization, which establishes an inert waste mass as the ultimate objective, and functional stability, which considers long-term emissions in the context of minimizing threats to HHE in the absence of active controls. The objective of this research was to conduct a case study evaluation of a closed MSW landfill using long-term data on landfill gas (LFG) production, leachate quality, site geology, and solids decomposition. Evaluations based on both functional and organic stability criteria were compared. The results showed that longer periods of LFG and leachate management would be required using organic stability criteria relative to an approach based on functional stability. These findings highlight the somewhat arbitrary and overly stringent nature of assigning universal stability criteria without due consideration of the landfill's hydrogeologic setting and potential environmental receptors. This supports previous studies that advocated for transition to a passive or inactive control stage based on a performance-based functional stability framework as a defensible mechanism for optimizing and ending regulatory PCC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling Land Use/Cover Changes in an African Rural Landscape

NASA Astrophysics Data System (ADS)

Kamusoko, C.; Aniya, M.

2006-12-01

Land use/cover changes are analyzed in the Bindura district of Zimbabwe, Africa through the integration of data from a time series of Landsat imagery (1973, 1989 and 2000), a household survey and GIS coverages. We employed a hybrid supervised/unsupervised classification approach to generate land use/cover maps from which landscape metrics were calculated. Population and other household variables were derived from a sample of surveyed villages, while road accessibility and slope were obtained from topographic maps and digital elevation model, respectively. Markov-cellular automata modeling approach that incorporates Markov chain analysis, cellular automata and multi-criteria evaluation (MCE) / multi-objective allocation (MOLA) procedures was used to simulate land use/cover changes. A GIS-based MCE technique computed transition potential maps, whereas transition areas were derived from the 1973-2000 land use/cover maps using the Markov chain analysis. A 5 x 5 cellular automata filter was used to develop a spatially explicit contiguity- weighting factor to change the cells based on its previous state and those of its neighbors, while MOLA resolved land use/cover class allocation conflicts. The kappa index of agreement was used for model validation. Observed trends in land use/cover changes indicate that deforestation and the encroachment of cultivation in woodland areas is a continuous trend in the study area. This suggests that economic activities driven by agricultural expansion were the main causes of landscape fragmentation, leading to landscape degradation. Rigorous calibration of transition potential maps done by a MCE algorithm and Markovian transition probabilities produced accurate inputs for the simulation of land use/cover changes. Overall standard kappa index of agreement ranged from 0.73 to 0.83, which is sufficient for simulating land use/cover changes in the study area. Land use/cover simulations under the 1989 and 2000 scenario indicated further landscape degradation in the rural areas of the Bindura district. Keywords: Zimbabwe, land use/cover changes, landscape fragmentation, GIS, land use/cover change modeling, multi-criteria evaluation/multi-objective allocation procedures, Markov-cellular automata

The optimal design of UAV wing structure

NASA Astrophysics Data System (ADS)

Długosz, Adam; Klimek, Wiktor

2018-01-01

The paper presents an optimal design of UAV wing, made of composite materials. The aim of the optimization is to improve strength and stiffness together with reduction of the weight of the structure. Three different types of functionals, which depend on stress, stiffness and the total mass are defined. The paper presents an application of the in-house implementation of the evolutionary multi-objective algorithm in optimization of the UAV wing structure. Values of the functionals are calculated on the basis of results obtained from numerical simulations. Numerical FEM model, consisting of different composite materials is created. Adequacy of the numerical model is verified by results obtained from the experiment, performed on a tensile testing machine. Examples of multi-objective optimization by means of Pareto-optimal set of solutions are presented.

Attention enhances multi-voxel representation of novel objects in frontal, parietal and visual cortices.

PubMed

Woolgar, Alexandra; Williams, Mark A; Rich, Anina N

2015-04-01

Selective attention is fundamental for human activity, but the details of its neural implementation remain elusive. One influential theory, the adaptive coding hypothesis (Duncan, 2001, An adaptive coding model of neural function in prefrontal cortex, Nature Reviews Neuroscience 2:820-829), proposes that single neurons in certain frontal and parietal regions dynamically adjust their responses to selectively encode relevant information. This selective representation may in turn support selective processing in more specialized brain regions such as the visual cortices. Here, we use multi-voxel decoding of functional magnetic resonance images to demonstrate selective representation of attended--and not distractor--objects in frontal, parietal, and visual cortices. In addition, we highlight a critical role for task demands in determining which brain regions exhibit selective coding. Strikingly, representation of attended objects in frontoparietal cortex was highest under conditions of high perceptual demand, when stimuli were hard to perceive and coding in early visual cortex was weak. Coding in early visual cortex varied as a function of attention and perceptual demand, while coding in higher visual areas was sensitive to the allocation of attention but robust to changes in perceptual difficulty. Consistent with high-profile reports, peripherally presented objects could also be decoded from activity at the occipital pole, a region which corresponds to the fovea. Our results emphasize the flexibility of frontoparietal and visual systems. They support the hypothesis that attention enhances the multi-voxel representation of information in the brain, and suggest that the engagement of this attentional mechanism depends critically on current task demands. Copyright © 2015 Elsevier Inc. All rights reserved.

Measuring the Clustering Around Normal and Dust-Obscured Quasars at 2 in the Spitzer Extragalactic Representative Volume Survey (SERVS)

NASA Astrophysics Data System (ADS)

Jones, Kristen M.; Lacy, M.; Spitzer Extragalactic Representative Volume Survey Team

2014-01-01

Little is known about the environments of high redshift quasars, particularly those obscured by dust. Previous work suggests that dust-shrouded (type 2) quasars are at least as common as un-obscured optical (type 1) quasars; therefore, in order to fully understand the role quasars play in the evolutionary history of the universe, we must understand both types of objects. This project seeks to explore the environments in which obscured quasars form. In this poster, we present mid-infrared clustering measurements for a sample of 45 quasars with 1.3 < z < 2.5, a redshift range that is unexplored in the literature. The objects were selected using IRAC multi-color criteria to remove low-redshift starburst and quiescent galaxies, and subsequently had spectroscopy carried out to both obtain redshifts, and to distinguish between type 1 and type 2 quasars; the high-redshift sample presented in this paper is roughly evenly distributed between the two types. We use the SERVS galaxy catalogs to estimate the cross-correlation between each quasar and its surrounding galaxies. The amplitude of this function gives us the richness of the environments in which these quasars are found, and we compare our results with a matched sample with z < 1.3.

Predictors and Outcomes of Childhood Primary Enuresis

PubMed Central

Kessel, Ellen M.; Allmann, Anna E. S.; Goldstein, Brandon; Finsaas, Megan; Dougherty, Lea R.; Bufferd, Sara J.; Carlson, Gabrielle A.; Klein, Daniel N.

2017-01-01

Objective Although enuresis is relatively common in early childhood, research exploring its antecedents and implications is surprisingly limited, perhaps because the condition typically remits in middle childhood. Method We examined the prevalence, predictors, prognostic factors, and outcomes of primary enuresis in a large (N = 559) multi-method, multi-informant prospective study with a community-based sample of children followed from age 3 to age 9. Results We found that 12.7% of our sample met criteria for lifetime enuresis, suggesting that it is a commonly occurring childhood disorder. Males were over twice as likely to have a lifetime diagnosis than females. Significant age 3 predictors of developing primary enuresis at age 9 included child anxiety and low positive affectivity, maternal history of anxiety, and low authoritative parenting. In addition, poorer global functioning and more depressive and anxiety symptoms at age 3 predicted a greater likelihood of persistence through age 9. By age 9, 77% of children who had received a diagnosis of primary enuresis were in remission and continent. However, children who had remitted exhibited a higher rate of ADHD and greater ADHD and depressive symptoms at age 9 compared to children with no lifetime history of enuresis. Conclusions Results of the present study underscore the clinical significance of primary enuresis and demonstrate that it shows both strong antecedent and prospective associations with psychopathology. The findings also highlight the possible role of parenting in the development of enuresis. PMID:28219491

Multi-criteria manufacturability indices for ranking high-concentration monoclonal antibody formulations.

PubMed

Yang, Yang; Velayudhan, Ajoy; Thornhill, Nina F; Farid, Suzanne S

2017-09-01

The need for high-concentration formulations for subcutaneous delivery of therapeutic monoclonal antibodies (mAbs) can present manufacturability challenges for the final ultrafiltration/diafiltration (UF/DF) step. Viscosity levels and the propensity to aggregate are key considerations for high-concentration formulations. This work presents novel frameworks for deriving a set of manufacturability indices related to viscosity and thermostability to rank high-concentration mAb formulation conditions in terms of their ease of manufacture. This is illustrated by analyzing published high-throughput biophysical screening data that explores the influence of different formulation conditions (pH, ions, and excipients) on the solution viscosity and product thermostability. A decision tree classification method, CART (Classification and Regression Tree) is used to identify the critical formulation conditions that influence the viscosity and thermostability. In this work, three different multi-criteria data analysis frameworks were investigated to derive manufacturability indices from analysis of the stress maps and the process conditions experienced in the final UF/DF step. Polynomial regression techniques were used to transform the experimental data into a set of stress maps that show viscosity and thermostability as functions of the formulation conditions. A mathematical filtrate flux model was used to capture the time profiles of protein concentration and flux decay behavior during UF/DF. Multi-criteria decision-making analysis was used to identify the optimal formulation conditions that minimize the potential for both viscosity and aggregation issues during UF/DF. Biotechnol. Bioeng. 2017;114: 2043-2056. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Perodicals, Inc. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Perodicals, Inc.

Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

NASA Astrophysics Data System (ADS)

Faber, W. R.; Zaidi, W.; Hussein, I. I.; Roscoe, C. W. T.; Wilkins, M. P.; Schumacher, P. W., Jr.

As more objects are launched into space, the potential for breakup events and space object collisions is ever increasing. These events create large clouds of debris that are extremely hazardous to space operations. Providing timely, accurate, and statistically meaningful Space Situational Awareness (SSA) data is crucial in order to protect assets and operations in space. The space object tracking problem, in general, is nonlinear in both state dynamics and observations, making it ill-suited to linear filtering techniques such as the Kalman filter. Additionally, given the multi-object, multi-scenario nature of the problem, space situational awareness requires multi-hypothesis tracking and management that is combinatorially challenging in nature. In practice, it is often seen that assumptions of underlying linearity and/or Gaussianity are used to provide tractable solutions to the multiple space object tracking problem. However, these assumptions are, at times, detrimental to tracking data and provide statistically inconsistent solutions. This paper details a tractable solution to the multiple space object tracking problem applicable to space object breakup events. Within this solution, simplifying assumptions of the underlying probability density function are relaxed and heuristic methods for hypothesis management are avoided. This is done by implementing Sequential Monte Carlo (SMC) methods for both nonlinear filtering as well as hypothesis management. This goal of this paper is to detail the solution and use it as a platform to discuss computational limitations that hinder proper analysis of large breakup events.

Design criteria for a PC-based common user interface to remote information systems

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Hall, Philip P.

1984-01-01

A set of design criteria are presented which will allow the implementation of an interface to multiple remote information systems on a microcomputer. The focus of the design description is on providing the user with the functionality required to retrieve, store and manipulate data residing in remote information systems through the utilization of a standardized interface system. The intent is to spare the user from learning the details of retrieval from specific systems while retaining the full capabilities of each system. The system design includes multi-level capabilities to enhance usability by a wide range of users and utilizes microcomputer graphics capabilities where applicable. A data collection subsystem for evaluation purposes is also described.

Stability of discrete time recurrent neural networks and nonlinear optimization problems.

PubMed

Singh, Jayant; Barabanov, Nikita

2016-02-01

We consider the method of Reduction of Dissipativity Domain to prove global Lyapunov stability of Discrete Time Recurrent Neural Networks. The standard and advanced criteria for Absolute Stability of these essentially nonlinear systems produce rather weak results. The method mentioned above is proved to be more powerful. It involves a multi-step procedure with maximization of special nonconvex functions over polytopes on every step. We derive conditions which guarantee an existence of at most one point of local maximum for such functions over every hyperplane. This nontrivial result is valid for wide range of neuron transfer functions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improving IT Portfolio Management Decision Confidence Using Multi-Criteria Decision Making and Hypervariate Display Techniques

ERIC Educational Resources Information Center

Landmesser, John Andrew

2014-01-01

Information technology (IT) investment decision makers are required to process large volumes of complex data. An existing body of knowledge relevant to IT portfolio management (PfM), decision analysis, visual comprehension of large volumes of information, and IT investment decision making suggest Multi-Criteria Decision Making (MCDM) and…

Balancing costs and benefits at different stages of medical innovation: a systematic review of Multi-criteria decision analysis (MCDA).

PubMed

Wahlster, Philip; Goetghebeur, Mireille; Kriza, Christine; Niederländer, Charlotte; Kolominsky-Rabas, Peter

2015-07-09

The diffusion of health technologies from translational research to reimbursement depends on several factors included the results of health economic analysis. Recent research identified several flaws in health economic concepts. Additionally, the heterogeneous viewpoints of participating stakeholders are rarely systematically addressed in current decision-making. Multi-criteria Decision Analysis (MCDA) provides an opportunity to tackle these issues. The objective of this study was to review applications of MCDA methods in decisions addressing the trade-off between costs and benefits. Using basic steps of the PRISMA guidelines, a systematic review of the healthcare literature was performed to identify original research articles from January 1990 to April 2014. Medline, PubMed, Springer Link and specific journals were searched. Using predefined categories, bibliographic records were systematically extracted regarding the type of policy applications, MCDA methodology, criteria used and their definitions. 22 studies were included in the analysis. 15 studies (68 %) used direct MCDA approaches and seven studies (32 %) used preference elicitation approaches. Four studies (19 %) focused on technologies in the early innovation process. The majority (18 studies - 81 %) examined reimbursement decisions. Decision criteria used in studies were obtained from the literature research and context-specific studies, expert opinions, and group discussions. The number of criteria ranged between three up to 15. The most frequently used criteria were health outcomes (73 %), disease impact (59 %), and implementation of the intervention (40 %). Economic criteria included cost-effectiveness criteria (14 studies, 64 %), and total costs/budget impact of an intervention (eight studies, 36 %). The process of including economic aspects is very different among studies. Some studies directly compare costs with other criteria while some include economic consideration in a second step. In early innovation processes, MCDA can provide information about stakeholder preferences as well as evidence needs in further development. However, only a minority of these studies include economic features due to the limited evidence. The most important economic criterion cost-effectiveness should not be included from a technical perspective as it is already a composite of costs and benefit. There is a significant lack of consensus in methodology employed by the various studies which highlights the need for guidance on application of MCDA at specific phases of an innovation.

How do new dams impact downstream countries? - A screening approach to identify the best compromise assets and negotiate their designs

NASA Astrophysics Data System (ADS)

Geressu, Robel; Harou, Julien

2015-04-01

Water use rights are disputed in many transboundary basins. Even when water projects can benefit all, agreeing on cost and benefit sharing can be difficult where stakeholders have conflicting preferences on the designs and use of proposed water infrastructures. This study suggests a combination of many objective optimization and multi-criteria ranking methods to support negotiations regarding designs of new assets. The method allows competing users to assess development options based on their individual perspectives and agree on designs by incorporating coordination strategies into multi-reservoir system designs. We demonstrate a hypothetical negotiation on proposed Blue Nile reservoirs. The result form a set of Pareto-optimal designs i.e., reservoirs, storage capacity and their operating rules, and power trade, cost sharing and/or financing coordination strategies, which maximize benefit to all countries and show which trade-offs are implied by which designs. The approach fulfils decision-maker's desire to understand a) the critical design parameters that affect various objectives and b) how coordination mechanisms would enable them to incur benefits from proposed new dams.

Multi Objective Optimization Using Genetic Algorithm of a Pneumatic Connector

NASA Astrophysics Data System (ADS)

Salaam, HA; Taha, Zahari; Ya, TMYS Tuan

2018-03-01

The concept of sustainability was first introduced by Dr Harlem Brutland in the 1980’s promoting the need to preserve today’s natural environment for the sake of future generations. Based on this concept, John Elkington proposed an approach to measure sustainability known as Triple Bottom Line (TBL). There are three evaluation criteria’s involved in the TBL approach; namely economics, environmental integrity and social equity. In manufacturing industry the manufacturing costs measure the economic sustainability of a company in a long term. Environmental integrity is a measure of the impact of manufacturing activities on the environment. Social equity is complicated to evaluate; but when the focus is at the production floor level, the production operator health can be considered. In this paper, the TBL approach is applied in the manufacturing of a pneumatic nipple hose. The evaluation criteria used are manufacturing costs, environmental impact, ergonomics impact and also energy used for manufacturing. This study involves multi objective optimization by using genetic algorithm of several possible alternatives for material used in the manufacturing of the pneumatic nipple.

Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm

NASA Astrophysics Data System (ADS)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.

[Diagnosis and the technology for optimizing the medical support of a troop unit].

PubMed

Korshever, N G; Polkovov, S V; Lavrinenko, O V; Krupnov, P A; Anastasov, K N

2000-05-01

The work is devoted to investigation of the system of military unit medical support with the use of principles and states of organizational diagnosis; development of the method allowing to assess its functional activity; and determination of optimization trends. Basing on the conducted organizational diagnosis and expert inquiry the informative criteria were determined which characterize the stages of functioning of the military unit medical support system. To evaluate the success of military unit medical support the complex multi-criteria pattern was developed and algorithm of this process optimization was substantiated. Using the results obtained, particularly realization of principles and states of decision taking theory in machine program it is possible to solve more complex problem of comparison between any number of military units: to dispose them according to priority decrease; to select the programmed number of the best and worst; to determine the trends of activity optimization in corresponding medical service personnel.

Mathematical Methods of System Analysis in Construction Materials

NASA Astrophysics Data System (ADS)

Garkina, Irina; Danilov, Alexander

2017-10-01

System attributes of construction materials are defined: complexity of an object, integrity of set of elements, existence of essential, stable relations between elements defining integrative properties of system, existence of structure, etc. On the basis of cognitive modelling (intensive and extensive properties; the operating parameters) materials (as difficult systems) and creation of the cognitive map the hierarchical modular structure of criteria of quality is under construction. It actually is a basis for preparation of the specification on development of material (the required organization and properties). Proceeding from a modern paradigm (model of statement of problems and their decisions) of development of materials, levels and modules are specified in structure of material. It when using the principles of the system analysis allows to considered technological process as the difficult system consisting of elements of the distinguished specification level: from atomic before separate process. Each element of system depending on an effective objective is considered as separate system with more detailed levels of decomposition. Among them, semantic and qualitative analyses of an object (are considered a research objective, decomposition levels, separate elements and communications between them come to light). Further formalization of the available knowledge in the form of mathematical models (structural identification) is carried out; communications between input and output parameters (parametrical identification) are defined. Hierarchical structures of criteria of quality are under construction for each allocated level. On her the relevant hierarchical structures of system (material) are under construction. Regularities of structurization and formation of properties, generally are considered at the levels from micro to a macrostructure. The mathematical model of material is represented as set of the models corresponding to private criteria by which separate modules and their levels (the mathematical description, a decision algorithm) are defined. Adequacy is established (compliance of results of modelling to experimental data; is defined by the level of knowledge of process and validity of the accepted assumptions). The global criterion of quality of material is considered as a set of private criteria (properties). Synthesis of material is carried out on the basis of one-criteria optimization on each of the chosen private criteria. Results of one-criteria optimization are used at multicriteria optimization. The methods of developing materials as single-purpose, multi-purpose, including contradictory, systems are indicated. The scheme of synthesis of composite materials as difficult systems is developed. The specified system approach effectively was used in case of synthesis of composite materials with special properties.

A new web-based framework development for fuzzy multi-criteria group decision-making.

PubMed

Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

2016-01-01

Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.

Applying a multi-criteria genetic algorithm framework for brownfield reuse optimization: improving redevelopment options based on stakeholder preferences.

PubMed

Morio, Maximilian; Schädler, Sebastian; Finkel, Michael

2013-11-30

The reuse of underused or abandoned contaminated land, so-called brownfields, is increasingly seen as an important means for reducing the consumption of land and natural resources. Many existing decision support systems are not appropriate because they focus mainly on economic aspects, while neglecting sustainability issues. To fill this gap, we present a framework for spatially explicit, integrated planning and assessment of brownfield redevelopment options. A multi-criteria genetic algorithm allows us to determine optimal land use configurations with respect to assessment criteria and given constraints on the composition of land use classes, according to, e.g., stakeholder preferences. Assessment criteria include sustainability indicators as well as economic aspects, including remediation costs and land value. The framework is applied to a case study of a former military site near Potsdam, Germany. Emphasis is placed on the trade-off between possibly conflicting objectives (e.g., economic goals versus the need for sustainable development in the regional context of the brownfield site), which may represent different perspectives of involved stakeholders. The economic analysis reveals the trade-off between the increase in land value due to reuse and the costs for remediation required to make reuse possible. We identify various reuse options, which perform similarly well although they exhibit different land use patterns. High-cost high-value options dominated by residential land use and low-cost low-value options with less sensitive land use types may perform equally well economically. The results of the integrated analysis show that the quantitative integration of sustainability may change optimal land use patterns considerably. Copyright © 2013 Elsevier Ltd. All rights reserved.

Adaptation policies to increase terrestrial ecosystem resilience. Potential utility of a multicriteria approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

de Bremond, Ariane; Engle, Nathan L.

2014-01-30

Climate change is rapidly undermining terrestrial ecosystem resilience and capacity to continue providing their services to the benefit of humanity and nature. Because of the importance of terrestrial ecosystems to human well-being and supporting services, decision makers throughout the world are busy creating policy responses that secure multiple development and conservation objectives- including that of supporting terrestrial ecosystem resilience in the context of climate change. This article aims to advance analyses on climate policy evaluation and planning in the area of terrestrial ecosystem resilience by discussing adaptation policy options within the ecology-economy-social nexus. The paper evaluates these decisions in themore » realm of terrestrial ecosystem resilience and evaluates the utility of a set of criteria, indicators, and assessment methods, proposed by a new conceptual multi-criteria framework for pro-development climate policy and planning developed by the United Nations Environment Programme. Potential applications of a multicriteria approach to climate policy vis-A -vis terrestrial ecosystems are then explored through two hypothetical case study examples. The paper closes with a brief discussion of the utility of the multi-criteria approach in the context of other climate policy evaluation approaches, considers lessons learned as a result efforts to evaluate climate policy in the realm of terrestrial ecosystems, and reiterates the role of ecosystem resilience in creating sound policies and actions that support the integration of climate change and development goals.« less

Biokinetic model-based multi-objective optimization of Dunaliella tertiolecta cultivation using elitist non-dominated sorting genetic algorithm with inheritance.

PubMed

Sinha, Snehal K; Kumar, Mithilesh; Guria, Chandan; Kumar, Anup; Banerjee, Chiranjib

2017-10-01

Algal model based multi-objective optimization using elitist non-dominated sorting genetic algorithm with inheritance was carried out for batch cultivation of Dunaliella tertiolecta using NPK-fertilizer. Optimization problems involving two- and three-objective functions were solved simultaneously. The objective functions are: maximization of algae-biomass and lipid productivity with minimization of cultivation time and cost. Time variant light intensity and temperature including NPK-fertilizer, NaCl and NaHCO 3 loadings are the important decision variables. Algal model involving Monod/Andrews adsorption kinetics and Droop model with internal nutrient cell quota was used for optimization studies. Sets of non-dominated (equally good) Pareto optimal solutions were obtained for the problems studied. It was observed that time variant optimal light intensity and temperature trajectories, including optimum NPK fertilizer, NaCl and NaHCO 3 concentration has significant influence to improve biomass and lipid productivity under minimum cultivation time and cost. Proposed optimization studies may be helpful to implement the control strategy in scale-up operation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimizing structure of complex technical system by heterogeneous vector criterion in interval form

NASA Astrophysics Data System (ADS)

Lysenko, A. V.; Kochegarov, I. I.; Yurkov, N. K.; Grishko, A. K.

2018-05-01

The article examines the methods of development and multi-criteria choice of the preferred structural variant of the complex technical system at the early stages of its life cycle in the absence of sufficient knowledge of parameters and variables for optimizing this structure. The suggested methods takes into consideration the various fuzzy input data connected with the heterogeneous quality criteria of the designed system and the parameters set by their variation range. The suggested approach is based on the complex use of methods of interval analysis, fuzzy sets theory, and the decision-making theory. As a result, the method for normalizing heterogeneous quality criteria has been developed on the basis of establishing preference relations in the interval form. The method of building preferential relations in the interval form on the basis of the vector of heterogeneous quality criteria suggest the use of membership functions instead of the coefficients considering the criteria value. The former show the degree of proximity of the realization of the designed system to the efficient or Pareto optimal variants. The study analyzes the example of choosing the optimal variant for the complex system using heterogeneous quality criteria.

The Neurologic Assessment in Neuro-Oncology (NANO) scale: a tool to assess neurologic function for integration into the Response Assessment in Neuro-Oncology (RANO) criteria

PubMed Central

DeAngelis, Lisa M.; Brandes, Alba A.; Peereboom, David M.; Galanis, Evanthia; Lin, Nancy U.; Soffietti, Riccardo; Macdonald, David R.; Chamberlain, Marc; Perry, James; Jaeckle, Kurt; Mehta, Minesh; Stupp, Roger; Muzikansky, Alona; Pentsova, Elena; Cloughesy, Timothy; Iwamoto, Fabio M.; Tonn, Joerg-Christian; Vogelbaum, Michael A.; Wen, Patrick Y.; van den Bent, Martin J.; Reardon, David A.

2017-01-01

Abstract Background. The Macdonald criteria and the Response Assessment in Neuro-Oncology (RANO) criteria define radiologic parameters to classify therapeutic outcome among patients with malignant glioma and specify that clinical status must be incorporated and prioritized for overall assessment. But neither provides specific parameters to do so. We hypothesized that a standardized metric to measure neurologic function will permit more effective overall response assessment in neuro-oncology. Methods. An international group of physicians including neurologists, medical oncologists, radiation oncologists, and neurosurgeons with expertise in neuro-oncology drafted the Neurologic Assessment in Neuro-Oncology (NANO) scale as an objective and quantifiable metric of neurologic function evaluable during a routine office examination. The scale was subsequently tested in a multicenter study to determine its overall reliability, inter-observer variability, and feasibility. Results. The NANO scale is a quantifiable evaluation of 9 relevant neurologic domains based on direct observation and testing conducted during routine office visits. The score defines overall response criteria. A prospective, multinational study noted a >90% inter-observer agreement rate with kappa statistic ranging from 0.35 to 0.83 (fair to almost perfect agreement), and a median assessment time of 4 minutes (interquartile range, 3–5). Conclusion. The NANO scale provides an objective clinician-reported outcome of neurologic function with high inter-observer agreement. It is designed to combine with radiographic assessment to provide an overall assessment of outcome for neuro-oncology patients in clinical trials and in daily practice. Furthermore, it complements existing patient-reported outcomes and cognition testing to combine for a global clinical outcome assessment of well-being among brain tumor patients. PMID:28453751

Enduring Mental Health Morbidity and Social Function Impairment in World Trade Center Rescue, Recovery, and Cleanup Workers: The Psychological Dimension of an Environmental Health Disaster

PubMed Central

Stellman, Jeanne Mager; Smith, Rebecca P.; Katz, Craig L.; Sharma, Vansh; Charney, Dennis S.; Herbert, Robin; Moline, Jacqueline; Luft, Benjamin J.; Markowitz, Steven; Udasin, Iris; Harrison, Denise; Baron, Sherry; Landrigan, Philip J.; Levin, Stephen M.; Southwick, Steven

2008-01-01

Background The World Trade Center (WTC) attacks exposed thousands of workers to hazardous environmental conditions and psychological trauma. In 2002, to assess the health of these workers, Congress directed the National Institute for Occupational Safety and Health to establish the WTC Medical Monitoring and Treatment Program. This program has established a large cohort of WTC rescue, recovery, and cleanup workers. We previously documented extensive pulmonary dysfunction in this cohort related to toxic environmental exposures. Objectives Our objective in this study was to describe mental health outcomes, social function impairment, and psychiatric comorbidity in the WTC worker cohort, as well as perceived symptomatology in workers’ children. Methods Ten to 61 months after the WTC attack, 10,132 WTC workers completed a self-administered mental health questionnaire. Results Of the workers who completd the questionnaire, 11.1% met criteria for probable post-traumatic stress disorder (PTSD), 8.8% met criteria for probable depression, 5.0% met criteria for probable panic disorder, and 62% met criteria for substantial stress reaction. PTSD prevalence was comparable to that seen in returning Afghanistan war veterans and was much higher than in the U.S. general population. Point prevalence declined from 13.5% to 9.7% over the 5 years of observation. Comorbidity was extensive and included extremely high risks for impairment of social function. PTSD was significantly associated with loss of family members and friends, disruption of family, work, and social life, and higher rates of behavioral symptoms in children of workers. Conclusions Working in 9/11 recovery operations is associated with chronic impairment of mental health and social functioning. Psychological distress and psychopathology in WTC workers greatly exceed population norms. Surveillance and treatment programs continue to be needed. PMID:18795171

Multi-objective and Perishable Fuzzy Inventory Models Having Weibull Life-time With Time Dependent Demand, Demand Dependent Production and Time Varying Holding Cost: A Possibility/Necessity Approach

NASA Astrophysics Data System (ADS)

Pathak, Savita; Mondal, Seema Sarkar

2010-10-01

A multi-objective inventory model of deteriorating item has been developed with Weibull rate of decay, time dependent demand, demand dependent production, time varying holding cost allowing shortages in fuzzy environments for non- integrated and integrated businesses. Here objective is to maximize the profit from different deteriorating items with space constraint. The impreciseness of inventory parameters and goals for non-integrated business has been expressed by linear membership functions. The compromised solutions are obtained by different fuzzy optimization methods. To incorporate the relative importance of the objectives, the different cardinal weights crisp/fuzzy have been assigned. The models are illustrated with numerical examples and results of models with crisp/fuzzy weights are compared. The result for the model assuming them to be integrated business is obtained by using Generalized Reduced Gradient Method (GRG). The fuzzy integrated model with imprecise inventory cost is formulated to optimize the possibility necessity measure of fuzzy goal of the objective function by using credibility measure of fuzzy event by taking fuzzy expectation. The results of crisp/fuzzy integrated model are illustrated with numerical examples and results are compared.

Multi-objective optimization for model predictive control.

PubMed

Wojsznis, Willy; Mehta, Ashish; Wojsznis, Peter; Thiele, Dirk; Blevins, Terry

2007-06-01

This paper presents a technique of multi-objective optimization for Model Predictive Control (MPC) where the optimization has three levels of the objective function, in order of priority: handling constraints, maximizing economics, and maintaining control. The greatest weights are assigned dynamically to control or constraint variables that are predicted to be out of their limits. The weights assigned for economics have to out-weigh those assigned for control objectives. Control variables (CV) can be controlled at fixed targets or within one- or two-sided ranges around the targets. Manipulated Variables (MV) can have assigned targets too, which may be predefined values or current actual values. This MV functionality is extremely useful when economic objectives are not defined for some or all the MVs. To achieve this complex operation, handle process outputs predicted to go out of limits, and have a guaranteed solution for any condition, the technique makes use of the priority structure, penalties on slack variables, and redefinition of the constraint and control model. An engineering implementation of this approach is shown in the MPC embedded in an industrial control system. The optimization and control of a distillation column, the standard Shell heavy oil fractionator (HOF) problem, is adequately achieved with this MPC.

Cardiac Light-Sheet Fluorescent Microscopy for Multi-Scale and Rapid Imaging of Architecture and Function

NASA Astrophysics Data System (ADS)

Fei, Peng; Lee, Juhyun; Packard, René R. Sevag; Sereti, Konstantina-Ioanna; Xu, Hao; Ma, Jianguo; Ding, Yichen; Kang, Hanul; Chen, Harrison; Sung, Kevin; Kulkarni, Rajan; Ardehali, Reza; Kuo, C.-C. Jay; Xu, Xiaolei; Ho, Chih-Ming; Hsiai, Tzung K.

2016-03-01

Light Sheet Fluorescence Microscopy (LSFM) enables multi-dimensional and multi-scale imaging via illuminating specimens with a separate thin sheet of laser. It allows rapid plane illumination for reduced photo-damage and superior axial resolution and contrast. We hereby demonstrate cardiac LSFM (c-LSFM) imaging to assess the functional architecture of zebrafish embryos with a retrospective cardiac synchronization algorithm for four-dimensional reconstruction (3-D space + time). By combining our approach with tissue clearing techniques, we reveal the entire cardiac structures and hypertrabeculation of adult zebrafish hearts in response to doxorubicin treatment. By integrating the resolution enhancement technique with c-LSFM to increase the resolving power under a large field-of-view, we demonstrate the use of low power objective to resolve the entire architecture of large-scale neonatal mouse hearts, revealing the helical orientation of individual myocardial fibers. Therefore, our c-LSFM imaging approach provides multi-scale visualization of architecture and function to drive cardiovascular research with translational implication in congenital heart diseases.

Investigating multi-objective fluence and beam orientation IMRT optimization

NASA Astrophysics Data System (ADS)

Potrebko, Peter S.; Fiege, Jason; Biagioli, Matthew; Poleszczuk, Jan

2017-07-01

Radiation Oncology treatment planning requires compromises to be made between clinical objectives that are invariably in conflict. It would be beneficial to have a ‘bird’s-eye-view’ perspective of the full spectrum of treatment plans that represent the possible trade-offs between delivering the intended dose to the planning target volume (PTV) while optimally sparing the organs-at-risk (OARs). In this work, the authors demonstrate Pareto-aware radiotherapy evolutionary treatment optimization (PARETO), a multi-objective tool featuring such bird’s-eye-view functionality, which optimizes fluence patterns and beam angles for intensity-modulated radiation therapy (IMRT) treatment planning. The problem of IMRT treatment plan optimization is managed as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. To achieve this, PARETO is built around a powerful multi-objective evolutionary algorithm, called Ferret, which simultaneously optimizes multiple fitness functions that encode the attributes of the desired dose distribution for the PTV and OARs. The graphical interfaces within PARETO provide useful information such as: the convergence behavior during optimization, trade-off plots between the competing objectives, and a graphical representation of the optimal solution database allowing for the rapid exploration of treatment plan quality through the evaluation of dose-volume histograms and isodose distributions. PARETO was evaluated for two relatively complex clinical cases, a paranasal sinus and a pancreas case. The end result of each PARETO run was a database of optimal (non-dominated) treatment plans that demonstrated trade-offs between the OAR and PTV fitness functions, which were all equally good in the Pareto-optimal sense (where no one objective can be improved without worsening at least one other). Ferret was able to produce high quality solutions even though a large number of parameters, such as beam fluence and beam angles, were included in the optimization.

Research of Simple Multi-Attribute Rating Technique for Decision Support

NASA Astrophysics Data System (ADS)

Siregar, Dodi; Arisandi, Diki; Usman, Ari; Irwan, Dedy; Rahim, Robbi

2017-12-01

One of the roles of decision support system is that it can assist the decision maker in obtaining the appropriate alternative with the desired criteria, one of the methods that could apply for the decision maker is SMART method with multicriteria decision making. This multi-criteria decision-making theory has meaning where every alternative has criteria and has value and weight, and the author uses this approach to facilitate decision making with a compelling case. The problems discussed in this paper are classified into problems of a variety Multiobjective (multiple goals to be accomplished) and multicriteria (many of the decisive criteria in reaching such decisions).

Participatory flood vulnerability assessment: a multi-criteria approach

NASA Astrophysics Data System (ADS)

Madruga de Brito, Mariana; Evers, Mariele; Delos Santos Almoradie, Adrian

2018-01-01

This paper presents a participatory multi-criteria decision-making (MCDM) approach for flood vulnerability assessment while considering the relationships between vulnerability criteria. The applicability of the proposed framework is demonstrated in the municipalities of Lajeado and Estrela, Brazil. The model was co-constructed by 101 experts from governmental organizations, universities, research institutes, NGOs, and private companies. Participatory methods such as the Delphi survey, focus groups, and workshops were applied. A participatory problem structuration, in which the modellers work closely with end users, was used to establish the structure of the vulnerability index. The preferences of each participant regarding the criteria importance were spatially modelled through the analytical hierarchy process (AHP) and analytical network process (ANP) multi-criteria methods. Experts were also involved at the end of the modelling exercise for validation. The final product is a set of individual and group flood vulnerability maps. Both AHP and ANP proved to be effective for flood vulnerability assessment; however, ANP is preferred as it considers the dependences among criteria. The participatory approach enabled experts to learn from each other and acknowledge different perspectives towards social learning. The findings highlight that to enhance the credibility and deployment of model results, multiple viewpoints should be integrated without forcing consensus.

Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

Towards lexicographic multi-objective linear programming using grossone methodology

NASA Astrophysics Data System (ADS)

Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.

2016-10-01

Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.

Energy acceptance and on momentum aperture optimization for the Sirius project

NASA Astrophysics Data System (ADS)

Dester, P. S.; Sá, F. H.; Liu, L.

2017-07-01

A fast objective function to calculate Touschek lifetime and on momentum aperture is essential to explore the vast search space of strength of quadrupole and sextupole families in Sirius. Touschek lifetime is estimated by using the energy aperture (dynamic and physical), RF system parameters and driving terms. Non-linear induced betatron oscillations are considered to determine the energy aperture. On momentum aperture is estimated by using a chaos indicator and resonance crossing considerations. Touschek lifetime and on momentum aperture constitute the objective function, which was used in a multi-objective genetic algorithm to perform an optimization for Sirius.

Comparison of Evolutionary (Genetic) Algorithm and Adjoint Methods for Multi-Objective Viscous Airfoil Optimizations

NASA Technical Reports Server (NTRS)

Pulliam, T. H.; Nemec, M.; Holst, T.; Zingg, D. W.; Kwak, Dochan (Technical Monitor)

2002-01-01

A comparison between an Evolutionary Algorithm (EA) and an Adjoint-Gradient (AG) Method applied to a two-dimensional Navier-Stokes code for airfoil design is presented. Both approaches use a common function evaluation code, the steady-state explicit part of the code,ARC2D. The parameterization of the design space is a common B-spline approach for an airfoil surface, which together with a common griding approach, restricts the AG and EA to the same design space. Results are presented for a class of viscous transonic airfoils in which the optimization tradeoff between drag minimization as one objective and lift maximization as another, produces the multi-objective design space. Comparisons are made for efficiency, accuracy and design consistency.

Energy Technology Allocation for Distributed Energy Resources: A Technology-Policy Framework

NASA Astrophysics Data System (ADS)

Mallikarjun, Sreekanth

Distributed energy resources (DER) are emerging rapidly. New engineering technologies, materials, and designs improve the performance and extend the range of locations for DER. In contrast, constructing new or modernizing existing high voltage transmission lines for centralized generation are expensive and challenging. In addition, customer demand for reliability has increased and concerns about climate change have created a pull for swift renewable energy penetration. In this context, DER policy makers, developers, and users are interested in determining which energy technologies to use to accommodate different end-use energy demands. We present a two-stage multi-objective strategic technology-policy framework for determining the optimal energy technology allocation for DER. The framework simultaneously considers economic, technical, and environmental objectives. The first stage utilizes a Data Envelopment Analysis model for each end-use to evaluate the performance of each energy technology based on the three objectives. The second stage incorporates factor efficiencies determined in the first stage, capacity limitations, dispatchability, and renewable penetration for each technology, and demand for each end-use into a bottleneck multi-criteria decision model which provides the Pareto-optimal energy resource allocation. We conduct several case studies to understand the roles of various distributed energy technologies in different scenarios. We construct some policy implications based on the model results of set of case studies.

Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

NASA Astrophysics Data System (ADS)

Peng, Haijun; Wang, Wei

2016-10-01

An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

Association between the -455T>C promoter polymorphism of the APOC3 gene and the metabolic syndrome in a multi-ethnic sample.

PubMed

Pollex, Rebecca L; Ban, Matthew R; Young, T Kue; Bjerregaard, Peter; Anand, Sonia S; Yusuf, Salim; Zinman, Bernard; Harris, Stewart B; Hanley, Anthony J G; Connelly, Philip W; Huff, Murray W; Hegele, Robert A

2007-12-20

Common polymorphisms in the promoter of the APOC3 gene have been associated with hypertriglyceridemia and may impact on phenotypic expression of the metabolic syndrome (MetS). The rs7566605 marker, located near the INSIG2 gene, has been found to be associated with obesity, making it also a potential genetic determinant for MetS. The objective of this study is to examine the APOC3 -455T>C and the INSIG2 rs7566605 polymorphisms as potential genetic determinants for MetS in a multi-ethnic sample. Subjects were genotyped for both the APOC3 -455T>C and INSIG2 rs7566605 polymorphisms, and classified for the presence or absence of MetS (NCEP ATP III and IDF definitions). The total study population included 2675 subjects (> or =18 years of age) from six different geographical ancestries. For the overall study population, the prevalence of MetS was 22.6% (NCEP ATP III definition). Carriers of > or =1 copy of APOC3 -455C were more likely to have MetS (NCEP ATP III definition) than noncarriers (carrier odds ratio 1.73, 95% CI 1.40 to 2.14, adjusting for age and study group). The basis of the association was related not only to a higher proportion of -455C carriers meeting the triglyceride and high-density lipoprotein cholesterol criteria, but also the blood pressure criteria compared with wild-type homozygotes. Plasma apo C-III concentrations were not associated with APOC3 -455T>C genotype. The INSIG2 rs7566605 polymorphism was not associated with MetS or measures of obesity. Meta-analysis of the sample of multiple geographic ancestries indicated that the functional -455T>C promoter polymorphism in APOC3 was associated with an approximately 2-fold increased risk of MetS, whereas the INSIG2 rs7566605 polymorphism was not associated with MetS.

Association between the -455T>C promoter polymorphism of the APOC3 gene and the metabolic syndrome in a multi-ethnic sample

PubMed Central

Pollex, Rebecca L; Ban, Matthew R; Young, T Kue; Bjerregaard, Peter; Anand, Sonia S; Yusuf, Salim; Zinman, Bernard; Harris, Stewart B; Hanley, Anthony JG; Connelly, Philip W; Huff, Murray W; Hegele, Robert A

2007-01-01

Background Common polymorphisms in the promoter of the APOC3 gene have been associated with hypertriglyceridemia and may impact on phenotypic expression of the metabolic syndrome (MetS). The rs7566605 marker, located near the INSIG2 gene, has been found to be associated with obesity, making it also a potential genetic determinant for MetS. The objective of this study is to examine the APOC3 -455T>C and the INSIG2 rs7566605 polymorphisms as potential genetic determinants for MetS in a multi-ethnic sample. Methods Subjects were genotyped for both the APOC3 -455T>C and INSIG2 rs7566605 polymorphisms, and classified for the presence or absence of MetS (NCEP ATP III and IDF definitions). The total study population included 2675 subjects (≥18 years of age) from six different geographical ancestries. Results For the overall study population, the prevalence of MetS was 22.6% (NCEP ATP III definition). Carriers of ≥1 copy of APOC3 -455C were more likely to have MetS (NCEP ATP III definition) than noncarriers (carrier odds ratio 1.73, 95% CI 1.40 to 2.14, adjusting for age and study group). The basis of the association was related not only to a higher proportion of -455C carriers meeting the triglyceride and high-density lipoprotein cholesterol criteria, but also the blood pressure criteria compared with wild-type homozygotes. Plasma apo C-III concentrations were not associated with APOC3 -455T>C genotype. The INSIG2 rs7566605 polymorphism was not associated with MetS or measures of obesity. Conclusion Meta-analysis of the sample of multiple geographic ancestries indicated that the functional -455T>C promoter polymorphism in APOC3 was associated with an approximately 2-fold increased risk of MetS, whereas the INSIG2 rs7566605 polymorphism was not associated with MetS. PMID:18096054

MCSDSS: A Multi-Criteria Decision Support System for Merging Geoscience Information with Natural User Interfaces, Preference Ranking, and Interactive Data Utilities

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Gentle, J.

2015-12-01

The multi-criteria decision support system (MCSDSS) is a newly completed application for touch-enabled group decision support that uses D3 data visualization tools, a geojson conversion utility that we developed, and Paralelex to create an interactive tool. The MCSDSS is a prototype system intended to demonstrate the potential capabilities of a single page application (SPA) running atop a web and cloud based architecture utilizing open source technologies. The application is implemented on current web standards while supporting human interface design that targets both traditional mouse/keyboard interactions and modern touch/gesture enabled interactions. The technology stack for MCSDSS was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The application integrates current frameworks for highly performant agile development with unit testing, statistical analysis, data visualization, mapping technologies, geographic data manipulation, and cloud infrastructure while retaining support for traditional HTML5/CSS3 web standards. The software lifecylcle for MCSDSS has following best practices to develop, share, and document the codebase and application. Code is documented and shared via an online repository with the option for programmers to see, contribute, or fork the codebase. Example data files and tutorial documentation have been shared with clear descriptions and data object identifiers. And the metadata about the application has been incorporated into an OntoSoft entry to ensure that MCSDSS is searchable and clearly described. MCSDSS is a flexible platform that allows for data fusion and inclusion of large datasets in an interactive front-end application capable of connecting with other science-based applications and advanced computing resources. In addition, MCSDSS offers functionality that enables communication with non-technical users for policy, education, or engagement with groups around scientific topics with societal relevance.

A Comprehensive, Multi-modal Evaluation of the Assessment System of an Undergraduate Research Methodology Course: Translating Theory into Practice

PubMed Central

Mohammad Abdulghani, Hamza; G. Ponnamperuma, Gominda; Ahmad, Farah; Amin, Zubair

2014-01-01

Objective: To evaluate assessment system of the 'Research Methodology Course' using utility criteria (i.e. validity, reliability, acceptability, educational impact, and cost-effectiveness). This study demonstrates comprehensive evaluation of assessment system and suggests a framework for similar courses. Methods: Qualitative and quantitative methods used for evaluation of the course assessment components (50 MCQ, 3 Short Answer Questions (SAQ) and research project) using the utility criteria. Results of multiple evaluation methods for all the assessment components were collected and interpreted together to arrive at holistic judgments, rather than judgments based on individual methods or individual assessment. Results: Face validity, evaluated using a self-administered questionnaire (response rate-88.7%) disclosed that the students perceived that there was an imbalance in the contents covered by the assessment. This was confirmed by the assessment blueprint. Construct validity was affected by the low correlation between MCQ and SAQ scores (r=0.326). There was a higher correlation between the project and MCQ (r=0.466)/SAQ (r=0.463) scores. Construct validity was also affected by the presence of recall type of MCQs (70%; 35/50), item construction flaws and non-functioning distractors. High discriminating indices (>0.35) were found in MCQs with moderate difficulty indices (0.3-0.7). Reliability of the MCQs was 0.75 which could be improved up to 0.8 by increasing the number of MCQs to at least 70. A positive educational impact was found in the form of the research project assessment driving students to present/publish their work in conferences/peer reviewed journals. Cost per student to complete the course was US$164.50. Conclusions: The multi-modal evaluation of an assessment system is feasible and provides thorough and diagnostic information. Utility of the assessment system could be further improved by modifying the psychometrically inappropriate assessment items. PMID:24772117

Priority setting for the prevention and control of cardiovascular diseases: multi-criteria decision analysis in four eastern Mediterranean countries.

PubMed

Ghandour, Rula; Shoaibi, Azza; Khatib, Rana; Abu Rmeileh, Niveen; Unal, Belgin; Sözmen, Kaan; Kılıç, Bülent; Fouad, Fouad; Al Ali, Radwan; Ben Romdhane, Habiba; Aissi, Wafa; Ahmad, Balsam; Capewell, Simon; Critchley, Julia; Husseini, Abdullatif

2015-01-01

To explore the feasibility of using a simple multi-criteria decision analysis method with policy makers/key stakeholders to prioritize cardiovascular disease (CVD) policies in four Mediterranean countries: Palestine, Syria, Tunisia and Turkey. A simple multi-criteria decision analysis (MCDA) method was piloted. A mixed methods study was used to identify a preliminary list of policy options in each country. These policies were rated by different policymakers/stakeholders against pre-identified criteria to generate a priority score for each policy and then rank the policies. Twenty-five different policies were rated in the four countries to create a country-specific list of CVD prevention and control policies. The response rate was 100% in each country. The top policies were mostly population level interventions and health systems' level policies. Successful collaboration between policy makers/stakeholders and researchers was established in this small pilot study. MCDA appeared to be feasible and effective. Future applications should aim to engage a larger, representative sample of policy makers, especially from outside the health sector. Weighting the selected criteria might also be assessed.

Multi-level multi-criteria analysis of alternative fuels for waste collection vehicles in the United States.

PubMed

Maimoun, Mousa; Madani, Kaveh; Reinhart, Debra

2016-04-15

Historically, the U.S. waste collection fleet was dominated by diesel-fueled waste collection vehicles (WCVs); the growing need for sustainable waste collection has urged decision makers to incorporate economically efficient alternative fuels, while mitigating environmental impacts. The pros and cons of alternative fuels complicate the decisions making process, calling for a comprehensive study that assesses the multiple factors involved. Multi-criteria decision analysis (MCDA) methods allow decision makers to select the best alternatives with respect to selection criteria. In this study, two MCDA methods, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW), were used to rank fuel alternatives for the U.S. waste collection industry with respect to a multi-level environmental and financial decision matrix. The environmental criteria consisted of life-cycle emissions, tail-pipe emissions, water footprint (WFP), and power density, while the financial criteria comprised of vehicle cost, fuel price, fuel price stability, and fueling station availability. The overall analysis showed that conventional diesel is still the best option, followed by hydraulic-hybrid WCVs, landfill gas (LFG) sourced natural gas, fossil natural gas, and biodiesel. The elimination of the WFP and power density criteria from the environmental criteria ranked biodiesel 100 (BD100) as an environmentally better alternative compared to other fossil fuels (diesel and natural gas). This result showed that considering the WFP and power density as environmental criteria can make a difference in the decision process. The elimination of the fueling station and fuel price stability criteria from the decision matrix ranked fossil natural gas second after LFG-sourced natural gas. This scenario was found to represent the status quo of the waste collection industry. A sensitivity analysis for the status quo scenario showed the overall ranking of diesel and fossil natural gas to be more sensitive to changing fuel prices as compared to other alternatives. Copyright © 2016 Elsevier B.V. All rights reserved.

Multi-criteria decision-making on assessment of proposed tidal barrage schemes in terms of environmental impacts.

PubMed

Wu, Yunna; Xu, Chuanbo; Ke, Yiming; Chen, Kaifeng; Xu, Hu

2017-12-15

For tidal range power plants to be sustainable, the environmental impacts caused by the implement of various tidal barrage schemes must be assessed before construction. However, several problems exist in the current researches: firstly, evaluation criteria of the tidal barrage schemes environmental impact assessment (EIA) are not adequate; secondly, uncertainty of criteria information fails to be processed properly; thirdly, correlation among criteria is unreasonably measured. Hence the contributions of this paper are as follows: firstly, an evaluation criteria system is established from three dimensions of hydrodynamic, biological and morphological aspects. Secondly, cloud model is applied to describe the uncertainty of criteria information. Thirdly, Choquet integral with respect to λ-fuzzy measure is introduced to measure the correlation among criteria. On the above bases, a multi-criteria decision-making decision framework for tidal barrage scheme EIA is established to select the optimal scheme. Finally, a case study demonstrates the effectiveness of the proposed framework. Copyright © 2017 Elsevier Ltd. All rights reserved.

Keeping All the PIECES: Phylogenetically Informed Ex Situ Conservation of Endangered Species.

PubMed

Larkin, Daniel J; Jacobi, Sarah K; Hipp, Andrew L; Kramer, Andrea T

2016-01-01

Ex situ conservation in germplasm and living collections is a major focus of global plant conservation strategies. Prioritizing species for ex situ collection is a necessary component of this effort for which sound strategies are needed. Phylogenetic considerations can play an important role in prioritization. Collections that are more phylogenetically diverse are likely to encompass more ecological and trait variation, and thus provide stronger conservation insurance and richer resources for future restoration efforts. However, phylogenetic criteria need to be weighed against other, potentially competing objectives. We used ex situ collection and threat rank data for North American angiosperms to investigate gaps in ex situ coverage and phylogenetic diversity of collections and to develop a flexible framework for prioritizing species across multiple objectives. We found that ex situ coverage of 18,766 North American angiosperm taxa was low with respect to the most vulnerable taxa: just 43% of vulnerable to critically imperiled taxa were in ex situ collections, far short of a year-2020 goal of 75%. In addition, species held in ex situ collections were phylogenetically clustered (P < 0.001), i.e., collections comprised less phylogenetic diversity than would be expected had species been drawn at random. These patterns support incorporating phylogenetic considerations into ex situ prioritization in a manner balanced with other criteria, such as vulnerability. To meet this need, we present the 'PIECES' index (Phylogenetically Informed Ex situ Conservation of Endangered Species). PIECES integrates phylogenetic considerations into a flexible framework for prioritizing species across competing objectives using multi-criteria decision analysis. Applying PIECES to prioritizing ex situ conservation of North American angiosperms, we show strong return on investment across multiple objectives, some of which are negatively correlated with each other. A spreadsheet-based decision support tool for North American angiosperms is provided; this tool can be customized to align with different conservation objectives.

Keeping All the PIECES: Phylogenetically Informed Ex Situ Conservation of Endangered Species

PubMed Central

Larkin, Daniel J.; Jacobi, Sarah K.; Hipp, Andrew L.; Kramer, Andrea T.

2016-01-01

Ex situ conservation in germplasm and living collections is a major focus of global plant conservation strategies. Prioritizing species for ex situ collection is a necessary component of this effort for which sound strategies are needed. Phylogenetic considerations can play an important role in prioritization. Collections that are more phylogenetically diverse are likely to encompass more ecological and trait variation, and thus provide stronger conservation insurance and richer resources for future restoration efforts. However, phylogenetic criteria need to be weighed against other, potentially competing objectives. We used ex situ collection and threat rank data for North American angiosperms to investigate gaps in ex situ coverage and phylogenetic diversity of collections and to develop a flexible framework for prioritizing species across multiple objectives. We found that ex situ coverage of 18,766 North American angiosperm taxa was low with respect to the most vulnerable taxa: just 43% of vulnerable to critically imperiled taxa were in ex situ collections, far short of a year-2020 goal of 75%. In addition, species held in ex situ collections were phylogenetically clustered (P < 0.001), i.e., collections comprised less phylogenetic diversity than would be expected had species been drawn at random. These patterns support incorporating phylogenetic considerations into ex situ prioritization in a manner balanced with other criteria, such as vulnerability. To meet this need, we present the ‘PIECES’ index (Phylogenetically Informed Ex situ Conservation of Endangered Species). PIECES integrates phylogenetic considerations into a flexible framework for prioritizing species across competing objectives using multi-criteria decision analysis. Applying PIECES to prioritizing ex situ conservation of North American angiosperms, we show strong return on investment across multiple objectives, some of which are negatively correlated with each other. A spreadsheet-based decision support tool for North American angiosperms is provided; this tool can be customized to align with different conservation objectives. PMID:27257671

The use of multi-criteria decision making models in evaluating anesthesia method options in circumcision surgery.

PubMed

Hancerliogullari, Gulsah; Hancerliogullari, Kadir Oymen; Koksalmis, Emrah

2017-01-23

Determining the most suitable anesthesia method for circumcision surgery plays a fundamental role in pediatric surgery. This study is aimed to present pediatric surgeons' perspective on the relative importance of the criteria for selecting anesthesia method for circumcision surgery by utilizing the multi-criteria decision making methods. Fuzzy set theory offers a useful tool for transforming linguistic terms into numerical assessments. Since the evaluation of anesthesia methods requires linguistic terms, we utilize the fuzzy Analytic Hierarchy Process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Both mathematical decision-making methods are originated from individual judgements for qualitative factors utilizing the pair-wise comparison matrix. Our model uses four main criteria, eight sub-criteria as well as three alternatives. To assess the relative priorities, an online questionnaire was completed by three experts, pediatric surgeons, who had experience with circumcision surgery. Discussion of the results with the experts indicates that time-related factors are the most important criteria, followed by psychology, convenience and duration. Moreover, general anesthesia with penile block for circumcision surgery is the preferred choice of anesthesia compared to general anesthesia without penile block, which has a greater priority compared to local anesthesia under the discussed main-criteria and sub-criteria. The results presented in this study highlight the need to integrate surgeons' criteria into the decision making process for selecting anesthesia methods. This is the first study in which multi-criteria decision making tools, specifically fuzzy AHP and fuzzy TOPSIS, are used to evaluate anesthesia methods for a pediatric surgical procedure.

Weighted feature selection criteria for visual servoing of a telerobot

NASA Technical Reports Server (NTRS)

Feddema, John T.; Lee, C. S. G.; Mitchell, O. R.

1989-01-01

Because of the continually changing environment of a space station, visual feedback is a vital element of a telerobotic system. A real time visual servoing system would allow a telerobot to track and manipulate randomly moving objects. Methodologies for the automatic selection of image features to be used to visually control the relative position between an eye-in-hand telerobot and a known object are devised. A weighted criteria function with both image recognition and control components is used to select the combination of image features which provides the best control. Simulation and experimental results of a PUMA robot arm visually tracking a randomly moving carburetor gasket with a visual update time of 70 milliseconds are discussed.

An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing Problems

PubMed Central

Yu, Hao; Solvang, Wei Deng

2016-01-01

Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment. PMID:27258293

An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing Problems.

PubMed

Yu, Hao; Solvang, Wei Deng

2016-05-31

Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.

Management of complex knowledge in planning for sustainable development: The use of multi-criteria decision aids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kain, Jaan-Henrik; Soederberg, Henriette

2008-01-15

The vision of sustainable development entails new and complex planning situations, confronting local policy makers with changing political conditions, different content in decision making and planning and new working methods. Moreover, the call for sustainable development has been a major driving force towards an increasingly multi-stakeholder planning system. This situation requires competence in working in, and managing, groups of actors, including not only experts and project owners but also other categories of stakeholders. Among other qualities, such competence requires a working strategy aimed at integrating various, and sometimes incommensurable, forms of knowledge to construct a relevant and valid knowledge basemore » prior to decision making. Consequently, there lies great potential in methods that facilitate the evaluation of strategies for infrastructural development across multiple knowledge areas, so-called multi-criteria decision aids (MCDAs). In the present article, observations from six case studies are discussed, where the common denominators are infrastructural planning, multi-stakeholder participation and the use of MCDAs as interactive decision support. Three MCDAs are discussed - NAIADE, SCA and STRAD - with an emphasis on how they function in their procedural context. Accordingly, this is not an analysis of MCDA algorithms, of software programming aspects or of MCDAs as context-independent 'decision machines'-the focus is on MCDAs as actor systems, not as expert systems. The analysis is carried out across four main themes: (a) symmetrical management of different forms of knowledge; (b) management of heterogeneity, pluralism and conflict; (c) functionality and ease of use; and (d) transparency and trust. It shows that STRAD, by far, seems to be the most useful MCDA in interactive settings. NAIADE and SCA are roughly equivalent but have their strengths and weaknesses in different areas. Moreover, it was found that some MCDA issues require further attention, i.e., regarding transparency and understandability; qualitative/quantitative knowledge input; switching between different modes of weighting; software flexibility; as well as graphic and user interfaces.« less

The aerodynamic design of an advanced rotor airfoil

NASA Technical Reports Server (NTRS)

Blackwell, J. A., Jr.; Hinson, B. L.

1978-01-01

An advanced rotor airfoil, designed utilizing supercritical airfoil technology and advanced design and analysis methodology is described. The airfoil was designed subject to stringent aerodynamic design criteria for improving the performance over the entire rotor operating regime. The design criteria are discussed. The design was accomplished using a physical plane, viscous, transonic inverse design procedure, and a constrained function minimization technique for optimizing the airfoil leading edge shape. The aerodynamic performance objectives of the airfoil are discussed.

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks.

PubMed

Keel, Brittney N; Deng, Bo; Moriyama, Etsuko N

2018-04-15

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot. emoriyama2@unl.edu. Supplementary data are available at Bioinformatics online.

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

A multi-objective optimization approach accurately resolves protein domain architectures

PubMed Central

Bernardes, J.S.; Vieira, F.R.J.; Zaverucha, G.; Carbone, A.

2016-01-01

Motivation: Given a protein sequence and a number of potential domains matching it, what are the domain content and the most likely domain architecture for the sequence? This problem is of fundamental importance in protein annotation, constituting one of the main steps of all predictive annotation strategies. On the other hand, when potential domains are several and in conflict because of overlapping domain boundaries, finding a solution for the problem might become difficult. An accurate prediction of the domain architecture of a multi-domain protein provides important information for function prediction, comparative genomics and molecular evolution. Results: We developed DAMA (Domain Annotation by a Multi-objective Approach), a novel approach that identifies architectures through a multi-objective optimization algorithm combining scores of domain matches, previously observed multi-domain co-occurrence and domain overlapping. DAMA has been validated on a known benchmark dataset based on CATH structural domain assignments and on the set of Plasmodium falciparum proteins. When compared with existing tools on both datasets, it outperforms all of them. Availability and implementation: DAMA software is implemented in C++ and the source code can be found at http://www.lcqb.upmc.fr/DAMA. Contact: juliana.silva_bernardes@upmc.fr or alessandra.carbone@lip6.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26458889

User-Centric Multi-Criteria Information Retrieval

NASA Technical Reports Server (NTRS)

Wolfe, Shawn R.; Zhang, Yi

2009-01-01

Information retrieval models usually represent content only, and not other considerations, such as authority, cost, and recency. How could multiple criteria be utilized in information retrieval, and how would it affect the results? In our experiments, using multiple user-centric criteria always produced better results than a single criteria.

Focusing elliptical laser beams

NASA Astrophysics Data System (ADS)

Marchant, A. B.

1984-03-01

The spot formed by focusing an elliptical laser beam through an ordinary objective lens can be optimized by properly filling the objective lens. Criteria are given for maximizing the central irradiance and the line-spread function. An optimized spot is much less elliptical than the incident laser beam. For beam ellipticities as high as 2:1, this spatial filtering reduces the central irradiance by less than 14 percent.

Shapes, scents and sounds: quantifying the full multi-sensory basis of conceptual knowledge.

PubMed

Hoffman, Paul; Lambon Ralph, Matthew A

2013-01-01

Contemporary neuroscience theories assume that concepts are formed through experience in multiple sensory-motor modalities. Quantifying the contribution of each modality to different object categories is critical to understanding the structure of the conceptual system and to explaining category-specific knowledge deficits. Verbal feature listing is typically used to elicit this information but has a number of drawbacks: sensory knowledge often cannot easily be translated into verbal features and many features are experienced in multiple modalities. Here, we employed a more direct approach in which subjects rated their knowledge of objects in each sensory-motor modality separately. Compared with these ratings, feature listing over-estimated the importance of visual form and functional knowledge and under-estimated the contributions of other sensory channels. An item's sensory rating proved to be a better predictor of lexical-semantic processing speed than the number of features it possessed, suggesting that ratings better capture the overall quantity of sensory information associated with a concept. Finally, the richer, multi-modal rating data not only replicated the sensory-functional distinction between animals and non-living things but also revealed novel distinctions between different types of artefact. Hierarchical cluster analyses indicated that mechanical devices (e.g., vehicles) were distinct from other non-living objects because they had strong sound and motion characteristics, making them more similar to animals in this respect. Taken together, the ratings align with neuroscience evidence in suggesting that a number of distinct sensory processing channels make important contributions to object knowledge. Multi-modal ratings for 160 objects are provided as supplementary materials. Copyright © 2012 Elsevier Ltd. All rights reserved.

From supramolecular polymers to multi-component biomaterials.

PubMed

Goor, Olga J G M; Hendrikse, Simone I S; Dankers, Patricia Y W; Meijer, E W

2017-10-30

The most striking and general property of the biological fibrous architectures in the extracellular matrix (ECM) is the strong and directional interaction between biologically active protein subunits. These fibers display rich dynamic behavior without losing their architectural integrity. The complexity of the ECM taking care of many essential properties has inspired synthetic chemists to mimic these properties in artificial one-dimensional fibrous structures with the aim to arrive at multi-component biomaterials. Due to the dynamic character required for interaction with natural tissue, supramolecular biomaterials are promising candidates for regenerative medicine. Depending on the application area, and thereby the design criteria of these multi-component fibrous biomaterials, they are used as elastomeric materials or hydrogel systems. Elastomeric materials are designed to have load bearing properties whereas hydrogels are proposed to support in vitro cell culture. Although the chemical structures and systems designed and studied today are rather simple compared to the complexity of the ECM, the first examples of these functional supramolecular biomaterials reaching the clinic have been reported. The basic concept of many of these supramolecular biomaterials is based on their ability to adapt to cell behavior as a result of dynamic non-covalent interactions. In this review, we show the translation of one-dimensional supramolecular polymers into multi-component functional biomaterials for regenerative medicine applications.

Measuring sustainable development using a multi-criteria model: a case study.

PubMed

Boggia, Antonio; Cortina, Carla

2010-11-01

This paper shows how Multi-criteria Decision Analysis (MCDA) can help in a complex process such as the assessment of the level of sustainability of a certain area. The paper presents the results of a study in which a model for measuring sustainability was implemented to better aid public policy decisions regarding sustainability. In order to assess sustainability in specific areas, a methodological approach based on multi-criteria analysis has been developed. The aim is to rank areas in order to understand the specific technical and/or financial support that they need to develop sustainable growth. The case study presented is an assessment of the level of sustainability in different areas of an Italian Region using the MCDA approach. Our results show that MCDA is a proper approach for sustainability assessment. The results are easy to understand and the evaluation path is clear and transparent. This is what decision makers need for having support to their decisions. The multi-criteria model for evaluation has been developed respecting the sustainable development economic theory, so that final results can have a clear meaning in terms of sustainability. Copyright 2010 Elsevier Ltd. All rights reserved.

Time Line for Noncopers to Pass Return-to-Sports Criteria After Anterior Cruciate Ligament Reconstruction

PubMed Central

Hartigan, Erin H.; Axe, Michael J.; Snyder-Mackler, Lynn

2013-01-01

STUDY DESIGN Randomized clinical trial. OBJECTIVES Determine effective interventions for improving readiness to return to sports post-operatively in patients with complete, unilateral, anterior cruciate ligament (ACL) rupture who do not compensate well after the injury (noncopers). Specifically, we compared the effects of 2 preoperative interventions on quadriceps strength and functional outcomes. BACKGROUND The percentage of athletes who return to sports after ACL reconstruction varies considerably, possibly due to differential responses after acute ACL rupture and different management. Prognostic data for noncopers following ACL reconstruction is absent in the literature. METHODS Forty noncopers were randomly assigned to receive either progressive quadriceps strength-training exercises (STR group) or perturbation training in conjunction with strength-training exercises (PERT group) for 10 preoperative rehabilitation sessions. Postoperative rehabilitation was similar between groups. Data on quadriceps strength indices [(involved limb/uninvolved limb force) ×100], 4 hop score indices, and 2 self-report questionnaires were collected preoperatively and 3, 6, and 12 months postoperatively. Mann-Whitney U tests were used to compare functional differences between the groups. Chi-square tests were used to compare frequencies of passing functional criteria and reasons for differences in performance between groups postoperatively. RESULTS Functional outcomes were not different between groups, except a greater number of patients in the PERT group achieved global rating scores (current knee function expressed as a percentage of overall knee function prior to injury) necessary to pass return-to-sports criteria 6 and 12 months after surgery. Mean scores for each functional outcome met return-to-sports criteria 6 and 12 months postoperatively. Frequency counts of individual data, however, indicated that 5% of noncopers passed RTS criteria at 3, 48% at 6, and 78% at 12 months after surgery. CONCLUSION Functional outcomes suggest that a subgroup of noncopers require additional supervised rehabilitation to pass stringent criteria to return to sports. LEVEL OF EVIDENCE Therapy, level 2b. PMID:20195019

Disinfection efficacy of contact lens care solutions against ocular pathogens.

PubMed

Miller, M J; Callahan, D E; McGrath, D; Manchester, R; Norton, S E

2001-01-01

Three commercially available products labeled as multi-purpose contact lens solutions, one multi-purpose disinfecting solution, and a hydrogen peroxide system were evaluated for antimicrobial activity according to the current International Organization for Standardization (ISO) and the U.S. Food and Drug Administration (FDA) stand-alone procedure for disinfecting products. One multi-purpose solution was selected to assess its antimicrobial activity against two human corneal isolates of Pseudomonas aeruginosa. Products were challenged with bacteria and fungi, and following a specified period, aliquots of inoculated test solution were neutralized and plated on validated recovery media. After incubation the number of viable microorganisms was enumerated and mean log reductions determined. ReNu MultiPlus (Bausch & Lomb, Rochester, NY), AOSEPT (CIBA Vision Corporation, Duluth, GA), and Opti-Free Express with Aldox (Alcon Laboratories, Ft. Worth, TX) were the only lens care products that met the stand-alone criteria for all required microorganisms within their minimum recommended disinfection time. Of these, ReNu MultiPlus provided the greatest overall antimicrobial activity. ReNu MultiPlus demonstrated a significantly higher mean log reduction of Staphylococcus aureus and Serratia marcescens than Opti-Free Express. ReNu MultiPlus also gave a higher mean log reduction of S. aureus and S. marcescens than AOSEPT, and a higher mean log reduction of Candida albicans and Fusarium solani than AOSEPT, Complete Comfort Plus (Allergan, Irivine, CA), and Solo-Care (CIBA Vision Corp.) (at 4 hours). Both Complete Comfort Plus and Solo-Care (at 4 hours) met the primary acceptance criteria for bacteria; however, neither product possessed enough antimicrobial activity to meet the minimum criteria for yeast or mold. ReNu Multiplus was effective against corneal isolates of P. aeruginosa. ReNu MultiPlus, AOSEPT, and Opti-Free Express met the requirements of the stand-alone primary criteria for disinfecting solutions. ReNu MultiPlus demonstrated the greatest overall disinfection efficacy, as well as excellent activity against clinical strains of P. aeruginosa.

Particle Swarm Optimization Toolbox

NASA Technical Reports Server (NTRS)

Grant, Michael J.

2010-01-01

The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

A New Glaucoma Severity Score Combining Structural and Functional Defects.

PubMed

Wachtl, J; Töteberg-Harms, M; Frimmel, S; Kniestedt, C

2017-04-01

Background In order to assess glaucoma severity and to compare the success of surgical and medical therapy and study outcomes, an objective and independent staging tool is necessary. A combination of information from both structural and functional testing is probably the best approach to stage glaucomatous damage. There has been no universally accepted standard for glaucoma staging. The aim of this study was to develop a Glaucoma Severity Score (GSS) for objective assessment of a patient's glaucoma severity, combining both functional and structural information. Materials and methods The Glaucoma Severity Score includes the following 3 criteria: superior and inferior Retinal Nerve Fibre Layer (RNFL) thickness, perimetric mean defect (MD), and agreement of anatomical and perimetric defects, as assessed by two glaucoma specialists. The specialists defined a staging tool for each of the 3 criteria in a consensus process, assigning specific characteristics to a scale value between 0 and 2 or 0 and 3, respectively. The GSS ranges between 0 and 10 points. In a prospective observational study, the data of 112 glaucoma patients were assessed independently by the two specialists according to this staging tool. Results The GSS was applied to 112 eyes and patients (59.8 % female) with a mean age of 66.3 ± 13.1 years. Mean GSS was 4.73 points. Cohen's kappa coefficient was determined to measure inter-rater agreement between glaucoma specialists for the third criterion. With κ = 0.83, the agreement was very good. Thus, all 3 criteria of the GSS may be regarded as objective. Conclusions The Glaucoma Severity Score is an objective tool, combining both structural and functional characteristics, and permitting comparison of different patients, populations and studies. The Glaucoma Severity Score has proven effective in the objective assessment of 112 glaucoma patients and is relatively user-friendly in clinical practice. A comparative study of the GSS with the results of the FORUM® Glaucoma Workplace (Carl Zeiss Meditec AG, Jena, Germany) will be the next step. If outcomes match, the Glaucoma Severity Score can be accepted as a promising tool to stage glaucoma and monitor changes objectively in patients when comparing glaucoma progression in study analyses. Georg Thieme Verlag KG Stuttgart · New York.

Genetic algorithm-based multi-objective optimal absorber system for three-dimensional seismic structures

NASA Astrophysics Data System (ADS)

Ren, Wenjie; Li, Hongnan; Song, Gangbing; Huo, Linsheng

2009-03-01

The problem of optimizing an absorber system for three-dimensional seismic structures is addressed. The objective is to determine the number and position of absorbers to minimize the coupling effects of translation-torsion of structures at minimum cost. A procedure for a multi-objective optimization problem is developed by integrating a dominance-based selection operator and a dominance-based penalty function method. Based on the two-branch tournament genetic algorithm, the selection operator is constructed by evaluating individuals according to their dominance in one run. The technique guarantees the better performing individual winning its competition, provides a slight selection pressure toward individuals and maintains diversity in the population. Moreover, due to the evaluation for individuals in each generation being finished in one run, less computational effort is taken. Penalty function methods are generally used to transform a constrained optimization problem into an unconstrained one. The dominance-based penalty function contains necessary information on non-dominated character and infeasible position of an individual, essential for success in seeking a Pareto optimal set. The proposed approach is used to obtain a set of non-dominated designs for a six-storey three-dimensional building with shape memory alloy dampers subjected to earthquake.

Optimization of Land Use Suitability for Agriculture Using Integrated Geospatial Model and Genetic Algorithms

NASA Astrophysics Data System (ADS)

Mansor, S. B.; Pormanafi, S.; Mahmud, A. R. B.; Pirasteh, S.

2012-08-01

In this study, a geospatial model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the infrastructural preference. The model was developed based on multi-agent genetic algorithm. The model was customized to accommodate the constraint set for the study area, namely the resource saving and environmental-friendly. The model was then applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Menderjan Basin in Iran. The first task was to study the dominant crops and economic suitability evaluation of land. Second task was to determine the fitness function for the genetic algorithms. The third objective was to optimize the land use map using economical benefits. The results has indicated that the proposed model has much better performance for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.

Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data

NASA Technical Reports Server (NTRS)

Hill, Matthew L. (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Castelli, Vittorio (Inventor); Bergman, Lawrence David (Inventor)

2008-01-01

An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.

Methods and apparatus for extraction and tracking of objects from multi-dimensional sequence data

NASA Technical Reports Server (NTRS)

Hill, Matthew L. (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Castelli, Vittorio (Inventor); Bergman, Lawrence David (Inventor)

2005-01-01

An object tracking technique is provided which, given: (i) a potentially large data set; (ii) a set of dimensions along which the data has been ordered; and (iii) a set of functions for measuring the similarity between data elements, a set of objects are produced. Each of these objects is defined by a list of data elements. Each of the data elements on this list contains the probability that the data element is part of the object. The method produces these lists via an adaptive, knowledge-based search function which directs the search for high-probability data elements. This serves to reduce the number of data element combinations evaluated while preserving the most flexibility in defining the associations of data elements which comprise an object.

Release Report for Building Debris for TA-21 Sewage Treatment Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whicker, Jeffrey Jay; Gillis, Jessica; Ruedig, Elizabeth

2017-05-03

ENV-ES finds that the materials associated with TA-21 Buildings 227 (superstructure only), and 229 (see Figure 1) meet the criteria for unrestricted release to the public for recycle or as sanitary/commercial waste. The interior and exterior of the metal shed, building 387, passed the release criteria collectively; however, results from the roof of the structure were above reference background measurements. Waste management should be consulted for waste disposition options for the roofing metal. These findings are consistent with the requirements of DOE Order 458.1 “Radiation Protection of the Public and the Environment” and LANL Policy 412 “Environmental Radiation Protection.” Samplingmore » and data analysis, as described in this report, were sufficient to meet measurement objectives under the Multi-Agency Radiation Survey and Assessment of Materials and Equipment (MARSAME) manual (2009).« less

Development of ecological indicator guilds for land management

USGS Publications Warehouse

Krzysik, A.J.; Balbach, H.E.; Duda, J.J.; Emlen, J.M.; Freeman, D.C.; Graham, J.H.; Kovacic, D.A.; Smith, L.M.; Zak, J.C.

2005-01-01

Agency land-use must be efficiently and cost-effectively monitored to assess conditions and trends in ecosystem processes and natural resources relevant to mission requirements and legal mandates. Ecological Indicators represent important land management tools for tracking ecological changes and preventing irreversible environmental damage in disturbed landscapes. The overall objective of the research was to develop both individual and integrated sets (i.e., statistically derived guilds) of Ecological Indicators to: quantify habitat conditions and trends, track and monitor ecological changes, provide early warning or threshold detection, and provide guidance for land managers. The derivation of Ecological Indicators was based on statistical criteria, ecosystem relevance, reliability and robustness, economy and ease of use for land managers, multi-scale performance, and stress response criteria. The basis for the development of statistically based Ecological Indicators was the identification of ecosystem metrics that analytically tracked a landscape disturbance gradient.

Evaluation of a novel waste heat recovery system for the cement industry using multi-criteria analysis (MCA) approach

NASA Astrophysics Data System (ADS)

Han, Yue; Guo, Junshan; Zheng, Wei; Ding, Junqi; Zhu, Lingkai; Che, Yongqiang; Zhang, Yanpeng

2017-12-01

Based on a novel waste heat recovery project established in a cement plant, this paper aims to evaluate the performance of the project using multi-criteria analysis (MCA) approach. Economic, environmental, social, and technical perspectives were concerned and analyzed. Different sustainability criteria and indicators related with the project were evaluated through ranking/rating process and pairwise comparison. Results have shown similar outcomes, that ten out of eleven criteria are favorable at a high standard, which reveals the project’s success. Although the project has performed so well in economic, environmental and technical terms, social aspects have some weak points, and measures should be taken to improve social benefit.

Modeling, simulation and optimization approaches for design of lightweight car body structures

NASA Astrophysics Data System (ADS)

Kiani, Morteza

Simulation-based design optimization and finite element method are used in this research to investigate weight reduction of car body structures made of metallic and composite materials under different design criteria. Besides crashworthiness in full frontal, offset frontal, and side impact scenarios, vibration frequencies, static stiffness, and joint rigidity are also considered. Energy absorption at the component level is used to study the effectiveness of carbon fiber reinforced polymer (CFRP) composite material with consideration of different failure criteria. A global-local design strategy is introduced and applied to multi-objective optimization of car body structures with CFRP components. Multiple example problems involving the analysis of full-vehicle crash and body-in-white models are used to examine the effect of material substitution and the choice of design criteria on weight reduction. The results of this study show that car body structures that are optimized for crashworthiness alone may not meet the vibration criterion. Moreover, optimized car body structures with CFRP components can be lighter with superior crashworthiness than the baseline and optimized metallic structures.

The optimal algorithm for Multi-source RS image fusion.

PubMed

Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

2016-01-01

In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.

Proposed Diagnostic Criteria for Night Eating Syndrome

PubMed Central

Allison, Kelly C.; Lundgren, Jennifer D.; O’Reardon, John P.; Geliebter, Allan; Gluck, Marci E.; Vinai, Piergiuseppe; Mitchell, James E.; Schenck, Carlos H.; Howell, Michael J.; Crow, Scott J.; Engel, Scott; Latzer, Yael; Tzischinsky, Orna; Mahowald, Mark W.; Stunkard, Albert J.

2015-01-01

Objective To propose criteria for diagnosis of the night eating syndrome (NES). Method An international research meeting was held in April 2008, and consensus criteria for NES diagnosis were determined. Results The core criterion is an abnormally increased food intake in the evening and nighttime, manifested by (1) consumption of at least 25% of intake after the evening meal, and/or (2) nocturnal awakenings with ingestions at least twice per week. Awareness of the eating episodes is required, as is distress or impairment in functioning. Three of five modifiers must also be endorsed. These criteria must be met for a minimum duration of 3 months. Discussion These criteria help standardize the definition of NES. Additional aspects of the nosology of NES yet to be fully elaborated include its relationship to other eating and sleep disorders. Assessment and analytic tools are needed to assess these new criteria more accurately. PMID:19378289

An improved hybrid multi-criteria/multidimensional model for strategic industrial location selection: Casablanca industrial zones as a case study.

PubMed

Boutkhoum, Omar; Hanine, Mohamed; Agouti, Tarik; Tikniouine, Abdessadek

2015-01-01

In this paper, we examine the issue of strategic industrial location selection in uncertain decision making environments for implanting new industrial corporation. In fact, the industrial location issue is typically considered as a crucial factor in business research field which is related to many calculations about natural resources, distributors, suppliers, customers, and most other things. Based on the integration of environmental, economic and social decisive elements of sustainable development, this paper presents a hybrid decision making model combining fuzzy multi-criteria analysis with analytical capabilities that OLAP systems can provide for successful and optimal industrial location selection. The proposed model mainly consists in three stages. In the first stage, a decision-making committee has been established to identify the evaluation criteria impacting the location selection process. In the second stage, we develop fuzzy AHP software based on the extent analysis method to assign the importance weights to the selected criteria, which allows us to model the linguistic vagueness, ambiguity, and incomplete knowledge. In the last stage, OLAP analysis integrated with multi-criteria analysis employs these weighted criteria as inputs to evaluate, rank and select the strategic industrial location for implanting new business corporation in the region of Casablanca, Morocco. Finally, a sensitivity analysis is performed to evaluate the impact of criteria weights and the preferences given by decision makers on the final rankings of strategic industrial locations.

Decomposition-Based Decision Making for Aerospace Vehicle Design

NASA Technical Reports Server (NTRS)

Borer, Nicholas K.; Mavris, DImitri N.

2005-01-01

Most practical engineering systems design problems have multiple and conflicting objectives. Furthermore, the satisfactory attainment level for each objective ( requirement ) is likely uncertain early in the design process. Systems with long design cycle times will exhibit more of this uncertainty throughout the design process. This is further complicated if the system is expected to perform for a relatively long period of time, as now it will need to grow as new requirements are identified and new technologies are introduced. These points identify a need for a systems design technique that enables decision making amongst multiple objectives in the presence of uncertainty. Traditional design techniques deal with a single objective or a small number of objectives that are often aggregates of the overarching goals sought through the generation of a new system. Other requirements, although uncertain, are viewed as static constraints to this single or multiple objective optimization problem. With either of these formulations, enabling tradeoffs between the requirements, objectives, or combinations thereof is a slow, serial process that becomes increasingly complex as more criteria are added. This research proposal outlines a technique that attempts to address these and other idiosyncrasies associated with modern aerospace systems design. The proposed formulation first recasts systems design into a multiple criteria decision making problem. The now multiple objectives are decomposed to discover the critical characteristics of the objective space. Tradeoffs between the objectives are considered amongst these critical characteristics by comparison to a probabilistic ideal tradeoff solution. The proposed formulation represents a radical departure from traditional methods. A pitfall of this technique is in the validation of the solution: in a multi-objective sense, how can a decision maker justify a choice between non-dominated alternatives? A series of examples help the reader to observe how this technique can be applied to aerospace systems design and compare the results of this so-called Decomposition-Based Decision Making to more traditional design approaches.

Usability Guidelines for Product Recommenders Based on Example Critiquing Research

NASA Astrophysics Data System (ADS)

Pu, Pearl; Faltings, Boi; Chen, Li; Zhang, Jiyong; Viappiani, Paolo

Over the past decade, our group has developed a suite of decision tools based on example critiquing to help users find their preferred products in e-commerce environments. In this chapter, we survey important usability research work relative to example critiquing and summarize the major results by deriving a set of usability guidelines. Our survey is focused on three key interaction activities between the user and the system: the initial preference elicitation process, the preference revision process, and the presentation of the systems recommendation results. To provide a basis for the derivation of the guidelines, we developed a multi-objective framework of three interacting criteria: accuracy, confidence, and effort (ACE). We use this framework to analyze our past work and provide a specific context for each guideline: when the system should maximize its ability to increase users' decision accuracy, when to increase user confidence, and when to minimize the interaction effort for the users. Due to the general nature of this multi-criteria model, the set of guidelines that we propose can be used to ease the usability engineering process of other recommender systems, especially those used in e-commerce environments. The ACE framework presented here is also the first in the field to evaluate the performance of preference-based recommenders from a user-centric point of view.

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

PubMed

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Using multi-species occupancy models in structured decision making on managed lands

USGS Publications Warehouse

Sauer, John R.; Blank, Peter J.; Zipkin, Elise F.; Fallon, Jane E.; Fallon, Frederick W.

2013-01-01

Land managers must balance the needs of a variety of species when manipulating habitats. Structured decision making provides a systematic means of defining choices and choosing among alternative management options; implementation of a structured decision requires quantitative approaches to predicting consequences of management on the relevant species. Multi-species occupancy models provide a convenient framework for making structured decisions when the management objective is focused on a collection of species. These models use replicate survey data that are often collected on managed lands. Occupancy can be modeled for each species as a function of habitat and other environmental features, and Bayesian methods allow for estimation and prediction of collective responses of groups of species to alternative scenarios of habitat management. We provide an example of this approach using data from breeding bird surveys conducted in 2008 at the Patuxent Research Refuge in Laurel, Maryland, evaluating the effects of eliminating meadow and wetland habitats on scrub-successional and woodland-breeding bird species using summed total occupancy of species as an objective function. Removal of meadows and wetlands decreased value of an objective function based on scrub-successional species by 23.3% (95% CI: 20.3–26.5), but caused only a 2% (0.5, 3.5) increase in value of an objective function based on woodland species, documenting differential effects of elimination of meadows and wetlands on these groups of breeding birds. This approach provides a useful quantitative tool for managers interested in structured decision making.

Computer language for identifying chemicals with comprehensive two-dimensional gas chromatography and mass spectrometry.

PubMed

Reichenbach, Stephen E; Kottapalli, Visweswara; Ni, Mingtian; Visvanathan, Arvind

2005-04-15

This paper describes a language for expressing criteria for chemical identification with comprehensive two-dimensional gas chromatography paired with mass spectrometry (GC x GC-MS) and presents computer-based tools implementing the language. The Computer Language for Indentifying Chemicals (CLIC) allows expressions that describe rules (or constraints) for selecting chemical peaks or data points based on multi-dimensional chromatographic properties and mass spectral characteristics. CLIC offers chromatographic functions of retention times, functions of mass spectra, numbers for quantitative and relational evaluation, and logical and arithmetic operators. The language is demonstrated with the compound-class selection rules described by Welthagen et al. [W. Welthagen, J. Schnelle-Kreis, R. Zimmermann, J. Chromatogr. A 1019 (2003) 233-249]. A software implementation of CLIC provides a calculator-like graphical user-interface (GUI) for building and applying selection expressions. From the selection calculator, expressions can be used to select chromatographic peaks that meet the criteria or create selection chromatograms that mask data points inconsistent with the criteria. Selection expressions can be combined with graphical, geometric constraints in the retention-time plane as a powerful component for chemical identification with template matching or used to speed and improve mass spectrum library searches.

Multi-Stage Hybrid Rocket Conceptual Design for Micro-Satellites Launch using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Kitagawa, Yosuke; Kitagawa, Koki; Nakamiya, Masaki; Kanazaki, Masahiro; Shimada, Toru

The multi-objective genetic algorithm (MOGA) is applied to the multi-disciplinary conceptual design problem for a three-stage launch vehicle (LV) with a hybrid rocket engine (HRE). MOGA is an optimization tool used for multi-objective problems. The parallel coordinate plot (PCP), which is a data mining method, is employed in the post-process in MOGA for design knowledge discovery. A rocket that can deliver observing micro-satellites to the sun-synchronous orbit (SSO) is designed. It consists of an oxidizer tank containing liquid oxidizer, a combustion chamber containing solid fuel, a pressurizing tank and a nozzle. The objective functions considered in this study are to minimize the total mass of the rocket and to maximize the ratio of the payload mass to the total mass. To calculate the thrust and the engine size, the regression rate is estimated based on an empirical model for a paraffin (FT-0070) propellant. Several non-dominated solutions are obtained using MOGA, and design knowledge is discovered for the present hybrid rocket design problem using a PCP analysis. As a result, substantial knowledge on the design of an LV with an HRE is obtained for use in space transportation.

Strategic Environmental Assessment of Greenhouse Gas Mitigation Options in the Canadian Agricultural Sector

NASA Astrophysics Data System (ADS)

Noble, Bram F.; Christmas, Lisa M.

2008-01-01

This article presents a methodological framework for strategic environmental assessment (SEA) application. The overall objective is to demonstrate SEA as a systematic and structured policy, plan, and program (PPP) decision support tool. In order to accomplish this objective, a stakeholder-based SEA application to greenhouse gas (GHG) mitigation policy options in Canadian agriculture is presented. Using a mail-out impact assessment exercise, agricultural producers and nonproducers from across the Canadian prairie region were asked to evaluate five competing GHG mitigation options against 13 valued environmental components (VECs). Data were analyzed using multi-criteria and exploratory analytical techniques. The results suggest considerable variation in perceived impacts and GHG mitigation policy preferences, suggesting that a blanket policy approach to GHG mitigation will create gainers and losers based on soil type and associate cropping and on-farm management practices. It is possible to identify a series of regional greenhouse gas mitigation programs that are robust, socially meaningful, and operationally relevant to both agricultural producers and policy decision makers. The assessment demonstrates the ability of SEA to address, in an operational sense, environmental problems that are characterized by conflicting interests and competing objectives and alternatives. A structured and systematic SEA methodology provides the necessary decision support framework for the consideration of impacts, and allows for PPPs to be assessed based on a much broader set of properties, objectives, criteria, and constraints whereas maintaining rigor and accountability in the assessment process.

Reconstruction of the unknown optimization cost functions from experimental recordings during static multi-finger prehension

PubMed Central

Niu, Xun; Terekhov, Alexander V.; Latash, Mark L.; Zatsiorsky, Vladimir M.

2013-01-01

The goal of the research is to reconstruct the unknown cost (objective) function(s) presumably used by the neural controller for sharing the total force among individual fingers in multi-finger prehension. The cost function was determined from experimental data by applying the recently developed Analytical Inverse Optimization (ANIO) method (Terekhov et al 2010). The core of the ANIO method is the Theorem of Uniqueness that specifies conditions for unique (with some restrictions) estimation of the objective functions. In the experiment, subjects (n=8) grasped an instrumented handle and maintained it at rest in the air with various external torques, loads, and target grasping forces applied to the object. The experimental data recorded from 80 trials showed a tendency to lie on a 2-dimensional hyperplane in the 4-dimensional finger-force space. Because the constraints in each trial were different, such a propensity is a manifestation of a neural mechanism (not the task mechanics). In agreement with the Lagrange principle for the inverse optimization, the plane of experimental observations was close to the plane resulting from the direct optimization. The latter plane was determined using the ANIO method. The unknown cost function was reconstructed successfully for each performer, as well as for the group data. The cost functions were found to be quadratic with non-zero linear terms. The cost functions obtained with the ANIO method yielded more accurate results than other optimization methods. The ANIO method has an evident potential for addressing the problem of optimization in motor control. PMID:22104742

Probabilistic objective functions for sensor management

NASA Astrophysics Data System (ADS)

Mahler, Ronald P. S.; Zajic, Tim R.

2004-08-01

This paper continues the investigation of a foundational and yet potentially practical basis for control-theoretic sensor management, using a comprehensive, intuitive, system-level Bayesian paradigm based on finite-set statistics (FISST). In this paper we report our most recent progress, focusing on multistep look-ahead -- i.e., allocation of sensor resources throughout an entire future time-window. We determine future sensor states in the time-window using a "probabilistically natural" sensor management objective function, the posterior expected number of targets (PENT). This objective function is constructed using a new "maxi-PIMS" optimization strategy that hedges against unknowable future observation-collections. PENT is used in conjuction with approximate multitarget filters: the probability hypothesis density (PHD) filter or the multi-hypothesis correlator (MHC) filter.

The sampled-data consensus of multi-agent systems with probabilistic time-varying delays and packet losses

NASA Astrophysics Data System (ADS)

Sui, Xin; Yang, Yongqing; Xu, Xianyun; Zhang, Shuai; Zhang, Lingzhong

2018-02-01

This paper investigates the consensus of multi-agent systems with probabilistic time-varying delays and packet losses via sampled-data control. On the one hand, a Bernoulli-distributed white sequence is employed to model random packet losses among agents. On the other hand, a switched system is used to describe packet dropouts in a deterministic way. Based on the special property of the Laplacian matrix, the consensus problem can be converted into a stabilization problem of a switched system with lower dimensions. Some mean square consensus criteria are derived in terms of constructing an appropriate Lyapunov function and using linear matrix inequalities (LMIs). Finally, two numerical examples are given to show the effectiveness of the proposed method.

Multi-objective Optimization Strategies Using Adjoint Method and Game Theory in Aerodynamics

NASA Astrophysics Data System (ADS)

Tang, Zhili

2006-08-01

There are currently three different game strategies originated in economics: (1) Cooperative games (Pareto front), (2) Competitive games (Nash game) and (3) Hierarchical games (Stackelberg game). Each game achieves different equilibria with different performance, and their players play different roles in the games. Here, we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multi-criteria aerodynamic optimization problems. The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments. We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method. The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front. Non-dominated Pareto front solutions are obtained, however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.

Design Optimization of a Centrifugal Fan with Splitter Blades

NASA Astrophysics Data System (ADS)

Heo, Man-Woong; Kim, Jin-Hyuk; Kim, Kwang-Yong

2015-05-01

Multi-objective optimization of a centrifugal fan with additionally installed splitter blades was performed to simultaneously maximize the efficiency and pressure rise using three-dimensional Reynolds-averaged Navier-Stokes equations and hybrid multi-objective evolutionary algorithm. Two design variables defining the location of splitter, and the height ratio between inlet and outlet of impeller were selected for the optimization. In addition, the aerodynamic characteristics of the centrifugal fan were investigated with the variation of design variables in the design space. Latin hypercube sampling was used to select the training points, and response surface approximation models were constructed as surrogate models of the objective functions. With the optimization, both the efficiency and pressure rise of the centrifugal fan with splitter blades were improved considerably compared to the reference model.

Multivariate Cluster Analysis.

ERIC Educational Resources Information Center

McRae, Douglas J.

Procedures for grouping students into homogeneous subsets have long interested educational researchers. The research reported in this paper is an investigation of a set of objective grouping procedures based on multivariate analysis considerations. Four multivariate functions that might serve as criteria for adequate grouping are given and…

Transition Room Program, 1967 Report.

ERIC Educational Resources Information Center

Glassner, Leonard E.

The Transition Room Program of the Pittsburgh Schools was defined and evaluated by the staff, the administration, and a program evaluator from the Office of Research. The definition included general objectives, anticipated outcomes, student criteria and characteristics, staff qualifications and functions, media, student activities, and staff…

[Treatment of multi-segment fracture of complex femoral shaft with instrument-assisted reduction combined with intramedullary interlocking nail fixation].

PubMed

Fan, Ke-Jie; Chen, Ke; Ma, Wen-Long; Tian, Ke-Wei; Ye, Ye; Chen, Hong-Gan; Tang, Yan-Feng; Cai, Hong-Min

2018-05-25

To investigate the effect of minimally invasive mini-incision and instrumented reduction combined with interlocking intramedullary nailing in the treatment of patients with multi-segment fracture of complex femoral shaft. From January 2013 to January 2016, 32 patients with multiple fractures segments of femoral shaft were treated with instrumentation-assisted reduction combined with interlocking intramedullary nailing, including 22 males and 10 females with an average age of 45 years old ranging 17 to 68 years old. The time from injured to operation was 5 to 10 days with an average of 7 days. After admission, routine tibial tubercle or supracondylar bone traction was performed. The patient's general condition was evaluated, the operation time and intraoperative blood loss were recorded. According to Thorsen femoral fracture morphology evaluation criteria and Hohl knee function evaluation of postoperative efficacy, postoperative fracture healing, complications and postoperative recovery of limb function were observed. All patients were followed up for 6 to 24 months with an average of 12 months. The operative time ranged from 48 to 76 minutes with an average of 67 min. The intraoperative blood loss was 150 to 400 ml with an average of 220 ml. The surgical incisions all achieved grade A healing. The fractures reached the clinical standard of healing. The fracture healing time ranged from 4.2 to 10.8 months with an average of 5.7 months. There were no nonunion, incision infection and internal fixation fracture, failure and other complications. According to Thorsen femoral fracture morphology evaluation criteria, the result was excellent in 28 cases, good in 3 cases, fair in 1 case. According to Hohl knee function evaluation criteria, the result was excellent in 30 cases, good in 2 cases. Instrument-assisted reduction combined with interlocking intramedullary nail fixation is a safe and effective method for the treatment of complex femoral shaft fractures. It has advantages of small trauma, fixed fixation, quick recovery, early postoperative functional exercise. Copyright© 2018 by the China Journal of Orthopaedics and Traumatology Press.

Novel Mahalanobis-based feature selection improves one-class classification of early hepatocellular carcinoma.

PubMed

Thomaz, Ricardo de Lima; Carneiro, Pedro Cunha; Bonin, João Eliton; Macedo, Túlio Augusto Alves; Patrocinio, Ana Claudia; Soares, Alcimar Barbosa

2018-05-01

Detection of early hepatocellular carcinoma (HCC) is responsible for increasing survival rates in up to 40%. One-class classifiers can be used for modeling early HCC in multidetector computed tomography (MDCT), but demand the specific knowledge pertaining to the set of features that best describes the target class. Although the literature outlines several features for characterizing liver lesions, it is unclear which is most relevant for describing early HCC. In this paper, we introduce an unconstrained GA feature selection algorithm based on a multi-objective Mahalanobis fitness function to improve the classification performance for early HCC. We compared our approach to a constrained Mahalanobis function and two other unconstrained functions using Welch's t-test and Gaussian Data Descriptors. The performance of each fitness function was evaluated by cross-validating a one-class SVM. The results show that the proposed multi-objective Mahalanobis fitness function is capable of significantly reducing data dimensionality (96.4%) and improving one-class classification of early HCC (0.84 AUC). Furthermore, the results provide strong evidence that intensity features extracted at the arterial to portal and arterial to equilibrium phases are important for classifying early HCC.

Identification of vehicle suspension parameters by design optimization

NASA Astrophysics Data System (ADS)

Tey, J. Y.; Ramli, R.; Kheng, C. W.; Chong, S. Y.; Abidin, M. A. Z.

2014-05-01

The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.

System modeling with the DISC framework: evidence from safety-critical domains.

PubMed

Reiman, Teemu; Pietikäinen, Elina; Oedewald, Pia; Gotcheva, Nadezhda

2012-01-01

The objective of this paper is to illustrate the development and application of the Design for Integrated Safety Culture (DISC) framework for system modeling by evaluating organizational potential for safety in nuclear and healthcare domains. The DISC framework includes criteria for good safety culture and a description of functions that the organization needs to implement in order to orient the organization toward the criteria. Three case studies will be used to illustrate the utilization of the DISC framework in practice.

[Multi-criteria decision analysis for health technology resource allocation and assessment: so far and so near?

PubMed

Campolina, Alessandro Gonçalves; Soárez, Patrícia Coelho De; Amaral, Fábio Vieira do; Abe, Jair Minoro

2017-10-26

Multi-criteria decision analysis (MCDA) is an emerging tool that allows the integration of relevant factors for health technology assessment (HTA). This study aims to present a summary of the methodological characteristics of MCDA: definitions, approaches, applications, and implementation stages. A case study was conducted in the São Paulo State Cancer Institute (ICESP) in order to understand the perspectives of decision-makers in the process of drafting a recommendation for the incorporation of technology in the Brazilian Unified National Health System (SUS), through a report by the Brazilian National Commission for the Incorporation of Technologies in the SUS (CONITEC). Paraconsistent annotated evidential logic Eτ was the methodological approach adopted in the study, since it can serve as an underlying logic for constructs capable of synthesizing objective information (from the scientific literature) and subjective information (from experts' values and preferences in the area of knowledge). It also allows the incorporation of conflicting information (contradictions), as well as vague and even incomplete information in the valuation process, resulting from imperfection of the available scientific evidence. The method has the advantages of allowing explicit consideration of the criteria that influenced the decision, facilitating follow-up and visualization of process stages, allowing assessment of the contribution of each criterion separately, and in aggregate, to the decision's outcome, facilitating the discussion of diverging perspectives by different stakeholder groups, and increasing the understanding of the resulting recommendations. The use of an explicit MCDA approach should facilitate conflict mediation and optimize participation by different stakeholder groups.

Decoupling optical function and geometrical form using conformal flexible dielectric metasurfaces

DOE PAGES

Kamali, Seyedeh Mahsa; Arbabi, Amir; Arbabi, Ehsan; ...

2016-05-19

Physical geometry and optical properties of objects are correlated: cylinders focus light to a line, spheres to a point and arbitrarily shaped objects introduce optical aberrations. Multifunctional components with decoupled geometrical form and optical function are needed when specific optical functionalities must be provided while the shapes are dictated by other considerations like ergonomics, aerodynamics or aesthetics. Here we demonstrate an approach for decoupling optical properties of objects from their physical shape using thin and flexible dielectric metasurfaces which conform to objects' surface and change their optical properties. The conformal metasurfaces are composed of silicon nano-posts embedded in a polymermore » substrate that locally modify near-infrared (λ = 915 nm) optical wavefronts. As proof of concept, we show that cylindrical lenses covered with metasurfaces can be transformed to function as aspherical lenses focusing light to a point. Lastly, the conformal metasurface concept is highly versatile for developing arbitrarily shaped multi-functional optical devices.« less

The Role of Presented Objects in Deriving Color Preference Criteria from Psychophysical Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Royer, Michael P.; Wei, Minchen

Of the many “components” of a color rendering measure, one is perhaps the most important: the set of color samples (spectral reflectance functions) that are employed as a standardized means of evaluating and rating a light source. At the same time, a standardized set of color samples can never apply perfectly to a real space or a real set of observed objects, meaning there will always be some level of mismatch between the predicted and observed color shifts. This mismatch is important for lighting specifiers to consider, but even more critical for experiments that seek to evaluate the relationship betweenmore » color rendering measures and human perception. This article explores how the color distortions of three possible experimental object sets compare to the color distortions predicted using the color evaluation samples of IES TM-30-15 (TM-30). The experimental object sets include those from Royer and colleagues [2016], a set of produce (10 fruits and vegetables), and the X-rite Color Checker Classic. The differences are traced back to properties of the samples sets, such as the coverage of color space, average chroma level, and specific spectral features. The consequence of the differences, that the visual evaluation is based on color distortions that are substantially different from what is predicted, can lead to inaccurate criteria or models of a given perception, such as preference. To minimize the error in using criteria or models when specifying color rendering attributes for a given application, the criteria or models should be developed using a set of experimental objects that matches the typical objects of the application as closely as possible. Alternatively, if typical objects of an application cannot be reasonably determined, an object set that matches the distortions predicted by TM-30 as close as possible is likely to provide the most meaningful results.« less

Towards a New Definition of Return-to-Work Outcomes in Common Mental Disorders from a Multi-Stakeholder Perspective

PubMed Central

Hees, Hiske L.; Nieuwenhuijsen, Karen; Koeter, Maarten W. J.; Bültmann, Ute; Schene, Aart H.

2012-01-01

Objectives To examine the perspectives of key stakeholders involved in the return-to-work (RTW) process regarding the definition of successful RTW outcome after sickness absence related to common mental disorders (CMD’s). Methods A mixed-method design was used: First, we used qualitative methods (focus groups, interviews) to identify a broad range of criteria important for the definition of successful RTW (N = 57). Criteria were grouped into content-related clusters. Second, we used a quantitative approach (online questionnaire) to identify, among a larger stakeholder sample (N = 178), the clusters and criteria most important for successful RTW. Results A total of 11 clusters, consisting of 52 unique criteria, were identified. In defining successful RTW, supervisors and occupational physicians regarded “Sustainability” and “At-work functioning” most important, while employees regarded “Sustainability,” “Job satisfaction,” “Work-home balance,” and “Mental Functioning” most important. Despite agreement on the importance of certain criteria, considerable differences among stakeholders were observed. Conclusions Key stakeholders vary in the aspects and criteria they regard as important when defining successful RTW after CMD-related sickness absence. Current definitions of RTW outcomes used in scientific research may not accurately reflect these key stakeholder perspectives. Future studies should be more aware of the perspective from which they aim to evaluate the effectiveness of a RTW intervention, and define their RTW outcomes accordingly. PMID:22768180

Implementation of preference ranking organization method for enrichment evaluation (Promethee) on selection system of student’s achievement

NASA Astrophysics Data System (ADS)

Karlitasari, L.; Suhartini, D.; Nurrosikawati, L.

2018-03-01

Selection of Student Achievement is conducted every year, starting from the level of Study Program, Faculty, to University, which then rank one will be sent to Kopertis level. The criteria made for the selection are Academic and Rich Scientific, Organizational, Personality, and English. In order for the selection of Student Achievement is Objective, then in addition to the presence of the jury is expected to use methods that support the decision to be more optimal in determining the Student Achievement. One method used is the Promethee Method. Preference Ranking Organization Method for Enrichment Evaluation (Promethee) is a method of ranking in Multi Criteria Decision Making (MCDM). PROMETHEE has the advantage that there is a preference type against the criteria that can take into account alternatives with other alternatives on the same criteria. The conjecture of alternate dominance over a criterion used in PROMETHEE is the use of values in the relationships between alternative ranking values. Based on the calculation result, from 7 applicants between Manual and Promethee Matrices, rank 1, 2, and 3, did not change, only 4 to 7 positions were changed. However, after the sensitivity test, almost all criteria experience a high level of sensitivity. Although it does not affect the students who will be sent to the next level, but can bring psychological impact on prospective student’s achievement

Geoengineering as a design problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kravitz, Ben; MacMartin, Douglas G.; Wang, Hailong

2016-01-01

Understanding the climate impacts of solar geoengineering is essential for evaluating its benefits and risks. Most previous simulations have prescribed a particular strategy and evaluated its modeled effects. Here we turn this approach around by first choosing example climate objectives and then designing a strategy to meet those objectives in climate models. There are four essential criteria for designing a strategy: (i) an explicit specification of the objectives, (ii) defining what climate forcing agents to modify so the objectives are met, (iii) a method for managing uncertainties, and (iv) independent verification of the strategy in an evaluation model. We demonstrate this design perspective throughmore » two multi-objective examples. First, changes in Arctic temperature and the position of tropical precipitation due to CO 2 increases are offset by adjusting high-latitude insolation in each hemisphere independently. Second, three different latitude-dependent patterns of insolation are modified to offset CO 2-induced changes in global mean temperature, interhemispheric temperature asymmetry, and the Equator-to-pole temperature gradient. In both examples, the "design" and "evaluation" models are state-of-the-art fully coupled atmosphere–ocean general circulation models.« less

Sustainability assessment of alternative end-uses for disused areas based on multi-criteria decision-making method.

PubMed

De Feo, Giovanni; De Gisi, Sabino; De Vita, Sabato; Notarnicola, Michele

2018-08-01

The main aim of this study was to define and apply a multidisciplinary and multi-criteria approach to sustainability in evaluating alternative end-uses for disused areas. Taking into account the three pillars of sustainability (social, economic and environmental dimension) as well as the need for stakeholders to have new practical instruments, the innovative approach consists of four modules stated (i) sociological, (ii) economic, (iii) environmental and (iv) multi-criteria assessment. By means of a case study on a small Municipality in Southern Italy, three end-uses alternatives, representing three essential services for citizens, were selected: Municipal gym; Market area; Municipal Solid Waste (MSW) separate collection centre. The sociological module was useful to select the most socially sound alternative by means of a consultative referendum, simulated with the use of a structured questionnaire administered to a sample of the population. The economic evaluation was conducted defining the bill of quantities with regarding to six main items (soil handling, landfill disposal tax, public services, structure and services, completion work, equipment and furnishings). The environmental evaluation was performed applying the Delphi method with local technicians who were involved in a qualitative-quantitative evaluation of the three alternatives with regarding to eight possible environmental impacts (landscape impact, soil handling, odour, traffic, noise, atmospheric pollution, wastewater, waste). Finally, the Simple Additive Weighting was used as multi-criteria technique to define alternatives priorities. The obtained results showed how the multi-criteria analysis is a useful decision support tool able to identify transparently and efficiently the most sustainable solutions to a complex social problem. Copyright © 2018 Elsevier B.V. All rights reserved.

WE-AB-209-12: Quasi Constrained Multi-Criteria Optimization for Automated Radiation Therapy Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watkins, W.T.; Siebers, J.V.

Purpose: To introduce quasi-constrained Multi-Criteria Optimization (qcMCO) for unsupervised radiation therapy optimization which generates alternative patient-specific plans emphasizing dosimetric tradeoffs and conformance to clinical constraints for multiple delivery techniques. Methods: For N Organs At Risk (OARs) and M delivery techniques, qcMCO generates M(N+1) alternative treatment plans per patient. Objective weight variations for OARs and targets are used to generate alternative qcMCO plans. For 30 locally advanced lung cancer patients, qcMCO plans were generated for dosimetric tradeoffs to four OARs: each lung, heart, and esophagus (N=4) and 4 delivery techniques (simple 4-field arrangements, 9-field coplanar IMRT, 27-field non-coplanar IMRT, and non-coplanarmore » Arc IMRT). Quasi-constrained objectives included target prescription isodose to 95% (PTV-D95), maximum PTV dose (PTV-Dmax)< 110% of prescription, and spinal cord Dmax<45 Gy. The algorithm’s ability to meet these constraints while simultaneously revealing dosimetric tradeoffs was investigated. Statistically significant dosimetric tradeoffs were defined such that the coefficient of determination between dosimetric indices which varied by at least 5 Gy between different plans was >0.8. Results: The qcMCO plans varied mean dose by >5 Gy to ipsilateral lung for 24/30 patients, contralateral lung for 29/30 patients, esophagus for 29/30 patients, and heart for 19/30 patients. In the 600 plans computed without human interaction, average PTV-D95=67.4±3.3 Gy, PTV-Dmax=79.2±5.3 Gy, and spinal cord Dmax was >45 Gy in 93 plans (>50 Gy in 2/600 plans). Statistically significant dosimetric tradeoffs were evident in 19/30 plans, including multiple tradeoffs of at least 5 Gy between multiple OARs in 7/30 cases. The most common statistically significant tradeoff was increasing PTV-Dmax to reduce OAR dose (15/30 patients). Conclusion: The qcMCO method can conform to quasi-constrained objectives while revealing significant variations in OAR doses including mean dose reductions >5 Gy. Clinical implementation will facilitate patient-specific decision making based on achievable dosimetry as opposed to accept/reject models based on population derived objectives.« less

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

NASA Astrophysics Data System (ADS)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.

Parana Basin Structure from Multi-Objective Inversion of Surface Wave and Receiver Function by Competent Genetic Algorithm

NASA Astrophysics Data System (ADS)

An, M.; Assumpcao, M.

2003-12-01

The joint inversion of receiver function and surface wave is an effective way to diminish the influences of the strong tradeoff among parameters and the different sensitivity to the model parameters in their respective inversions, but the inversion problem becomes more complex. Multi-objective problems can be much more complicated than single-objective inversion in the model selection and optimization. If objectives are involved and conflicting, models can be ordered only partially. In this case, Pareto-optimal preference should be used to select solutions. On the other hand, the inversion to get only a few optimal solutions can not deal properly with the strong tradeoff between parameters, the uncertainties in the observation, the geophysical complexities and even the incompetency of the inversion technique. The effective way is to retrieve the geophysical information statistically from many acceptable solutions, which requires more competent global algorithms. Competent genetic algorithms recently proposed are far superior to the conventional genetic algorithm and can solve hard problems quickly, reliably and accurately. In this work we used one of competent genetic algorithms, Bayesian Optimization Algorithm as the main inverse procedure. This algorithm uses Bayesian networks to draw out inherited information and can use Pareto-optimal preference in the inversion. With this algorithm, the lithospheric structure of Paran"› basin is inverted to fit both the observations of inter-station surface wave dispersion and receiver function.

Evidence-based Assessment of Cognitive Functioning in Pediatric Psychology

PubMed Central

Brown, Ronald T.; Cavanagh, Sarah E.; Vess, Sarah F.; Segall, Mathew J.

2008-01-01

Objective To review the evidence base for measures of cognitive functioning frequently used within the field of pediatric psychology. Methods From a list of 47 measures identified by the Society of Pediatric Psychology (Division 54) Evidence-Based Assessment Task Force Workgroup, 27 measures were included in the review. Measures were organized, reviewed, and evaluated according to general domains of functioning (e.g., attention/executive functioning, memory). Results Twenty-two of 27 measures reviewed demonstrated psychometric properties that met “Well-established” criteria as set forth by the Assessment Task Force. Psychometric properties were strongest for measures of general cognitive ability and weakest for measures of visual-motor functioning and attention. Conclusions We report use of “Well-established” measures of overall cognitive functioning, nonverbal intelligence, academic achievement, language, and memory and learning. For several specific tests in the domains of visual-motor functioning and attention, additional psychometric data are needed for measures to meet criteria as “Well established.” PMID:18194973

Revised Criteria for Mild Cognitive Impairment May Compromise the Diagnosis of Alzheimer Disease Dementia

PubMed Central

Morris, John C.

2012-01-01

Objective To evaluate the potential impact of revised criteria for mild cognitive impairment (MCI), developed by a Workgroup sponsored by the National Institute on Aging and the Alzheimer’s Association, on the diagnosis of very mild and mild Alzheimer disease (AD) dementia. Design Retrospective review of ratings of functional impairment across diagnostic categories. Participants: The functional ratings of individuals (N = 17,535) with normal cognition, MCI, or AD dementia who were evaluated at Alzheimer’s Disease Centers and submitted to the National Alzheimer’s Coordinating Center were assessed in accordance with the definition of “functional independence” allowed by the revised criteria. Methods Pairwise demographic differences between the 3 diagnostic groups were tested using t-tests for continuous variables and chi-square for categorical variables. Results Almost all (99.8%) of individuals currently diagnosed with very mild AD dementia and the large majority (92.7%) of those diagnosed with mild AD dementia could be reclassified as MCI with the revised criteria, based on their level of impairment in the Clinical Dementia Rating domains for performance of instrumental activities of daily living in the community and at home. Large percentages of these AD dementia individuals also meet the revised “functional independence” criterion for MCI as measured by the Functional Assessment Questionnaire. Conclusions The categorical distinction between MCI and milder stages of Alzheimer dementia has been compromised by the revised criteria. The resulting diagnostic overlap supports the premise that “MCI due to AD” represents the earliest symptomatic stage of AD. PMID:22312163