A framework for multi-stakeholder decision-making and conflict resolution

EPA Science Inventory

We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimiz...

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 game-theory models for conflict analysis in reservoir watershed management.

PubMed

Lee, Chih-Sheng

2012-05-01

This study focuses on the development of a multi-objective game-theory model (MOGM) for balancing economic and environmental concerns in reservoir watershed management and for assistance in decision. Game theory is used as an alternative tool for analyzing strategic interaction between economic development (land use and development) and environmental protection (water-quality protection and eutrophication control). Geographic information system is used to concisely illustrate and calculate the areas of various land use types. The MOGM methodology is illustrated in a case study of multi-objective watershed management in the Tseng-Wen reservoir, Taiwan. The innovation and advantages of MOGM can be seen in the results, which balance economic and environmental concerns in watershed management and which can be interpreted easily by decision makers. For comparison, the decision-making process using conventional multi-objective method to produce many alternatives was found to be more difficult. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Method for Decision Making using Sustainability Indicators

EPA Science Inventory

Calculations aimed at representing the thought process of decision makers are common within multi-objective decision support tools. These calculations that mathematically describe preferences most often combine various utility scores (i.e., abilities to satisfy desires) with weig...

Multi-objective optimization of solid waste flows: environmentally sustainable strategies for municipalities.

PubMed

Minciardi, Riccardo; Paolucci, Massimo; Robba, Michela; Sacile, Roberto

2008-11-01

An approach to sustainable municipal solid waste (MSW) management is presented, with the aim of supporting the decision on the optimal flows of solid waste sent to landfill, recycling and different types of treatment plants, whose sizes are also decision variables. This problem is modeled with a non-linear, multi-objective formulation. Specifically, four objectives to be minimized have been taken into account, which are related to economic costs, unrecycled waste, sanitary landfill disposal and environmental impact (incinerator emissions). An interactive reference point procedure has been developed to support decision making; these methods are considered appropriate for multi-objective decision problems in environmental applications. In addition, interactive methods are generally preferred by decision makers as they can be directly involved in the various steps of the decision process. Some results deriving from the application of the proposed procedure are presented. The application of the procedure is exemplified by considering the interaction with two different decision makers who are assumed to be in charge of planning the MSW system in the municipality of Genova (Italy).

Application of GIS in foreign direct investment decision support system

NASA Astrophysics Data System (ADS)

Zhou, Jianlan; Sun, Koumei

2007-06-01

It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.

Smart Grid as Multi-layer Interacting System for Complex Decision Makings

NASA Astrophysics Data System (ADS)

Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico

This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.

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.

Risk Decision Making Model for Reservoir Floodwater resources Utilization

NASA Astrophysics Data System (ADS)

Huang, X.

2017-12-01

Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

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.

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.

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.

Multi-disciplinary decision making in general practice.

PubMed

Kirby, Ann; Murphy, Aileen; Bradley, Colin

2018-04-09

Purpose Internationally, healthcare systems are moving towards delivering care in an integrated manner which advocates a multi-disciplinary approach to decision making. Such an approach is formally encouraged in the management of Atrial Fibrillation patients through the European Society of Cardiology guidelines. Since the emergence of new oral anticoagulants switching between oral anticoagulants (OACs) has become prevalent. This case study considers the role of multi-disciplinary decision making, given the complex nature of the agents. The purpose of this paper is to explore Irish General Practitioners' (GPs) experience of switching between all OACs for Arial Fibrillation (AF) patients; prevalence of multi-disciplinary decision making in OAC switching decisions and seeks to determine the GP characteristics that appear to influence the likelihood of multi-disciplinary decision making. Design/methodology/approach A probit model is used to determine the factors influencing multi-disciplinary decision making and a multinomial logit is used to examine the factors influencing who is involved in the multi-disciplinary decisions. Findings Results reveal that while some multi-disciplinary decision-making is occurring (64 per cent), it is not standard practice despite international guidelines on integrated care. Moreover, there is a lack of patient participation in the decision-making process. Female GPs and GPs who have initiated prescriptions for OACs are more likely to engage in multi-disciplinary decision-making surrounding switching OACs amongst AF patients. GPs with training practices were less likely to engage with cardiac consultants and those in urban areas were more likely to engage with other (non-cardiac) consultants. Originality/value For optimal decision making under uncertainty multi-disciplinary decision-making is needed to make a more informed judgement and to improve treatment decisions and reduce the opportunity cost of making the wrong decision.

Informed multi-objective decision-making in environmental management using Pareto optimality

Treesearch

Maureen C. Kennedy; E. David Ford; Peter Singleton; Mark Finney; James K. Agee

2008-01-01

Effective decisionmaking in environmental management requires the consideration of multiple objectives that may conflict. Common optimization methods use weights on the multiple objectives to aggregate them into a single value, neglecting valuable insight into the relationships among the objectives in the management problem.

A SYSTEMATIC PROCEDURE FOR DESIGNING PROCESSES WITH MULTIPLE ENVIRONMENTAL OBJECTIVES

EPA Science Inventory

Evaluation and analysis of multiple objectives are very important in designing environmentally benign processes. They require a systematic procedure for solving multi-objective decision-making problems due to the complex nature of the problems and the need for complex assessment....

A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making.

PubMed

van der Lee, J H; Svrcek, W Y; Young, B R

2008-01-01

Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.

A probabilistic multi-criteria decision making technique for conceptual and preliminary aerospace systems design

NASA Astrophysics Data System (ADS)

Bandte, Oliver

It has always been the intention of systems engineering to invent or produce the best product possible. Many design techniques have been introduced over the course of decades that try to fulfill this intention. Unfortunately, no technique has succeeded in combining multi-criteria decision making with probabilistic design. The design technique developed in this thesis, the Joint Probabilistic Decision Making (JPDM) technique, successfully overcomes this deficiency by generating a multivariate probability distribution that serves in conjunction with a criterion value range of interest as a universally applicable objective function for multi-criteria optimization and product selection. This new objective function constitutes a meaningful Xnetric, called Probability of Success (POS), that allows the customer or designer to make a decision based on the chance of satisfying the customer's goals. In order to incorporate a joint probabilistic formulation into the systems design process, two algorithms are created that allow for an easy implementation into a numerical design framework: the (multivariate) Empirical Distribution Function and the Joint Probability Model. The Empirical Distribution Function estimates the probability that an event occurred by counting how many times it occurred in a given sample. The Joint Probability Model on the other hand is an analytical parametric model for the multivariate joint probability. It is comprised of the product of the univariate criterion distributions, generated by the traditional probabilistic design process, multiplied with a correlation function that is based on available correlation information between pairs of random variables. JPDM is an excellent tool for multi-objective optimization and product selection, because of its ability to transform disparate objectives into a single figure of merit, the likelihood of successfully meeting all goals or POS. The advantage of JPDM over other multi-criteria decision making techniques is that POS constitutes a single optimizable function or metric that enables a comparison of all alternative solutions on an equal basis. Hence, POS allows for the use of any standard single-objective optimization technique available and simplifies a complex multi-criteria selection problem into a simple ordering problem, where the solution with the highest POS is best. By distinguishing between controllable and uncontrollable variables in the design process, JPDM can account for the uncertain values of the uncontrollable variables that are inherent to the design problem, while facilitating an easy adjustment of the controllable ones to achieve the highest possible POS. Finally, JPDM's superiority over current multi-criteria decision making techniques is demonstrated with an optimization of a supersonic transport concept and ten contrived equations as well as a product selection example, determining an airline's best choice among Boeing's B-747, B-777, Airbus' A340, and a Supersonic Transport. The optimization examples demonstrate JPDM's ability to produce a better solution with a higher POS than an Overall Evaluation Criterion or Goal Programming approach. Similarly, the product selection example demonstrates JPDM's ability to produce a better solution with a higher POS and different ranking than the Overall Evaluation Criterion or Technique for Order Preferences by Similarity to the Ideal Solution (TOPSIS) approach.

A framework for multi-stakeholder decision-making and ...

EPA Pesticide Factsheets

We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimization problem. The CVaR problem is parameterized by a probability level that shapes the tail of the dissatisfaction distribution. The proposed approach allows us to compute a family of compromise solutions and generalizes multi-stakeholder settings previously proposed in the literature that minimize average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem +and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework that involve complex decision-making processes. We demonstrate the developments using a biowaste facility location case study in which we seek to balance stakeholder priorities on transportation, safety, water quality, and capital costs. This manuscript describes the methodology of a new decision-making framework that computes compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives as needed for SHC Decision Science and Support Tools project. A biowaste facility location is employed as the case study

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.

Placement Decisions and Disparities among Aboriginal Groups: An Application of the Decision Making Ecology through Multi-Level Analysis

ERIC Educational Resources Information Center

Fluke, John D.; Chabot, Martin; Fallon, Barbara; MacLaurin, Bruce; Blackstock, Cindy

2010-01-01

Objective: This paper examined the relative influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. It tested the hypothesis that extraneous factors, specifically, organizational characteristics, impact the decision to place a child in…

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.

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.

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.

Energy Decision Science and Informatics | Integrated Energy Solutions |

Science.gov Websites

Science Advanced decision science methods include multi-objective and multi-criteria decision support. Our decision science methods, including multi-objective and multi-criteria decision support. For example, we

Using the Analytic Hierarchy Process for Decision-Making in Ecosystem Management

Treesearch

Daniel L. Schmoldt; David L. Peterson

1997-01-01

Land management activities on public lands combine multiple objectives in order to create a plan of action over a finite time horizon. Because management activities are constrained by time and money, it is critical to make the best use of available agency resources. The Analytic Hierarchy Process (AHP) offers a structure for multi-objective decisionmaking so that...

Risk-based analysis and decision making in multi-disciplinary environments

NASA Technical Reports Server (NTRS)

Feather, Martin S.; Cornford, Steven L.; Moran, Kelly

2003-01-01

A risk-based decision-making process conceived of and developed at JPL and NASA, has been used to help plan and guide novel technology applications for use on spacecraft. These applications exemplify key challenges inherent in multi-disciplinary design of novel technologies deployed in mission-critical settings. 1) Cross-disciplinary concerns are numerous (e.g., spacecraft involve navigation, propulsion, telecommunications). These concems are cross-coupled and interact in multiple ways (e.g., electromagnetic interference, heat transfer). 2) Time and budget pressures constrain development, operational resources constrain the resulting system (e.g., mass, volume, power). 3) Spacecraft are critical systems that must operate correctly the first time in only partially understood environments, with no chance for repair. 4) Past experience provides only a partial guide: New mission concepts are enhanced and enabled by new technologies, for which past experience is lacking. The decision-making process rests on quantitative assessments of the relationships between three classes of information - objectives (the things the system is to accomplish and constraints on its operation and development), risks (whose occurrence detracts from objectives), and mitigations (options for reducing the likelihood and or severity of risks). The process successfully guides experts to pool their knowledge, using custom-built software to support information gathering and decision-making.

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 multi-criteria decision making approach to identify a vaccine formulation.

PubMed

Dewé, Walthère; Durand, Christelle; Marion, Sandie; Oostvogels, Lidia; Devaster, Jeanne-Marie; Fourneau, Marc

2016-01-01

This article illustrates the use of a multi-criteria decision making approach, based on desirability functions, to identify an appropriate adjuvant composition for an influenza vaccine to be used in elderly. The proposed adjuvant system contained two main elements: monophosphoryl lipid and α-tocopherol with squalene in an oil/water emulsion. The objective was to elicit a stronger immune response while maintaining an acceptable reactogenicity and safety profile. The study design, the statistical models, the choice of the desirability functions, the computation of the overall desirability index, and the assessment of the robustness of the ranking are all detailed in this manuscript.

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-view Decision Making (MVDM) Workshop

DTIC Science & Technology

2009-02-01

reflect the realities of system-of-systems development, acquisition, fielding and support: multi-view decision making (MVDM). MVDM addresses the...including mission risk, interoperable acquisition, and operational security and survivability. Hence, a multi-view approach to decision making is

Compromise Programming in forest management

Treesearch

Boris A. Poff; Aregai Tecle; Daniel G. Neary; Brian Geils

2010-01-01

Multi-objective decision-making (MODM) is an appropriate approach for evaluating a forest management scenario involving multiple interests. Today's land managers must accommodate commercial as well as non-commercial objectives that may be expressed quantitatively and/or qualitatively, and respond to social, political, economic and cultural changes. The spatial and...

Research on AHP decision algorithms based on BP algorithm

NASA Astrophysics Data System (ADS)

Ma, Ning; Guan, Jianhe

2017-10-01

Decision making is the thinking activity that people choose or judge, and scientific decision-making has always been a hot issue in the field of research. Analytic Hierarchy Process (AHP) is a simple and practical multi-criteria and multi-objective decision-making method that combines quantitative and qualitative and can show and calculate the subjective judgment in digital form. In the process of decision analysis using AHP method, the rationality of the two-dimensional judgment matrix has a great influence on the decision result. However, in dealing with the real problem, the judgment matrix produced by the two-dimensional comparison is often inconsistent, that is, it does not meet the consistency requirements. BP neural network algorithm is an adaptive nonlinear dynamic system. It has powerful collective computing ability and learning ability. It can perfect the data by constantly modifying the weights and thresholds of the network to achieve the goal of minimizing the mean square error. In this paper, the BP algorithm is used to deal with the consistency of the two-dimensional judgment matrix of the AHP.

Shared decision-making – transferring research into practice: the Analytic Hierarchy Process (AHP)

PubMed Central

Dolan, James G.

2008-01-01

Objective To illustrate how the Analytic Hierarchy Process (AHP) can be used to promote shared decision-making and enhance clinician-patient communication. Methods Tutorial review. Results The AHP promotes shared decision making by creating a framework that is used to define the decision, summarize the information available, prioritize information needs, elicit preferences and values, and foster meaningful communication among decision stakeholders. Conclusions The AHP and related multi-criteria methods have the potential for improving the quality of clinical decisions and overcoming current barriers to implementing shared decision making in busy clinical settings. Further research is needed to determine the best way to implement these tools and to determine their effectiveness. Practice Implications Many clinical decisions involve preference-based trade-offs between competing risks and benefits. The AHP is a well-developed method that provides a practical approach for improving patient-provider communication, clinical decision-making, and the quality of patient care in these situations. PMID:18760559

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.

Multi-Objective Bidding Strategy for Genco Using Non-Dominated Sorting Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Saksinchai, Apinat; Boonchuay, Chanwit; Ongsakul, Weerakorn

2010-06-01

This paper proposes a multi-objective bidding strategy for a generation company (GenCo) in uniform price spot market using non-dominated sorting particle swarm optimization (NSPSO). Instead of using a tradeoff technique, NSPSO is introduced to solve the multi-objective strategic bidding problem considering expected profit maximization and risk (profit variation) minimization. Monte Carlo simulation is employed to simulate rivals' bidding behavior. Test results indicate that the proposed approach can provide the efficient non-dominated solution front effectively. In addition, it can be used as a decision making tool for a GenCo compromising between expected profit and price risk in spot market.

Pareto frontier analyses based decision making tool for transportation of hazardous waste.

PubMed

Das, Arup; Mazumder, T N; Gupta, A K

2012-08-15

Transportation of hazardous wastes through a region poses immense threat on the development along its road network. The risk to the population, exposed to such activities, has been documented in the past. However, a comprehensive framework for routing hazardous wastes has often been overlooked. A regional Hazardous Waste Management scheme should incorporate a comprehensive framework for hazardous waste transportation. This framework would incorporate the various stakeholders involved in decision making. Hence, a multi-objective approach is required to safeguard the interest of all the concerned stakeholders. The objective of this study is to design a methodology for routing of hazardous wastes between the generating units and the disposal facilities through a capacity constrained network. The proposed methodology uses posteriori method with multi-objective approach to find non-dominated solutions for the system consisting of multiple origins and destinations. A case study of transportation of hazardous wastes in Kolkata Metropolitan Area has also been provided to elucidate the methodology. Copyright © 2012 Elsevier B.V. All rights reserved.

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

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.

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

PubMed

Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

2014-03-01

This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case-based reasoning) obtaining with ENORA a classification rate of 0.9298, specificity of 0.9385, and sensitivity of 0.9364, with 14.2 interpretable fuzzy rules on average. Our proposal improves the accuracy and interpretability of the classifiers, compared with other non-evolutionary techniques. We also conclude that ENORA outperforms niched pre-selection and NSGA-II algorithms. Moreover, given that our multi-objective evolutionary methodology is non-combinational based on real parameter optimization, the time cost is significantly reduced compared with other evolutionary approaches existing in literature based on combinational optimization. Copyright © 2014 Elsevier B.V. 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…

Shared decision-making at the end of life: A focus group study exploring the perceptions and experiences of multi-disciplinary healthcare professionals working in the home setting.

PubMed

Brogan, Paula; Hasson, Felicity; McIlfatrick, Sonja

2018-01-01

Globally recommended in healthcare policy, Shared Decision-Making is also central to international policy promoting community palliative care. Yet realities of implementation by multi-disciplinary healthcare professionals who provide end-of-life care in the home are unclear. To explore multi-disciplinary healthcare professionals' perceptions and experiences of Shared Decision-Making at end of life in the home. Qualitative design using focus groups, transcribed verbatim and analysed thematically. A total of 43 participants, from multi-disciplinary community-based services in one region of the United Kingdom, were recruited. While the rhetoric of Shared Decision-Making was recognised, its implementation was impacted by several interconnecting factors, including (1) conceptual confusion regarding Shared Decision-Making, (2) uncertainty in the process and (3) organisational factors which impeded Shared Decision-Making. Multiple interacting factors influence implementation of Shared Decision-Making by professionals working in complex community settings at the end of life. Moving from rhetoric to reality requires future work exploring the realities of Shared Decision-Making practice at individual, process and systems levels.

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.

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.

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...

Efficient decision-making by volume-conserving physical object

NASA Astrophysics Data System (ADS)

Kim, Song-Ju; Aono, Masashi; Nameda, Etsushi

2015-08-01

Decision-making is one of the most important intellectual abilities of not only humans but also other biological organisms, helping their survival. This ability, however, may not be limited to biological systems and may be exhibited by physical systems. Here we demonstrate that any physical object, as long as its volume is conserved when coupled with suitable operations, provides a sophisticated decision-making capability. We consider the multi-armed bandit problem (MBP), the problem of finding, as accurately and quickly as possible, the most profitable option from a set of options that gives stochastic rewards. Efficient MBP solvers are useful for many practical applications, because MBP abstracts a variety of decision-making problems in real-world situations in which an efficient trial-and-error is required. These decisions are made as dictated by a physical object, which is moved in a manner similar to the fluctuations of a rigid body in a tug-of-war (TOW) game. This method, called ‘TOW dynamics’, exhibits higher efficiency than conventional reinforcement learning algorithms. We show analytical calculations that validate statistical reasons for TOW dynamics to produce the high performance despite its simplicity. These results imply that various physical systems in which some conservation law holds can be used to implement an efficient ‘decision-making object’. The proposed scheme will provide a new perspective to open up a physics-based analog computing paradigm and to understanding the biological information-processing principles that exploit their underlying physics.

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.

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-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

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method

NASA Astrophysics Data System (ADS)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.

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.

Incentives for Optimal Multi-level Allocation of HIV Prevention Resources

PubMed Central

Malvankar, Monali M.; Zaric, Gregory S.

2013-01-01

HIV/AIDS prevention funds are often allocated at multiple levels of decision-making. Optimal allocation of HIV prevention funds maximizes the number of HIV infections averted. However, decision makers often allocate using simple heuristics such as proportional allocation. We evaluate the impact of using incentives to encourage optimal allocation in a two-level decision-making process. We model an incentive based decision-making process consisting of an upper-level decision maker allocating funds to a single lower-level decision maker who then distributes funds to local programs. We assume that the lower-level utility function is linear in the amount of the budget received from the upper-level, the fraction of funds reserved for proportional allocation, and the number of infections averted. We assume that the upper level objective is to maximize the number of infections averted. We illustrate with an example using data from California, U.S. PMID:23766551

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.

An interval-parameter mixed integer multi-objective programming for environment-oriented evacuation management

NASA Astrophysics Data System (ADS)

Wu, C. Z.; Huang, G. H.; Yan, X. P.; Cai, Y. P.; Li, Y. P.

2010-05-01

Large crowds are increasingly common at political, social, economic, cultural and sports events in urban areas. This has led to attention on the management of evacuations under such situations. In this study, we optimise an approximation method for vehicle allocation and route planning in case of an evacuation. This method, based on an interval-parameter multi-objective optimisation model, has potential for use in a flexible decision support system for evacuation management. The modeling solutions are obtained by sequentially solving two sub-models corresponding to lower- and upper-bounds for the desired objective function value. The interval solutions are feasible and stable in the given decision space, and this may reduce the negative effects of uncertainty, thereby improving decision makers' estimates under different conditions. The resulting model can be used for a systematic analysis of the complex relationships among evacuation time, cost and environmental considerations. The results of a case study used to validate the proposed model show that the model does generate useful solutions for planning evacuation management and practices. Furthermore, these results are useful for evacuation planners, not only in making vehicle allocation decisions but also for providing insight into the tradeoffs among evacuation time, environmental considerations and economic objectives.

A multi-objective decision-making approach to the journal submission problem.

PubMed

Wong, Tony E; Srikrishnan, Vivek; Hadka, David; Keller, Klaus

2017-01-01

When researchers complete a manuscript, they need to choose a journal to which they will submit the study. This decision requires to navigate trade-offs between multiple objectives. One objective is to share the new knowledge as widely as possible. Citation counts can serve as a proxy to quantify this objective. A second objective is to minimize the time commitment put into sharing the research, which may be estimated by the total time from initial submission to final decision. A third objective is to minimize the number of rejections and resubmissions. Thus, researchers often consider the trade-offs between the objectives of (i) maximizing citations, (ii) minimizing time-to-decision, and (iii) minimizing the number of resubmissions. To complicate matters further, this is a decision with multiple, potentially conflicting, decision-maker rationalities. Co-authors might have different preferences, for example about publishing fast versus maximizing citations. These diverging preferences can lead to conflicting trade-offs between objectives. Here, we apply a multi-objective decision analytical framework to identify the Pareto-front between these objectives and determine the set of journal submission pathways that balance these objectives for three stages of a researcher's career. We find multiple strategies that researchers might pursue, depending on how they value minimizing risk and effort relative to maximizing citations. The sequences that maximize expected citations within each strategy are generally similar, regardless of time horizon. We find that the "conditional impact factor"-impact factor times acceptance rate-is a suitable heuristic method for ranking journals, to strike a balance between minimizing effort objectives and maximizing citation count. Finally, we examine potential co-author tension resulting from differing rationalities by mapping out each researcher's preferred Pareto front and identifying compromise submission strategies. The explicit representation of trade-offs, especially when multiple decision-makers (co-authors) have different preferences, facilitates negotiations and can support the decision process.

A multi-objective decision-making approach to the journal submission problem

PubMed Central

Hadka, David; Keller, Klaus

2017-01-01

When researchers complete a manuscript, they need to choose a journal to which they will submit the study. This decision requires to navigate trade-offs between multiple objectives. One objective is to share the new knowledge as widely as possible. Citation counts can serve as a proxy to quantify this objective. A second objective is to minimize the time commitment put into sharing the research, which may be estimated by the total time from initial submission to final decision. A third objective is to minimize the number of rejections and resubmissions. Thus, researchers often consider the trade-offs between the objectives of (i) maximizing citations, (ii) minimizing time-to-decision, and (iii) minimizing the number of resubmissions. To complicate matters further, this is a decision with multiple, potentially conflicting, decision-maker rationalities. Co-authors might have different preferences, for example about publishing fast versus maximizing citations. These diverging preferences can lead to conflicting trade-offs between objectives. Here, we apply a multi-objective decision analytical framework to identify the Pareto-front between these objectives and determine the set of journal submission pathways that balance these objectives for three stages of a researcher’s career. We find multiple strategies that researchers might pursue, depending on how they value minimizing risk and effort relative to maximizing citations. The sequences that maximize expected citations within each strategy are generally similar, regardless of time horizon. We find that the “conditional impact factor”—impact factor times acceptance rate—is a suitable heuristic method for ranking journals, to strike a balance between minimizing effort objectives and maximizing citation count. Finally, we examine potential co-author tension resulting from differing rationalities by mapping out each researcher’s preferred Pareto front and identifying compromise submission strategies. The explicit representation of trade-offs, especially when multiple decision-makers (co-authors) have different preferences, facilitates negotiations and can support the decision process. PMID:28582430

A queueing model of pilot decision making in a multi-task flight management situation

NASA Technical Reports Server (NTRS)

Walden, R. S.; Rouse, W. B.

1977-01-01

Allocation of decision making responsibility between pilot and computer is considered and a flight management task, designed for the study of pilot-computer interaction, is discussed. A queueing theory model of pilot decision making in this multi-task, control and monitoring situation is presented. An experimental investigation of pilot decision making and the resulting model parameters are discussed.

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.

Creating Multi Objective Value Functions from Non-Independent Values

DTIC Science & Technology

2009-03-01

1998) or oil companies trying to capitalize on the increasing flood of available data and statistics ( Coopersmith , Dean, McVean, & Storaune, 2001...Clemen, R. T., & Reilly, T. (2001). Making Hard Decisions. Pacific Grove: Duxbury. Coopersmith , E., Dean, G., McVean, J., & Storaune, E. (2001

Accounting for reasonableness: Exploring the personal internal framework affecting decisions about cancer drug funding.

PubMed

Sinclair, Shane; Hagen, Neil A; Chambers, Carole; Manns, Braden; Simon, Anita; Browman, George P

2008-05-01

Drug decision-makers are involved in developing and implementing policy, procedure and processes to support health resource allocation regarding drug treatment formularies. A variety of approaches to decision-making, including formal decision-making frameworks, have been developed to support transparent and fair priority setting. Recently, a decision tool, 'The 6-STEPPPs Tool', was developed to assist in making decisions about new cancer drugs within the public health care system. We conducted a qualitative study, utilizing focus groups and participant observation, in order to investigate the internal frameworks that supported and challenged individual participants as they applied this decision tool within a multi-stakeholder decision process. We discovered that health care resource allocation engaged not only the minds of decision-makers but profoundly called on the often conflicting values of the heart. Objective decision-making frameworks for new drug therapies need to consider the subjective internal frameworks of decision-makers that affect decisions. Understanding the very human, internal turmoil experienced by individuals involved in health care resource allocation, sheds additional insight into how to account for reasonableness and how to better support difficult decisions through transparent, values-based resource allocation policy, procedures and processes.

Eating and drinking interventions for people at risk of lacking decision-making capacity: who decides and how?

PubMed

Clarke, Gemma; Galbraith, Sarah; Woodward, Jeremy; Holland, Anthony; Barclay, Stephen

2015-06-11

Some people with progressive neurological diseases find they need additional support with eating and drinking at mealtimes, and may require artificial nutrition and hydration. Decisions concerning artificial nutrition and hydration at the end of life are ethically complex, particularly if the individual lacks decision-making capacity. Decisions may concern issues of life and death: weighing the potential for increasing morbidity and prolonging suffering, with potentially shortening life. When individuals lack decision-making capacity, the standard processes of obtaining informed consent for medical interventions are disrupted. Increasingly multi-professional groups are being utilised to make difficult ethical decisions within healthcare. This paper reports upon a service evaluation which examined decision-making within a UK hospital Feeding Issues Multi-Professional Team. A three month observation of a hospital-based multi-professional team concerning feeding issues, and a one year examination of their records. The key research questions are: a) How are decisions made concerning artificial nutrition for individuals at risk of lacking decision-making capacity? b) What are the key decision-making factors that are balanced? c) Who is involved in the decision-making process? Decision-making was not a singular decision, but rather involved many different steps. Discussions involving relatives and other clinicians, often took place outside of meetings. Topics of discussion varied but the outcome relied upon balancing the information along four interdependent axes: (1) Risks, burdens and benefits; (2) Treatment goals; (3) Normative ethical values; (4) Interested parties. Decision-making was a dynamic ongoing process with many people involved. The multiple points of decision-making, and the number of people involved with the decision-making process, mean the question of 'who decides' cannot be fully answered. There is a potential for anonymity of multiple decision-makers to arise. Decisions in real world clinical practice may not fit precisely into a model of decision-making. The findings from this service evaluation illustrate that within multi-professional team decision-making; decisions may contain elements of both substituted and supported decision-making, and may be better represented as existing upon a continuum.

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.

A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

NASA Astrophysics Data System (ADS)

Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

Many-objective robust decision making for water allocation under climate change.

PubMed

Yan, Dan; Ludwig, Fulco; Huang, He Qing; Werners, Saskia E

2017-12-31

Water allocation is facing profound challenges due to climate change uncertainties. To identify adaptive water allocation strategies that are robust to climate change uncertainties, a model framework combining many-objective robust decision making and biophysical modeling is developed for large rivers. The framework was applied to the Pearl River basin (PRB), China where sufficient flow to the delta is required to reduce saltwater intrusion in the dry season. Before identifying and assessing robust water allocation plans for the future, the performance of ten state-of-the-art MOEAs (multi-objective evolutionary algorithms) is evaluated for the water allocation problem in the PRB. The Borg multi-objective evolutionary algorithm (Borg MOEA), which is a self-adaptive optimization algorithm, has the best performance during the historical periods. Therefore it is selected to generate new water allocation plans for the future (2079-2099). This study shows that robust decision making using carefully selected MOEAs can help limit saltwater intrusion in the Pearl River Delta. However, the framework could perform poorly due to larger than expected climate change impacts on water availability. Results also show that subjective design choices from the researchers and/or water managers could potentially affect the ability of the model framework, and cause the most robust water allocation plans to fail under future climate change. Developing robust allocation plans in a river basin suffering from increasing water shortage requires the researchers and water managers to well characterize future climate change of the study regions and vulnerabilities of their tools. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Releases of whooping cranes to the Florida nonmigratory flock: a structured decision-making approach: report to the International Whooping Crane Recovery Team, September 22, 2008

USGS Publications Warehouse

Moore, Clinton T.; Converse, Sarah J.; Folk, Martin J.; Boughton, Robin; Brooks, Bill; French, John B.; O'Meara, Timothy; Putnam, Michael; Rodgers, James; Spalding, Marilyn

2008-01-01

We used a structured decision-making approach to inform the decision of whether the Florida Fish and Wildlife Conservation Commission should request of the International Whooping Crane Recovery Team that additional whooping crane chicks be released into the Florida Non-Migratory Population (FNMP). Structured decision-making is an application of decision science that strives to produce transparent, replicable, and defensible decisions that recognize the appropriate roles of management policy and science in decision-making. We present a multi-objective decision framework, where management objectives include successful establishment of a whooping crane population in Florida, minimization of costs, positive public relations, information gain, and providing a supply of captive-reared birds to alternative crane release projects, such as the Eastern Migratory Population. We developed models to predict the outcome relative to each of these objectives under 29 different scenarios of the release methodology used from 1993 to 2004, including options of no further releases and variable numbers of releases per year over the next 5-30 years. In particular, we developed a detailed set of population projection models, which make substantially different predictions about the probability of successful establishment of the FNMP. We used expert elicitation to develop prior model weights (measures of confidence in population model predictions); the results of the population model weighting and modelaveraging exercise indicated that the probability of successful establishment of the FNMP ranged from 9% if no additional releases are made, to as high as 41% with additional releases. We also used expert elicitation to develop weights (relative values) on the set of identified objectives, and we then used a formal optimization technique for identifying the optimal decision, which considers the tradeoffs between objectives. The optimal decision was identified as release of 3 cohorts (24 birds) per year over the next 10 years. However, any decision that involved release of 1-3 cohorts (8-24 birds) per year over the next 5 to 20 years, as well as decisions that involve skipping releases in every other year, performed better in our analysis than the alternative of no further releases. These results were driven by the relatively high objective weights that experts placed on the population objective (i.e., successful establishment of the FNMP) and the information gain objective (where releases are expected to accelerate learning on what was identified as a primary uncertainty: the demographic performance of wild-hatched birds). Additional considerations that were not formally integrated into the analysis are also discussed.

A decision aid for intensity-modulated radiation-therapy plan selection in prostate cancer based on a prognostic Bayesian network and a Markov model.

PubMed

Smith, Wade P; Doctor, Jason; Meyer, Jürgen; Kalet, Ira J; Phillips, Mark H

2009-06-01

The prognosis of cancer patients treated with intensity-modulated radiation-therapy (IMRT) is inherently uncertain, depends on many decision variables, and requires that a physician balance competing objectives: maximum tumor control with minimal treatment complications. In order to better deal with the complex and multiple objective nature of the problem we have combined a prognostic probabilistic model with multi-attribute decision theory which incorporates patient preferences for outcomes. The response to IMRT for prostate cancer was modeled. A Bayesian network was used for prognosis for each treatment plan. Prognoses included predicting local tumor control, regional spread, distant metastases, and normal tissue complications resulting from treatment. A Markov model was constructed and used to calculate a quality-adjusted life-expectancy which aids in the multi-attribute decision process. Our method makes explicit the tradeoffs patients face between quality and quantity of life. This approach has advantages over current approaches because with our approach risks of health outcomes and patient preferences determine treatment decisions.

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.

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.

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method.

PubMed

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection.

PubMed

Lin, Hui; Wang, Zhou-Jing

2017-09-17

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice.

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection

PubMed Central

Lin, Hui; Wang, Zhou-Jing

2017-01-01

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice. PMID:28926985

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.

Adaptive Allocation of Decision Making Responsibility Between Human and Computer in Multi-Task Situations. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chu, Y. Y.

1978-01-01

A unified formulation of computer-aided, multi-task, decision making is presented. Strategy for the allocation of decision making responsibility between human and computer is developed. The plans of a flight management systems are studied. A model based on the queueing theory was implemented.

Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay

USGS Publications Warehouse

McGowan, Conor P.; Smith, David R.; Nichols, James D.; Lyons, James E.; Sweka, John A.; Kalasz, Kevin; Niles, Lawrence J.; Wong, Richard; Brust, Jeffrey; Davis, Michelle C.; Spear, Braddock

2015-01-01

Decision analytic approaches have been widely recommended as well suited to solving disputed and ecologically complex natural resource management problems with multiple objectives and high uncertainty. However, the difference between theory and practice is substantial, as there are very few actual resource management programs that represent formal applications of decision analysis. We applied the process of structured decision making to Atlantic horseshoe crab harvest decisions in the Delaware Bay region to develop a multispecies adaptive management (AM) plan, which is currently being implemented. Horseshoe crab harvest has been a controversial management issue since the late 1990s. A largely unregulated horseshoe crab harvest caused a decline in crab spawning abundance. That decline coincided with a major decline in migratory shorebird populations that consume horseshoe crab eggs on the sandy beaches of Delaware Bay during spring migration. Our approach incorporated multiple stakeholders, including fishery and shorebird conservation advocates, to account for diverse management objectives and varied opinions on ecosystem function. Through consensus building, we devised an objective statement and quantitative objective function to evaluate alternative crab harvest policies. We developed a set of competing ecological models accounting for the leading hypotheses on the interaction between shorebirds and horseshoe crabs. The models were initially weighted based on stakeholder confidence in these hypotheses, but weights will be adjusted based on monitoring and Bayesian model weight updating. These models were used together to predict the effects of management actions on the crab and shorebird populations. Finally, we used a dynamic optimization routine to identify the state dependent optimal harvest policy for horseshoe crabs, given the possible actions, the stated objectives and our competing hypotheses about system function. The AM plan was reviewed, accepted and implemented by the Atlantic States Marine Fisheries Commission in 2012 and 2013. While disagreements among stakeholders persist, structured decision making enabled unprecedented progress towards a transparent and consensus driven management plan for crabs and shorebirds in Delaware Bay.

Understanding user needs for carbon monitoring information

NASA Astrophysics Data System (ADS)

Duren, R. M.; Macauley, M.; Gurney, K. R.; Saatchi, S. S.; Woodall, C. W.; Larsen, K.; Reidmiller, D.; Hockstad, L.; Weitz, M.; Croes, B.; Down, A.; West, T.; Mercury, M.

2015-12-01

The objectives of the Understanding User Needs project for NASA's Carbon Monitoring System (CMS) program are to: 1) engage the user community and identify needs for policy-relevant carbon monitoring information, 2) evaluate current and planned CMS data products with regard to their value for decision making, and 3) explore alternative methods for visualizing and communicating carbon monitoring information and associated uncertainties to decision makers and other stakeholders. To meet these objectives and help establish a sustained link between science and decision-making we have established a multi-disciplinary team that combines expertise in carbon-cycle science, engineering, economics, and carbon management and policy. We will present preliminary findings regarding emerging themes and needs for carbon information that may warrant increased attention by the science community. We will also demonstrate a new web-based tool that offers a common framework for facilitating user evaluation of carbon data products from multiple CMS projects.

A Multi-Objective Decision-Making Model for Resources Allocation in Humanitarian Relief

DTIC Science & Technology

2007-03-01

Applied Mathematics and Computation 163, 2005, pp756 19. Malczewski, J., GIS and Multicriteria Decision Analysis , John Wiley and Sons, New York... used when interpreting the results of the analysis . (Raimo et al. 2002) (7) Sensitivity analysis Sensitivity analysis in a DA process answers...Budget Scenario Analysis The MILP is solved ( using LINDO 6.1) for high, medium and low budget scenarios in both damage degree levels. Tables 17 and

Integrated Risk-Informed Decision-Making for an ALMR PRISM

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

Muhlheim, Michael David; Belles, Randy; Denning, Richard S.

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace ormore » supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.« less

A matter of tradeoffs: reintroduction as a multiple objective decision

USGS Publications Warehouse

Converse, Sarah J.; Moore, Clinton T.; Folk, Martin J.; Runge, Michael C.

2013-01-01

Decision making in guidance of reintroduction efforts is made challenging by the substantial scientific uncertainty typically involved. However, a less recognized challenge is that the management objectives are often numerous and complex. Decision makers managing reintroduction efforts are often concerned with more than just how to maximize the probability of reintroduction success from a population perspective. Decision makers are also weighing other concerns such as budget limitations, public support and/or opposition, impacts on the ecosystem, and the need to consider not just a single reintroduction effort, but conservation of the entire species. Multiple objective decision analysis is a powerful tool for formal analysis of such complex decisions. We demonstrate the use of multiple objective decision analysis in the case of the Florida non-migratory whooping crane reintroduction effort. In this case, the State of Florida was considering whether to resume releases of captive-reared crane chicks into the non-migratory whooping crane population in that state. Management objectives under consideration included maximizing the probability of successful population establishment, minimizing costs, maximizing public relations benefits, maximizing the number of birds available for alternative reintroduction efforts, and maximizing learning about the demographic patterns of reintroduced whooping cranes. The State of Florida engaged in a collaborative process with their management partners, first, to evaluate and characterize important uncertainties about system behavior, and next, to formally evaluate the tradeoffs between objectives using the Simple Multi-Attribute Rating Technique (SMART). The recommendation resulting from this process, to continue releases of cranes at a moderate intensity, was adopted by the State of Florida in late 2008. Although continued releases did not receive support from the International Whooping Crane Recovery Team, this approach does provide a template for the formal, transparent consideration of multiple, potentially competing, objectives in reintroduction decision making.

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.

System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Goienetxea Uriarte, A.; Ruiz Zúñiga, E.; Urenda Moris, M.; Ng, A. H. C.

2015-05-01

Discrete Event Simulation (DES) is nowadays widely used to support decision makers in system analysis and improvement. However, the use of simulation for improving stochastic logistic processes is not common among healthcare providers. The process of improving healthcare systems involves the necessity to deal with trade-off optimal solutions that take into consideration a multiple number of variables and objectives. Complementing DES with Multi-Objective Optimization (SMO) creates a superior base for finding these solutions and in consequence, facilitates the decision-making process. This paper presents how SMO has been applied for system improvement analysis in a Swedish Emergency Department (ED). A significant number of input variables, constraints and objectives were considered when defining the optimization problem. As a result of the project, the decision makers were provided with a range of optimal solutions which reduces considerably the length of stay and waiting times for the ED patients. SMO has proved to be an appropriate technique to support healthcare system design and improvement processes. A key factor for the success of this project has been the involvement and engagement of the stakeholders during the whole process.

Stochastic multi-objective auto-optimization for resource allocation decision-making in fixed-input health systems.

PubMed

Bastian, Nathaniel D; Ekin, Tahir; Kang, Hyojung; Griffin, Paul M; Fulton, Lawrence V; Grannan, Benjamin C

2017-06-01

The management of hospitals within fixed-input health systems such as the U.S. Military Health System (MHS) can be challenging due to the large number of hospitals, as well as the uncertainty in input resources and achievable outputs. This paper introduces a stochastic multi-objective auto-optimization model (SMAOM) for resource allocation decision-making in fixed-input health systems. The model can automatically identify where to re-allocate system input resources at the hospital level in order to optimize overall system performance, while considering uncertainty in the model parameters. The model is applied to 128 hospitals in the three services (Air Force, Army, and Navy) in the MHS using hospital-level data from 2009 - 2013. The results are compared to the traditional input-oriented variable returns-to-scale Data Envelopment Analysis (DEA) model. The application of SMAOM to the MHS increases the expected system-wide technical efficiency by 18 % over the DEA model while also accounting for uncertainty of health system inputs and outputs. The developed method is useful for decision-makers in the Defense Health Agency (DHA), who have a strategic level objective of integrating clinical and business processes through better sharing of resources across the MHS and through system-wide standardization across the services. It is also less sensitive to data outliers or sampling errors than traditional DEA methods.

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.

Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

PubMed

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.

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.

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

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

Cetiner, Sacit M; Kisner, Roger A; Muhlheim, Michael David

2015-07-01

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or nomore » human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.« less

Application of TOPSIS and VIKOR improved versions in a multi criteria decision analysis to develop an optimized municipal solid waste management model.

PubMed

Aghajani Mir, M; Taherei Ghazvinei, P; Sulaiman, N M N; Basri, N E A; Saheri, S; Mahmood, N Z; Jahan, A; Begum, R A; Aghamohammadi, N

2016-01-15

Selecting a suitable Multi Criteria Decision Making (MCDM) method is a crucial stage to establish a Solid Waste Management (SWM) system. Main objective of the current study is to demonstrate and evaluate a proposed method using Multiple Criteria Decision Making methods (MCDM). An improved version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied to obtain the best municipal solid waste management method by comparing and ranking the scenarios. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Besides, Viekriterijumsko Kompromisno Rangiranje (VIKOR) compromise solution method applied for sensitivity analyses. The proposed method can assist urban decision makers in prioritizing and selecting an optimized Municipal Solid Waste (MSW) treatment system. Besides, a logical and systematic scientific method was proposed to guide an appropriate decision-making. A modified TOPSIS methodology as a superior to existing methods for first time was applied for MSW problems. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Next, 11 scenarios of MSW treatment methods are defined and compared environmentally and economically based on the waste management conditions. Results show that integrating a sanitary landfill (18.1%), RDF (3.1%), composting (2%), anaerobic digestion (40.4%), and recycling (36.4%) was an optimized model of integrated waste management. An applied decision-making structure provides the opportunity for optimum decision-making. Therefore, the mix of recycling and anaerobic digestion and a sanitary landfill with Electricity Production (EP) are the preferred options for MSW management. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-Sector Sustainability Browser (MSSB) User Manual: A ...

EPA Pesticide Factsheets

EPA’s Sustainable and Healthy Communities (SHC) Research Program is developing methodologies, resources, and tools to assist community members and local decision makers in implementing policy choices that facilitate sustainable approaches in managing their resources affecting the built environment, natural environment, and human health. In order to assist communities and decision makers in implementing sustainable practices, EPA is developing computer-based systems including models, databases, web tools, and web browsers to help communities decide upon approaches that support their desired outcomes. Communities need access to resources that will allow them to achieve their sustainability objectives through intelligent decisions in four key sustainability areas: • Land Use • Buildings and Infrastructure • Transportation • Materials Management (i.e., Municipal Solid Waste [MSW] processing and disposal) The Multi-Sector Sustainability Browser (MSSB) is designed to support sustainable decision-making for communities, local and regional planners, and policy and decision makers. Document is an EPA Technical Report, which is the user manual for the Multi-Sector Sustainability Browser (MSSB) tool. The purpose of the document is to provide basic guidance on use of the tool for users

A decision model for cost effective design of biomass based green energy supply chains.

PubMed

Yılmaz Balaman, Şebnem; Selim, Hasan

2015-09-01

The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-Objective Reinforcement Learning for Cognitive Radio-Based Satellite Communications

NASA Technical Reports Server (NTRS)

Ferreira, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

2016-01-01

Previous research on cognitive radios has addressed the performance of various machine-learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different cross-layer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3.5 times for clear sky conditions and 6.8 times for rain conditions.

Multi-Objective Reinforcement Learning for Cognitive Radio Based Satellite Communications

NASA Technical Reports Server (NTRS)

Ferreira, Paulo; Paffenroth, Randy; Wyglinski, Alexander; Hackett, Timothy; Bilen, Sven; Reinhart, Richard; Mortensen, Dale John

2016-01-01

Previous research on cognitive radios has addressed the performance of various machine learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different crosslayer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3:5 times for clear sky conditions and 6:8 times for rain conditions.

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).

Equipment Selection by using Fuzzy TOPSIS Method

NASA Astrophysics Data System (ADS)

Yavuz, Mahmut

2016-10-01

In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide.

PubMed

Diaby, Vakaramoko; Goeree, Ron

2014-02-01

In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

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.

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.

What Is Robustness?: Problem Framing Challenges for Water Systems Planning Under Change

NASA Astrophysics Data System (ADS)

Herman, J. D.; Reed, P. M.; Zeff, H. B.; Characklis, G. W.

2014-12-01

Water systems planners have long recognized the need for robust solutions capable of withstanding deviations from the conditions for which they were designed. Faced with a set of alternatives to choose from—for example, resulting from a multi-objective optimization—existing analysis frameworks offer competing definitions of robustness under change. Robustness analyses have moved from expected utility to exploratory "bottom-up" approaches in which vulnerable scenarios are identified prior to assigning likelihoods; examples include Robust Decision Making (RDM), Decision Scaling, Info-Gap, and Many-Objective Robust Decision Making (MORDM). We propose a taxonomy of robustness frameworks to compare and contrast these approaches, based on their methods of (1) alternative selection, (2) sampling of states of the world, (3) quantification of robustness measures, and (4) identification of key uncertainties using sensitivity analysis. Using model simulations from recent work in multi-objective urban water supply portfolio planning, we illustrate the decision-relevant consequences that emerge from each of these choices. Results indicate that the methodological choices in the taxonomy lead to substantially different planning alternatives, underscoring the importance of an informed definition of robustness. We conclude with a set of recommendations for problem framing: that alternatives should be searched rather than prespecified; dominant uncertainties should be discovered rather than assumed; and that a multivariate satisficing measure of robustness allows stakeholders to achieve their problem-specific performance requirements. This work highlights the importance of careful problem formulation, and provides a common vocabulary to link the robustness frameworks widely used in the field of water systems planning.

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.

A multi-objective optimization model for hub network design under uncertainty: An inexact rough-interval fuzzy approach

NASA Astrophysics Data System (ADS)

Niakan, F.; Vahdani, B.; Mohammadi, M.

2015-12-01

This article proposes a multi-objective mixed-integer model to optimize the location of hubs within a hub network design problem under uncertainty. The considered objectives include minimizing the maximum accumulated travel time, minimizing the total costs including transportation, fuel consumption and greenhouse emissions costs, and finally maximizing the minimum service reliability. In the proposed model, it is assumed that for connecting two nodes, there are several types of arc in which their capacity, transportation mode, travel time, and transportation and construction costs are different. Moreover, in this model, determining the capacity of the hubs is part of the decision-making procedure and balancing requirements are imposed on the network. To solve the model, a hybrid solution approach is utilized based on inexact programming, interval-valued fuzzy programming and rough interval programming. Furthermore, a hybrid multi-objective metaheuristic algorithm, namely multi-objective invasive weed optimization (MOIWO), is developed for the given problem. Finally, various computational experiments are carried out to assess the proposed model and solution approaches.

Building a maintenance policy through a multi-criterion decision-making model

NASA Astrophysics Data System (ADS)

Faghihinia, Elahe; Mollaverdi, Naser

2012-08-01

A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.

Improving Multi-Objective Management of Water Quality Tipping Points: Revisiting the Classical Shallow Lake Problem

NASA Astrophysics Data System (ADS)

Quinn, J. D.; Reed, P. M.; Keller, K.

2015-12-01

Recent multi-objective extensions of the classical shallow lake problem are useful for exploring the conceptual and computational challenges that emerge when managing irreversible water quality tipping points. Building on this work, we explore a four objective version of the lake problem where a hypothetical town derives economic benefits from polluting a nearby lake, but at the risk of irreversibly tipping the lake into a permanently polluted state. The trophic state of the lake exhibits non-linear threshold dynamics; below some critical phosphorus (P) threshold it is healthy and oligotrophic, but above this threshold it is irreversibly eutrophic. The town must decide how much P to discharge each year, a decision complicated by uncertainty in the natural P inflow to the lake. The shallow lake problem provides a conceptually rich set of dynamics, low computational demands, and a high level of mathematical difficulty. These properties maximize its value for benchmarking the relative merits and limitations of emerging decision support frameworks, such as Direct Policy Search (DPS). Here, we explore the use of DPS as a formal means of developing robust environmental pollution control rules that effectively account for deeply uncertain system states and conflicting objectives. The DPS reformulation of the shallow lake problem shows promise in formalizing pollution control triggers and signposts, while dramatically reducing the computational complexity of the multi-objective pollution control problem. More broadly, the insights from the DPS variant of the shallow lake problem formulated in this study bridge emerging work related to socio-ecological systems management, tipping points, robust decision making, and robust control.

Multi-criteria evaluation methods in the production scheduling

NASA Astrophysics Data System (ADS)

Kalinowski, K.; Krenczyk, D.; Paprocka, I.; Kempa, W.; Grabowik, C.

2016-08-01

The paper presents a discussion on the practical application of different methods of multi-criteria evaluation in the process of scheduling in manufacturing systems. Among the methods two main groups are specified: methods based on the distance function (using metacriterion) and methods that create a Pareto set of possible solutions. The basic criteria used for scheduling were also described. The overall procedure of evaluation process in production scheduling was presented. It takes into account the actions in the whole scheduling process and human decision maker (HDM) participation. The specified HDM decisions are related to creating and editing a set of evaluation criteria, selection of multi-criteria evaluation method, interaction in the searching process, using informal criteria and making final changes in the schedule for implementation. According to need, process scheduling may be completely or partially automated. Full automatization is possible in case of metacriterion based objective function and if Pareto set is selected - the final decision has to be done by HDM.

Generalizable open source urban water portfolio simulation framework demonstrated using a multi-objective risk-based planning benchmark problem.

NASA Astrophysics Data System (ADS)

Trindade, B. C.; Reed, P. M.

2017-12-01

The growing access and reduced cost for computing power in recent years has promoted rapid development and application of multi-objective water supply portfolio planning. As this trend continues there is a pressing need for flexible risk-based simulation frameworks and improved algorithm benchmarking for emerging classes of water supply planning and management problems. This work contributes the Water Utilities Management and Planning (WUMP) model: a generalizable and open source simulation framework designed to capture how water utilities can minimize operational and financial risks by regionally coordinating planning and management choices, i.e. making more efficient and coordinated use of restrictions, water transfers and financial hedging combined with possible construction of new infrastructure. We introduce the WUMP simulation framework as part of a new multi-objective benchmark problem for planning and management of regionally integrated water utility companies. In this problem, a group of fictitious water utilities seek to balance the use of the mentioned reliability driven actions (e.g., restrictions, water transfers and infrastructure pathways) and their inherent financial risks. Several traits of this problem make it ideal for a benchmark problem, namely the presence of (1) strong non-linearities and discontinuities in the Pareto front caused by the step-wise nature of the decision making formulation and by the abrupt addition of storage through infrastructure construction, (2) noise due to the stochastic nature of the streamflows and water demands, and (3) non-separability resulting from the cooperative formulation of the problem, in which decisions made by stakeholder may substantially impact others. Both the open source WUMP simulation framework and its demonstration in a challenging benchmarking example hold value for promoting broader advances in urban water supply portfolio planning for regions confronting change.

Multi-criteria decision models for forestry and natural resources management: an annotated bibliography

Treesearch

Joseph E. de Steiguer; Leslie Liberti; Albert Schuler; Bruce Hansen

2003-01-01

Foresters and natural resource managers must balance conflicting objectives when developing land-management plans. Conflicts may encompass economic, environmental, social, cultural, technical, and aesthetic objectives. Selecting the best combination of management uses from numerous objectives is difficult and challenging. Multi-Criteria Decision Models (MCDM) provide a...

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.

Three essays on multi-level optimization models and applications

NASA Astrophysics Data System (ADS)

Rahdar, Mohammad

The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation problem in each node and decreasing the number of iterations. Computational experiments show that the proposed algorithm is faster than the existing ones.

A Framework for Multi-Stakeholder Decision-Making and Conflict Resolution (abstract)

EPA Science Inventory

This contribution describes the implementation of the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. It is observed that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as ran...

Interaction of Technology Adoption Constraints and Multi-level Policy Coherence at the Energy-Food Nexus

NASA Astrophysics Data System (ADS)

Gerst, M.; Cox, M. E.; Laser, M.; Locke, K. A.; Kapuscinski, A. R.

2017-12-01

Policy- and decision-making at the food-energy-water (FEW) nexus entails additional complexities due to the multi-objective nature of FEW socio-technical systems: policies and decisions meant to improve one facet of the nexus might be less beneficial, or even detrimental, to achieving goals for other facets. In addition, implementing policies and decisions may be more difficult due to increasing coordination required among stakeholders across each nexus facet. We highlight these issues in an economic, material/energy flow, and institutional assessment of dairy farms that produce power from anaerobic digestion of cow manure. This socio-technical system is an example of an integrated food-energy system (IFES), which co-produces food and energy. In the case of dairy farms, water is also a significant consideration because cow manure, if improperly managed, can negatively impact water bodies. Our assessment asks the questions (i) of whether or not adopting an IFES improves farm resilience under potential economic and environment futures and (ii) how decisions, policies, and information can best be tailored to the FEW nexus. Our study consists of semi-structured interviews of 60 farms split between the US states of New York and Vermont, both of which have enacted policies to encourage digester adoption. Each interview asks farmers about their material and energy flows, costs, and decision-making process for adopting (or not) an anaerobic digester. In addition, farmers are asked questions about challenges and barriers they might have faced and future drivers of change. Preliminary results highlight important interactions between policy and decision-making. Foremost, an analysis of policy cohesion shows that environmental objectives cross sectors and governance levels, as state-level greenhouse gas mitigation policies interact with federal-level nutrient management policies. This form of potential policy incoherence may introduce additional problems that hinder digester adoption and operation because technology options might be constrained and information needs may be too great for farmer's to consider adopting a digester.

Network-centric decision architecture for financial or 1/f data models

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.; Massey, Stoney; Case, Carl T.; Songy, Claude G.

2002-12-01

This paper presents a decision architecture algorithm for training neural equation based networks to make autonomous multi-goal oriented, multi-class decisions. These architectures make decisions based on their individual goals and draw from the same network centric feature set. Traditionally, these architectures are comprised of neural networks that offer marginal performance due to lack of convergence of the training set. We present an approach for autonomously extracting sample points as I/O exemplars for generation of multi-branch, multi-node decision architectures populated by adaptively derived neural equations. To test the robustness of this architecture, open source data sets in the form of financial time series were used, requiring a three-class decision space analogous to the lethal, non-lethal, and clutter discrimination problem. This algorithm and the results of its application are presented here.

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.

The environmental management problem of Pohorje, Slovenia: A new group approach within ANP - SWOT framework.

PubMed

Grošelj, Petra; Zadnik Stirn, Lidija

2015-09-15

Environmental management problems can be dealt with by combining participatory methods, which make it possible to include various stakeholders in a decision-making process, and multi-criteria methods, which offer a formal model for structuring and solving a problem. This paper proposes a three-phase decision making approach based on the analytic network process and SWOT (strengths, weaknesses, opportunities and threats) analysis. The approach enables inclusion of various stakeholders or groups of stakeholders in particular stages of decision making. The structure of the proposed approach is composed of a network consisting of an objective cluster, a cluster of strategic goals, a cluster of SWOT factors and a cluster of alternatives. The application of the suggested approach is applied to a management problem of Pohorje, a mountainous area in Slovenia. Stakeholders from sectors that are important for Pohorje (forestry, agriculture, tourism and nature protection agencies) who can offer a wide range of expert knowledge were included in the decision-making process. The results identify the alternative of "sustainable development" as the most appropriate for development of Pohorje. The application in the paper offers an example of employing the new approach to an environmental management problem. This can also be applied to decision-making problems in various other fields. Copyright © 2015 Elsevier Ltd. All rights reserved.

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Jamshidi, Mo

1997-01-01

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

An innovative approach to addressing childhood obesity: a knowledge-based infrastructure for supporting multi-stakeholder partnership decision-making in Quebec, Canada.

PubMed

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L; Dubé, Laurette

2015-01-23

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a "portrait", which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity.

An Innovative Approach to Addressing Childhood Obesity: A Knowledge-Based Infrastructure for Supporting Multi-Stakeholder Partnership Decision-Making in Quebec, Canada

PubMed Central

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L.; Dubé, Laurette

2015-01-01

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a “portrait”, which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity. PMID:25625409

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.

Integrating regional conservation priorities for multiple objectives into national policy

PubMed Central

Beger, Maria; McGowan, Jennifer; Treml, Eric A.; Green, Alison L.; White, Alan T.; Wolff, Nicholas H.; Klein, Carissa J.; Mumby, Peter J.; Possingham, Hugh P.

2015-01-01

Multinational conservation initiatives that prioritize investment across a region invariably navigate trade-offs among multiple objectives. It seems logical to focus where several objectives can be achieved efficiently, but such multi-objective hotspots may be ecologically inappropriate, or politically inequitable. Here we devise a framework to facilitate a regionally cohesive set of marine-protected areas driven by national preferences and supported by quantitative conservation prioritization analyses, and illustrate it using the Coral Triangle Initiative. We identify areas important for achieving six objectives to address ecosystem representation, threatened fauna, connectivity and climate change. We expose trade-offs between areas that contribute substantially to several objectives and those meeting one or two objectives extremely well. Hence there are two strategies to guide countries choosing to implement regional goals nationally: multi-objective hotspots and complementary sets of single-objective priorities. This novel framework is applicable to any multilateral or global initiative seeking to apply quantitative information in decision making. PMID:26364769

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.

A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs.

PubMed

Forkan, Abdur Rahim Mohammad; Khalil, Ibrahim

2017-02-01

In home-based context-aware monitoring patient's real-time data of multiple vital signs (e.g. heart rate, blood pressure) are continuously generated from wearable sensors. The changes in such vital parameters are highly correlated. They are also patient-centric and can be either recurrent or can fluctuate. The objective of this study is to develop an intelligent method for personalized monitoring and clinical decision support through early estimation of patient-specific vital sign values, and prediction of anomalies using the interrelation among multiple vital signs. In this paper, multi-label classification algorithms are applied in classifier design to forecast these values and related abnormalities. We proposed a completely new approach of patient-specific vital sign prediction system using their correlations. The developed technique can guide healthcare professionals to make accurate clinical decisions. Moreover, our model can support many patients with various clinical conditions concurrently by utilizing the power of cloud computing technology. The developed method also reduces the rate of false predictions in remote monitoring centres. In the experimental settings, the statistical features and correlations of six vital signs are formulated as multi-label classification problem. Eight multi-label classification algorithms along with three fundamental machine learning algorithms are used and tested on a public dataset of 85 patients. Different multi-label classification evaluation measures such as Hamming score, F1-micro average, and accuracy are used for interpreting the prediction performance of patient-specific situation classifications. We achieved 90-95% Hamming score values across 24 classifier combinations for 85 different patients used in our experiment. The results are compared with single-label classifiers and without considering the correlations among the vitals. The comparisons show that multi-label method is the best technique for this problem domain. The evaluation results reveal that multi-label classification techniques using the correlations among multiple vitals are effective ways for early estimation of future values of those vitals. In context-aware remote monitoring this process can greatly help the doctors in quick diagnostic decision making. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Reserch on Urban Spatial Expansion Model Based on Multi-Object Gray Decision-Making and Ca: a Case Study of Pidu District, Chengdu City

NASA Astrophysics Data System (ADS)

Liu, Z.; Li, Y.

2018-04-01

This paper from the perspective of the Neighbor cellular space, Proposed a new urban space expansion model based on a new multi-objective gray decision and CA. The model solved the traditional cellular automata conversion rules is difficult to meet the needs of the inner space-time analysis of urban changes and to overcome the problem of uncertainty in the combination of urban drivers and urban cellular automata. At the same time, the study takes Pidu District as a research area and carries out urban spatial simulation prediction and analysis, and draws the following conclusions: (1) The design idea of the urban spatial expansion model proposed in this paper is that the urban driving factor and the neighborhood function are tightly coupled by the multi-objective grey decision method based on geographical conditions. The simulation results show that the simulation error of urban spatial expansion is less than 5.27 %. The Kappa coefficient is 0.84. It shows that the model can better capture the inner transformation mechanism of the city. (2) We made a simulation prediction for Pidu District of Chengdu by discussing Pidu District of Chengdu as a system instance.In this way, we analyzed the urban growth tendency of this area.presenting a contiguous increasing mode, which is called "urban intensive development". This expansion mode accorded with sustainable development theory and the ecological urbanization design theory.

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.

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

NASA Astrophysics Data System (ADS)

Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

2015-08-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

Improving multi-objective reservoir operation optimization with sensitivity-informed problem decomposition

NASA Astrophysics Data System (ADS)

Chu, J. G.; Zhang, C.; Fu, G. T.; Li, Y.; Zhou, H. C.

2015-04-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce the computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed problem decomposition dramatically reduces the computational demands required for attaining high quality approximations of optimal tradeoff relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed problem decomposition and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform problem decomposition when solving the complex multi-objective reservoir operation problems.

CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

PubMed Central

Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

2015-01-01

Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. PMID:25848413

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.

Multi-Metric Sustainability Analysis

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

Cowlin, Shannon; Heimiller, Donna; Macknick, Jordan

2014-12-01

A readily accessible framework that allows for evaluating impacts and comparing tradeoffs among factors in energy policy, expansion planning, and investment decision making is lacking. Recognizing this, the Joint Institute for Strategic Energy Analysis (JISEA) funded an exploration of multi-metric sustainability analysis (MMSA) to provide energy decision makers with a means to make more comprehensive comparisons of energy technologies. The resulting MMSA tool lets decision makers simultaneously compare technologies and potential deployment locations.

The necessary burden of involving stakeholders in agent-based modelling for education and decision-making

NASA Astrophysics Data System (ADS)

Bommel, P.; Bautista Solís, P.; Leclerc, G.

2016-12-01

We implemented a participatory process with water stakeholders for improving resilience to drought at watershed scale, and for reducing water pollution disputes in drought prone Northwestern Costa Rica. The purpose is to facilitate co-management in a rural watershed impacted by recurrent droughts related to ENSO. The process involved designing "ContaMiCuenca", a hybrid agent-based model where users can specify the decisions of their agents. We followed a Companion Modeling approach (www.commod.org) and organized 10 workshops that included research techniques such as participatory diagnostics, actor-resources-interaction and UML diagrams, multi-agents model design, and interactive simulation sessions. We collectively assessed the main water issues in the watershed, prioritized their importance, defined the objectives of the process, and pilot-tested ContaMiCuenca for environmental education with adults and children. Simulation sessions resulted in debates about the need to improve the model accuracy, arguably more relevant for decision-making. This helped identify sensible knowledge gaps in the groundwater pollution and aquifer dynamics that need to be addressed in order to improve our collective learning. Significant mismatches among participants expectations, objectives, and agendas considerably slowed down the participatory process. The main issue may originate in participants expecting technical solutions from a positivist science, as constantly promoted in the region by dole-out initiatives, which is incompatible with the constructivist stance of participatory modellers. This requires much closer interaction of community members with modellers, which may be hard to attain in the current research practice and institutional context. Nevertheless, overcoming these constraints is necessary for a true involvement of water stakeholders to achieve community-based decisions that facilitate integrated water management. Our findings provide significant guidance for improving the trans-generational engagement of stakeholders in participatory modeling processes in a context of limited technical skills and information, research expectative mismatches, and poor multi-stakeholder interaction for decision-making.

Analysis and optimization of hybrid electric vehicle thermal management systems

NASA Astrophysics Data System (ADS)

Hamut, H. S.; Dincer, I.; Naterer, G. F.

2014-02-01

In this study, the thermal management system of a hybrid electric vehicle is optimized using single and multi-objective evolutionary algorithms in order to maximize the exergy efficiency and minimize the cost and environmental impact of the system. The objective functions are defined and decision variables, along with their respective system constraints, are selected for the analysis. In the multi-objective optimization, a Pareto frontier is obtained and a single desirable optimal solution is selected based on LINMAP decision-making process. The corresponding solutions are compared against the exergetic, exergoeconomic and exergoenvironmental single objective optimization results. The results show that the exergy efficiency, total cost rate and environmental impact rate for the baseline system are determined to be 0.29, ¢28 h-1 and 77.3 mPts h-1 respectively. Moreover, based on the exergoeconomic optimization, 14% higher exergy efficiency and 5% lower cost can be achieved, compared to baseline parameters at an expense of a 14% increase in the environmental impact. Based on the exergoenvironmental optimization, a 13% higher exergy efficiency and 5% lower environmental impact can be achieved at the expense of a 27% increase in the total cost.

Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process

NASA Astrophysics Data System (ADS)

Ghavami, Seyed Morsal; Taleai, Mohammad

2017-04-01

Most spatial problems are multi-actor, multi-issue and multi-phase in nature. In addition to their intrinsic complexity, spatial problems usually involve groups of actors from different organizational and cognitive backgrounds, all of whom participate in a social structure to resolve or reduce the complexity of a given problem. Hence, it is important to study and evaluate what different aspects influence the spatial problem resolution process. Recently, multi-agent systems consisting of groups of separate agent entities all interacting with each other have been put forward as appropriate tools to use to study and resolve such problems. In this study, then in order to generate a better level of understanding regarding the spatial problem group decision-making process, a conceptual multi-agent-based framework is used that represents and specifies all the necessary concepts and entities needed to aid group decision making, based on a simulation of the group decision-making process as well as the relationships that exist among the different concepts involved. The study uses five main influencing entities as concepts in the simulation process: spatial influence, individual-level influence, group-level influence, negotiation influence and group performance measures. Further, it explains the relationship among different concepts in a descriptive rather than explanatory manner. To illustrate the proposed framework, the approval process for an urban land use master plan in Zanjan—a provincial capital in Iran—is simulated using MAS, the results highlighting the effectiveness of applying an MAS-based framework when wishing to study the group decision-making process used to resolve spatial problems.

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.

Linguistic multi-criteria decision-making with representing semantics by programming

NASA Astrophysics Data System (ADS)

Yang, Wu-E.; Ma, Chao-Qun; Han, Zhi-Qiu

2017-01-01

A linguistic multi-criteria decision-making method is introduced. In this method, a maximising discrimination programming assigns the semanteme values to linguistic variables to represent their semantics. Incomplete preferences from using linguistic information are expressed by the constraints of the model. Such assignment can amplify the difference between alternatives. Thus, the discrimination of the decision model is increased, which facilitates the decision-maker to rank or order the alternatives for making a decision. We also discuss the parameter setting and its influence, and use an application example to illustrate the proposed method. Further, the results with three types of semantic structure highlight the ability of the method in handling different semantic structures.

A Markovian state-space framework for integrating flexibility into space system design decisions

NASA Astrophysics Data System (ADS)

Lafleur, Jarret M.

The past decades have seen the state of the art in aerospace system design progress from a scope of simple optimization to one including robustness, with the objective of permitting a single system to perform well even in off-nominal future environments. Integrating flexibility, or the capability to easily modify a system after it has been fielded in response to changing environments, into system design represents a further step forward. One challenge in accomplishing this rests in that the decision-maker must consider not only the present system design decision, but also sequential future design and operation decisions. Despite extensive interest in the topic, the state of the art in designing flexibility into aerospace systems, and particularly space systems, tends to be limited to analyses that are qualitative, deterministic, single-objective, and/or limited to consider a single future time period. To address these gaps, this thesis develops a stochastic, multi-objective, and multi-period framework for integrating flexibility into space system design decisions. Central to the framework are five steps. First, system configuration options are identified and costs of switching from one configuration to another are compiled into a cost transition matrix. Second, probabilities that demand on the system will transition from one mission to another are compiled into a mission demand Markov chain. Third, one performance matrix for each design objective is populated to describe how well the identified system configurations perform in each of the identified mission demand environments. The fourth step employs multi-period decision analysis techniques, including Markov decision processes from the field of operations research, to find efficient paths and policies a decision-maker may follow. The final step examines the implications of these paths and policies for the primary goal of informing initial system selection. Overall, this thesis unifies state-centric concepts of flexibility from economics and engineering literature with sequential decision-making techniques from operations research. The end objective of this thesis’ framework and its supporting tools is to enable selection of the next-generation space systems today, tailored to decision-maker budget and performance preferences, that will be best able to adapt and perform in a future of changing environments and requirements. Following extensive theoretical development, the framework and its steps are applied to space system planning problems of (1) DARPA-motivated multiple- or distributed-payload satellite selection and (2) NASA human space exploration architecture selection.

Considering Decision Variable Diversity in Multi-Objective Optimization: Application in Hydrologic Model Calibration

NASA Astrophysics Data System (ADS)

Sahraei, S.; Asadzadeh, M.

2017-12-01

Any modern multi-objective global optimization algorithm should be able to archive a well-distributed set of solutions. While the solution diversity in the objective space has been explored extensively in the literature, little attention has been given to the solution diversity in the decision space. Selection metrics such as the hypervolume contribution and crowding distance calculated in the objective space would guide the search toward solutions that are well-distributed across the objective space. In this study, the diversity of solutions in the decision-space is used as the main selection criteria beside the dominance check in multi-objective optimization. To this end, currently archived solutions are clustered in the decision space and the ones in less crowded clusters are given more chance to be selected for generating new solution. The proposed approach is first tested on benchmark mathematical test problems. Second, it is applied to a hydrologic model calibration problem with more than three objective functions. Results show that the chance of finding more sparse set of high-quality solutions increases, and therefore the analyst would receive a well-diverse set of options with maximum amount of information. Pareto Archived-Dynamically Dimensioned Search, which is an efficient and parsimonious multi-objective optimization algorithm for model calibration, is utilized in this study.

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.

Framing bioremediation decision making as negotiation: Rationale & guidelineFraming bioremediation decision making as negotiation: Rationale & guidelines

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

Bjornstad, David J.; Wolfe, Amy K.

Framing remediation decision making as negotiation: (1) social choice, not technology choice; (2) prompts decision makers to identify interested and affected parties, anticipate objections, effectively address and ameliorate objections, and avoid unacceptable decisions.

Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

PubMed

Li, Yan

2017-05-25

The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

Neuroeconomics: A bridge for translational research

PubMed Central

Sharp, Carla; Monterosso, John; Montague, Read

2014-01-01

Neuroeconomic methods combine behavioral economic experiments to parameterize aspects of reward-related decision-making with neuroimaging techniques to record corresponding brain activity. In this introductory paper to the current special issue, we propose that neuroeconomics is a potential bridge for translational research in psychiatry for several reasons. First, neuroeconomics-derived theoretical predictions about optimal adaptation in a changing environment provide an objective metric to examine psychopathology. Second, neuroeconomics provides a ‘multi-level’ research approach that combines performance (behavioral) measures with intermediate measures between behavior and neurobiology (e.g, neuroimaging) and uses a common metaphor to describe decision-making across multiple levels of explanation. As such, ecologically valid behavioral paradigms closely mirror the physical mechanisms of reward processing. Third, neuroeconomics provides a platform for investigators from neuroscience, economics, psychiatry and social and clinical psychology to develop a common language for studying reward-related decision making in psychiatric disorders. Therefore, neuroeconomics can provide promising candidate endophenotypes that may help clarify the basis of high heritability associated with psychiatric disorders and that may, in turn, inform treatment. PMID:22727459

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.

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)

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.

Shapley value-based multi-objective data envelopment analysis application for assessing academic efficiency of university departments

NASA Astrophysics Data System (ADS)

Abing, Stephen Lloyd N.; Barton, Mercie Grace L.; Dumdum, Michael Gerard M.; Bongo, Miriam F.; Ocampo, Lanndon A.

2018-02-01

This paper adopts a modified approach of data envelopment analysis (DEA) to measure the academic efficiency of university departments. In real-world case studies, conventional DEA models often identify too many decision-making units (DMUs) as efficient. This occurs when the number of DMUs under evaluation is not large enough compared to the total number of decision variables. To overcome this limitation and reduce the number of decision variables, multi-objective data envelopment analysis (MODEA) approach previously presented in the literature is applied. The MODEA approach applies Shapley value as a cooperative game to determine the appropriate weights and efficiency score of each category of inputs. To illustrate the performance of the adopted approach, a case study is conducted in a university in the Philippines. The input variables are academic staff, non-academic staff, classrooms, laboratories, research grants, and department expenditures, while the output variables are the number of graduates and publications. The results of the case study revealed that all DMUs are inefficient. DMUs with efficiency scores close to the ideal efficiency score may be emulated by other DMUs with least efficiency scores.

Comprehensive evaluation of garment assembly line with simulation

NASA Astrophysics Data System (ADS)

Xu, Y.; Thomassey, S.; Chen, Y.; Zeng, X.

2017-10-01

In this paper, a comprehensive evaluation system is established to assess the garment production performance. It is based on performance indicators and supported with the corresponding results obtained by manual calculation or computer simulation. The assembly lines of a typical men’s shirt are taken as the study objects. With the comprehensive evaluation results, garments production arrangement scenarios are better analysed and then the appropriate one is supposed to be put into actual production. This will be a guidance given to companies on quick decision-making and multi-objective optimization of garment production.

Is it time to use checklists in mental health care auditing?

PubMed

Abramowitz, Moshe Z; Polackiewicz, Jacob; Grinshpoon, Alexander

2011-02-22

A key strategy for improving the quality of mental health care is the design and implementation of a mechanism for on-site inspection and clinical auditing. We discuss the use of checklists in auditing providing an objective, comprehensive system for recording and analyzing multi-disciplinary, clinical auditing in mental health services. We believe such an approach can identify potential risks and allow for better decision making.

Is it time to use checklists in mental health care auditing?

PubMed Central

Abramowitz, Moshe Z.; Polackiewicz, Jacob; Grinshpoon, Alexander

2011-01-01

A key strategy for improving the quality of mental health care is the design and implementation of a mechanism for on-site inspection and clinical auditing. We discuss the use of checklists in auditing providing an objective, comprehensive system for recording and analyzing multi-disciplinary, clinical auditing in mental health services. We believe such an approach can identify potential risks and allow for better decision making. PMID:25478101

An effective and comprehensive model for optimal rehabilitation of separate sanitary sewer systems.

PubMed

Diogo, António Freire; Barros, Luís Tiago; Santos, Joana; Temido, Jorge Santos

2018-01-15

In the field of rehabilitation of separate sanitary sewer systems, a large number of technical, environmental, and economic aspects are often relevant in the decision-making process, which may be modelled as a multi-objective optimization problem. Examples are those related with the operation and assessment of networks, optimization of structural, hydraulic, sanitary, and environmental performance, rehabilitation programmes, and execution works. In particular, the cost of investment, operation and maintenance needed to reduce or eliminate Infiltration from the underground water table and Inflows of storm water surface runoff (I/I) using rehabilitation techniques or related methods can be significantly lower than the cost of transporting and treating these flows throughout the lifespan of the systems or period studied. This paper presents a comprehensive I/I cost-benefit approach for rehabilitation that explicitly considers all elements of the systems and shows how the approximation is incorporated as an objective function in a general evolutionary multi-objective optimization model. It takes into account network performance and wastewater treatment costs, average values of several input variables, and rates that can reflect the adoption of different predictable or limiting scenarios. The approach can be used as a practical and fast tool to support decision-making in sewer network rehabilitation in any phase of a project. The fundamental aspects, modelling, implementation details and preliminary results of a two-objective optimization rehabilitation model using a genetic algorithm, with a second objective function related to the structural condition of the network and the service failure risk, are presented. The basic approach is applied to three real world cases studies of sanitary sewerage systems in Coimbra and the results show the simplicity, suitability, effectiveness, and usefulness of the approximation implemented and of the objective function proposed. Copyright © 2017 Elsevier B.V. All rights reserved.

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 ...

Decision Making under Ambiguity and Objective Risk in Higher Age - A Review on Cognitive and Emotional Contributions.

PubMed

Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

2017-01-01

The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors - responsible for age-related differences in decision making - are additionally pointed out.

Decision Making under Ambiguity and Objective Risk in Higher Age – A Review on Cognitive and Emotional Contributions

PubMed Central

Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

2017-01-01

The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors – responsible for age-related differences in decision making – are additionally pointed out. PMID:29270145

An intuitionistic fuzzy multi-objective non-linear programming model for sustainable irrigation water allocation under the combination of dry and wet conditions

NASA Astrophysics Data System (ADS)

Li, Mo; Fu, Qiang; Singh, Vijay P.; Ma, Mingwei; Liu, Xiao

2017-12-01

Water scarcity causes conflicts among natural resources, society and economy and reinforces the need for optimal allocation of irrigation water resources in a sustainable way. Uncertainties caused by natural conditions and human activities make optimal allocation more complex. An intuitionistic fuzzy multi-objective non-linear programming (IFMONLP) model for irrigation water allocation under the combination of dry and wet conditions is developed to help decision makers mitigate water scarcity. The model is capable of quantitatively solving multiple problems including crop yield increase, blue water saving, and water supply cost reduction to obtain a balanced water allocation scheme using a multi-objective non-linear programming technique. Moreover, it can deal with uncertainty as well as hesitation based on the introduction of intuitionistic fuzzy numbers. Consideration of the combination of dry and wet conditions for water availability and precipitation makes it possible to gain insights into the various irrigation water allocations, and joint probabilities based on copula functions provide decision makers an average standard for irrigation. A case study on optimally allocating both surface water and groundwater to different growth periods of rice in different subareas in Heping irrigation area, Qing'an County, northeast China shows the potential and applicability of the developed model. Results show that the crop yield increase target especially in tillering and elongation stages is a prevailing concern when more water is available, and trading schemes can mitigate water supply cost and save water with an increased grain output. Results also reveal that the water allocation schemes are sensitive to the variation of water availability and precipitation with uncertain characteristics. The IFMONLP model is applicable for most irrigation areas with limited water supplies to determine irrigation water strategies under a fuzzy environment.

Risk approximation in decision making: approximative numeric abilities predict advantageous decisions under objective risk.

PubMed

Mueller, Silke M; Schiebener, Johannes; Delazer, Margarete; Brand, Matthias

2018-01-22

Many decision situations in everyday life involve mathematical considerations. In decisions under objective risk, i.e., when explicit numeric information is available, executive functions and abilities to handle exact numbers and ratios are predictors of objectively advantageous choices. Although still debated, exact numeric abilities, e.g., normative calculation skills, are assumed to be related to approximate number processing skills. The current study investigates the effects of approximative numeric abilities on decision making under objective risk. Participants (N = 153) performed a paradigm measuring number-comparison, quantity-estimation, risk-estimation, and decision-making skills on the basis of rapid dot comparisons. Additionally, a risky decision-making task with exact numeric information was administered, as well as tasks measuring executive functions and exact numeric abilities, e.g., mental calculation and ratio processing skills, were conducted. Approximative numeric abilities significantly predicted advantageous decision making, even beyond the effects of executive functions and exact numeric skills. Especially being able to make accurate risk estimations seemed to contribute to superior choices. We recommend approximation skills and approximate number processing to be subject of future investigations on decision making under risk.

Operation Exodus: The Massacre of 44 Philippine Police Commandos In Mamasapano Clash

DTIC Science & Technology

2016-09-01

strategic thinking, utilizing Game Theory and Multi-Attribute Decision Making; the combination of these two dynamic tools is used to evaluate their...thinking, utilizing Game Theory and Multi-Attribute Decision Making; the combination of these two dynamic tools is used to evaluate their potential...35 A. GAME THEORETIC APPROACH ......................................................36 B. APPLYING GAME THEORY TO OPLAN: EXODUS

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 ...

Deciding Factors: Do Factors beyond Achievement Influence Teachers' Student Placement Decisions?

ERIC Educational Resources Information Center

Riley, Tasha

2014-01-01

Since teachers' decisions potentially have consequences for learners' future educational and life opportunities, it is imperative to determine the basis of teachers' decision-making in order to determine whether it is discriminatory. This study combines qualitative and quantitative methods towards a multi-school, multi-region study of Australian…

Changing Times, Complex Decisions: Presidential Values and Decision Making

ERIC Educational Resources Information Center

Hornak, Anne M.; Garza Mitchell, Regina L.

2016-01-01

Objective: The objective of this article is to delve more deeply into the thought processes of the key decision makers at community colleges and understand how they make decisions. Specifically, this article focuses on the role of the community college president's personal values in decision making. Method: We conducted interviews with 13…

Application of fuzzy theories to formulation of multi-objective design problems. [for helicopters

NASA Technical Reports Server (NTRS)

Dhingra, A. K.; Rao, S. S.; Miura, H.

1988-01-01

Much of the decision making in real world takes place in an environment in which the goals, the constraints, and the consequences of possible actions are not known precisely. In order to deal with imprecision quantitatively, the tools of fuzzy set theory can by used. This paper demonstrates the effectiveness of fuzzy theories in the formulation and solution of two types of helicopter design problems involving multiple objectives. The first problem deals with the determination of optimal flight parameters to accomplish a specified mission in the presence of three competing objectives. The second problem addresses the optimal design of the main rotor of a helicopter involving eight objective functions. A method of solving these multi-objective problems using nonlinear programming techniques is presented. Results obtained using fuzzy formulation are compared with those obtained using crisp optimization techniques. The outlined procedures are expected to be useful in situations where doubt arises about the exactness of permissible values, degree of credibility, and correctness of statements and judgements.

Fuzzy decision-making framework for treatment selection based on the combined QUALIFLEX-TODIM method

NASA Astrophysics Data System (ADS)

Ji, Pu; Zhang, Hong-yu; Wang, Jian-qiang

2017-10-01

Treatment selection is a multi-criteria decision-making problem of significant concern in the medical field. In this study, a fuzzy decision-making framework is established for treatment selection. The framework mitigates information loss by introducing single-valued trapezoidal neutrosophic numbers to denote evaluation information. Treatment selection has multiple criteria that remarkably exceed the alternatives. In consideration of this characteristic, the framework utilises the idea of the qualitative flexible multiple criteria method. Furthermore, it considers the risk-averse behaviour of a decision maker by employing a concordance index based on TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) method. A sensitivity analysis is performed to illustrate the robustness of the framework. Finally, a comparative analysis is conducted to compare the framework with several extant methods. Results indicate the advantages of the framework and its better performance compared with the extant methods.

A multi-phase network situational awareness cognitive task analysis

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

Erbacher, Robert; Frincke, Deborah A.; Wong, Pak C.

Abstract The goal of our project is to create a set of next-generation cyber situational-awareness capabilities with applications to other domains in the long term. The objective is to improve the decision-making process to enable decision makers to choose better actions. To this end, we put extensive effort into making certain that we had feedback from network analysts and managers and understand what their genuine needs are. This article discusses the cognitive task-analysis methodology that we followed to acquire feedback from the analysts. This article also provides the details we acquired from the analysts on their processes, goals, concerns, themore » data and metadata that they analyze. Finally, we describe the generation of a novel task-flow diagram representing the activities of the target user base.« less

The Constructive Role of Decisions: Implications from a quantum Approach

DTIC Science & Technology

2016-12-01

objectives. The first was to explore the nature of constructive influences in decision making . The second concerned understanding decision making in...Prisoner’s Dilemma. **First objective; constructive judgments. This is the idea that sometimes making a decision can alter the underlying relevant mental...the performance of the agent. 15.  SUBJECT TERMS EOARD, Quantum Probability, Human Modeling, Human Decision Making 16.  SECURITY CLASSIFICATION OF

Young adults' decision making surrounding heavy drinking: a multi-staged model of planned behaviour.

PubMed

Northcote, Jeremy

2011-06-01

This paper examines the real life contexts in which decisions surrounding heavy drinking are made by young adults (that is, on occasions when five or more alcoholic drinks are consumed within a few hours). It presents a conceptual model that views such decision making as a multi-faceted and multi-staged process. The mixed method study draws on purposive data gathered through direct observation of eight social networks consisting of 81 young adults aged between 18 and 25 years in Perth, Western Australia, including in-depth interviews with 31 participants. Qualitative and some basic quantitative data were gathered using participant observation and in-depth interviews undertaken over an eighteen month period. Participants explained their decision to engage in heavy drinking as based on a variety of factors. These elements relate to socio-cultural norms and expectancies that are best explained by the theory of planned behaviour. A framework is proposed that characterises heavy drinking as taking place in a multi-staged manner, with young adults having: 1. A generalised orientation to the value of heavy drinking shaped by wider influences and norms; 2. A short-term orientation shaped by situational factors that determines drinking intentions for specific events; and 3. An evaluative orientation shaped by moderating factors. The value of qualitative studies of decision making in real life contexts is advanced to complement the mostly quantitative research that dominates research on alcohol decision making. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

NASA Astrophysics Data System (ADS)

Vahdani, Behnam; Tavakkoli-Moghaddam, Reza; Jolai, Fariborz; Baboli, Arman

2013-06-01

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.

A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach.

PubMed

Varmazyar, Mohsen; Dehghanbaghi, Maryam; Afkhami, Mehdi

2016-10-01

Balanced Scorecard (BSC) is a strategic evaluation tool using both financial and non-financial indicators to determine the business performance of organizations or companies. In this paper, a new integrated approach based on the Balanced Scorecard (BSC) and multi-criteria decision making (MCDM) methods are proposed to evaluate the performance of research centers of research and technology organization (RTO) in Iran. Decision-Making Trial and Evaluation Laboratory (DEMATEL) are employed to reflect the interdependencies among BSC perspectives. Then, Analytic Network Process (ANP) is utilized to weight the indices influencing the considered problem. In the next step, we apply four MCDM methods including Additive Ratio Assessment (ARAS), Complex Proportional Assessment (COPRAS), Multi-Objective Optimization by Ratio Analysis (MOORA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking of alternatives. Finally, the utility interval technique is applied to combine the ranking results of MCDM methods. Weighted utility intervals are computed by constructing a correlation matrix between the ranking methods. A real case is presented to show the efficacy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

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

Hierarchical Object-based Image Analysis approach for classification of sub-meter multispectral imagery in Tanzania

NASA Astrophysics Data System (ADS)

Chung, C.; Nagol, J. R.; Tao, X.; Anand, A.; Dempewolf, J.

2015-12-01

Increasing agricultural production while at the same time preserving the environment has become a challenging task. There is a need for new approaches for use of multi-scale and multi-source remote sensing data as well as ground based measurements for mapping and monitoring crop and ecosystem state to support decision making by governmental and non-governmental organizations for sustainable agricultural development. High resolution sub-meter imagery plays an important role in such an integrative framework of landscape monitoring. It helps link the ground based data to more easily available coarser resolution data, facilitating calibration and validation of derived remote sensing products. Here we present a hierarchical Object Based Image Analysis (OBIA) approach to classify sub-meter imagery. The primary reason for choosing OBIA is to accommodate pixel sizes smaller than the object or class of interest. Especially in non-homogeneous savannah regions of Tanzania, this is an important concern and the traditional pixel based spectral signature approach often fails. Ortho-rectified, calibrated, pan sharpened 0.5 meter resolution data acquired from DigitalGlobe's WorldView-2 satellite sensor was used for this purpose. Multi-scale hierarchical segmentation was performed using multi-resolution segmentation approach to facilitate the use of texture, neighborhood context, and the relationship between super and sub objects for training and classification. eCognition, a commonly used OBIA software program, was used for this purpose. Both decision tree and random forest approaches for classification were tested. The Kappa index agreement for both algorithms surpassed the 85%. The results demonstrate that using hierarchical OBIA can effectively and accurately discriminate classes at even LCCS-3 legend.

Group assessment of key indicators of sustainable waste management in developing countries.

PubMed

Tot, Bojana; Vujić, Goran; Srđević, Zorica; Ubavin, Dejan; Russo, Mário Augusto Tavares

2017-09-01

Decision makers in developing countries are struggling to solve the present problems of solid waste management. Prioritisation and ranking of the most important indicators that influence the waste management system is very useful for any decision maker for the future planning and implementation of a sustainable waste management system. The aim of this study is to evaluate key indicators and their related sub-indicators in a group decision-making environment. In order to gain insight into the subject it was necessary to obtain the qualified opinions of decision makers from different countries who understand the situation in the sector of waste management in developing countries. An assessment is performed by 43 decision makers from both developed and developing countries, and the applied methodology is based on a combined use of the analytic hierarchy process, from the multi-criteria decision-making set of tools, and the preferential voting method known as Borda Count, which belongs to social choice theory. Pairwise comparison of indicators is performed with the analytic hierarchy process, and the ranking of indicators once obtained is assessed with Borda Count. Detailed analysis of the final results showed that the Institutional-Administrative indicator was the most important one, with the maximum weight as derived by both groups of decision makers. The results also showed that the combined use of the analytic hierarchy process and Borda Count contributes to the credibility and objectivity of the decision-making process, allowing its use in more complex waste management group decision-making problems to be recommended.

Research on multi-level decision game strategy of electricity sales market considering ETS and block chain

NASA Astrophysics Data System (ADS)

Liu, Jinjie

2017-08-01

In order to fully consider the impact of future policies and technologies on the electricity sales market, improve the efficiency of electricity market operation, realize the dual goal of power reform and energy saving and emission reduction, this paper uses multi-level decision theory to put forward the double-layer game model under the consideration of ETS and block chain. We set the maximization of electricity sales profit as upper level objective and establish a game strategy model of electricity purchase; while we set maximization of user satisfaction as lower level objective and build a choice behavior model based on customer satisfaction. This paper applies the strategy to the simulation of a sales company's transaction, and makes a horizontal comparison of the same industry competitors as well as a longitudinal comparison of game strategies considering different factors. The results show that Double-layer game model is reasonable and effective, it can significantly improve the efficiency of the electricity sales companies and user satisfaction, while promoting new energy consumption and achieving energy-saving emission reduction.

PATIENT-CENTERED DECISION MAKING: LESSONS FROM MULTI-CRITERIA DECISION ANALYSIS FOR QUANTIFYING PATIENT PREFERENCES.

PubMed

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

2018-01-01

Patient preferences should be a central consideration in healthcare decision making. However, stories of patients challenging regulatory and reimbursement decisions has led to questions on whether patient voices are being considered sufficiently during those decision making processes. This has led some to argue that it is necessary to quantify patient preferences before they can be adequately considered. This study considers the lessons from the use of multi-criteria decision analysis (MCDA) for efforts to quantify patient preferences. It defines MCDA and summarizes the benefits it can provide to decision makers, identifies examples of MCDAs that have involved patients, and summarizes good practice guidelines as they relate to quantifying patient preferences. The guidance developed to support the use of MCDA in healthcare provide some useful considerations for the quantification of patient preferences, namely that researchers should give appropriate consideration to: the heterogeneity of patient preferences, and its relevance to decision makers; the cognitive challenges posed by different elicitation methods; and validity of the results they produce. Furthermore, it is important to consider how the relevance of these considerations varies with the decision being supported. The MCDA literature holds important lessons for how patient preferences should be quantified to support healthcare decision making.

Multiattribute selection of acute stroke imaging software platform for Extending the Time for Thrombolysis in Emergency Neurological Deficits (EXTEND) clinical trial.

PubMed

Churilov, Leonid; Liu, Daniel; Ma, Henry; Christensen, Soren; Nagakane, Yoshinari; Campbell, Bruce; Parsons, Mark W; Levi, Christopher R; Davis, Stephen M; Donnan, Geoffrey A

2013-04-01

The appropriateness of a software platform for rapid MRI assessment of the amount of salvageable brain tissue after stroke is critical for both the validity of the Extending the Time for Thrombolysis in Emergency Neurological Deficits (EXTEND) Clinical Trial of stroke thrombolysis beyond 4.5 hours and for stroke patient care outcomes. The objective of this research is to develop and implement a methodology for selecting the acute stroke imaging software platform most appropriate for the setting of a multi-centre clinical trial. A multi-disciplinary decision making panel formulated the set of preferentially independent evaluation attributes. Alternative Multi-Attribute Value Measurement methods were used to identify the best imaging software platform followed by sensitivity analysis to ensure the validity and robustness of the proposed solution. Four alternative imaging software platforms were identified. RApid processing of PerfusIon and Diffusion (RAPID) software was selected as the most appropriate for the needs of the EXTEND trial. A theoretically grounded generic multi-attribute selection methodology for imaging software was developed and implemented. The developed methodology assured both a high quality decision outcome and a rational and transparent decision process. This development contributes to stroke literature in the area of comprehensive evaluation of MRI clinical software. At the time of evaluation, RAPID software presented the most appropriate imaging software platform for use in the EXTEND clinical trial. The proposed multi-attribute imaging software evaluation methodology is based on sound theoretical foundations of multiple criteria decision analysis and can be successfully used for choosing the most appropriate imaging software while ensuring both robust decision process and outcomes. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.

Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA.

PubMed

Mühlbacher, Axel C; Kaczynski, Anika

2016-02-01

Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.

A conceptual framework for economic optimization of single hazard surveillance in livestock production chains.

PubMed

Guo, Xuezhen; Claassen, G D H; Oude Lansink, A G J M; Saatkamp, H W

2014-06-01

Economic analysis of hazard surveillance in livestock production chains is essential for surveillance organizations (such as food safety authorities) when making scientifically based decisions on optimization of resource allocation. To enable this, quantitative decision support tools are required at two levels of analysis: (1) single-hazard surveillance system and (2) surveillance portfolio. This paper addresses the first level by presenting a conceptual approach for the economic analysis of single-hazard surveillance systems. The concept includes objective and subjective aspects of single-hazard surveillance system analysis: (1) a simulation part to derive an efficient set of surveillance setups based on the technical surveillance performance parameters (TSPPs) and the corresponding surveillance costs, i.e., objective analysis, and (2) a multi-criteria decision making model to evaluate the impacts of the hazard surveillance, i.e., subjective analysis. The conceptual approach was checked for (1) conceptual validity and (2) data validity. Issues regarding the practical use of the approach, particularly the data requirement, were discussed. We concluded that the conceptual approach is scientifically credible for economic analysis of single-hazard surveillance systems and that the practicability of the approach depends on data availability. Copyright © 2014 Elsevier B.V. All rights reserved.

[A multi-measure analysis of the similarity, attraction, and compromise effects in multi-attribute decision making].

PubMed

Tsuzuki, Takashi; Matsui, Hiroshi; Kikuchi, Manabu

2012-12-01

In multi-attribute decision making, the similarity, attraction, and compromise effects warrant specific investigation as they cause violations of principles in rational choice. In order to investigate these three effects simultaneously, we assigned 145 undergraduates to three context effect conditions. We requested them to solve the same 20 hypothetical purchase problems, each of which had three alternatives described along two attributes. We measured their choices, confidence ratings, and response times. We found that manipulating the third alternative had significant context effects for choice proportions and confidence ratings in all three conditions. Furthermore, the attraction effect was the most prominent with regard to choice proportions. In the compromise effect condition, although the choice proportion of the third alternative was high, the confidence rating was low and the response time was long. These results indicate that the relationship between choice proportions and confidence ratings requires further theoretical investigation. They also suggest that a combination of experimental and modeling studies is imperative to reveal the mechanisms underlying the context effects in multi-attribute, multi-alternative decision making.

TACtic- A Multi Behavioral Agent for Trading Agent Competition

NASA Astrophysics Data System (ADS)

Khosravi, Hassan; Shiri, Mohammad E.; Khosravi, Hamid; Iranmanesh, Ehsan; Davoodi, Alireza

Software agents are increasingly being used to represent humans in online auctions. Such agents have the advantages of being able to systematically monitor a wide variety of auctions and then make rapid decisions about what bids to place in what auctions. They can do this continuously and repetitively without losing concentration. To provide a means of evaluating and comparing (benchmarking) research methods in this area the trading agent competition (TAC) was established. This paper describes the design, of TACtic. Our agent uses multi behavioral techniques at the heart of its decision making to make bidding decisions in the face of uncertainty, to make predictions about the likely outcomes of auctions, and to alter the agent's bidding strategy in response to the prevailing market conditions.

Application of best practice approaches for designing decision support tools: The preparatory education about clinical trials (PRE-ACT) study

PubMed Central

Fleisher, Linda; Ruggieri, Dominique G.; Miller, Suzanne M.; Manne, Sharon; Albrecht, Terrance; Buzaglo, Joanne; Collins, Michael A.; Katz, Michael; Kinzy, Tyler G.; Liu, Tasnuva; Manning, Cheri; Charap, Ellen Specker; Millard, Jennifer; Miller, Dawn M.; Poole, David; Raivitch, Stephanie; Roach, Nancy; Ross, Eric A.; Meropol, Neal J.

2014-01-01

Objective This article describes the rigorous development process and initial feedback of the PRE-ACT (Preparatory Education About Clinical Trials) web-based- intervention designed to improve preparation for decision making in cancer clinical trials. Methods The multi-step process included stakeholder input, formative research, user testing and feedback. Diverse teams (researchers, advocates and developers) participated including content refinement, identification of actors, and development of video scripts. Patient feedback was provided in the final production period and through a vanguard group (N = 100) from the randomized trial. Results Patients/advocates confirmed barriers to cancer clinical trial participation, including lack of awareness and knowledge, fear of side effects, logistical concerns, and mistrust. Patients indicated they liked the tool’s user-friendly nature, the organized and comprehensive presentation of the subject matter, and the clarity of the videos. Conclusion The development process serves as an example of operationalizing best practice approaches and highlights the value of a multi-disciplinary team to develop a theory-based, sophisticated tool that patients found useful in their decision making process. Practice implications Best practice approaches can be addressed and are important to ensure evidence-based tools that are of value to patients and supports the usefulness of a process map in the development of e-health tools. PMID:24813474

Multidisciplinary design optimization of vehicle instrument panel based on multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Ping; Wu, Guangqiang

2013-03-01

Typical multidisciplinary design optimization(MDO) has gradually been proposed to balance performances of lightweight, noise, vibration and harshness(NVH) and safety for instrument panel(IP) structure in the automotive development. Nevertheless, plastic constitutive relation of Polypropylene(PP) under different strain rates, has not been taken into consideration in current reliability-based and collaborative IP MDO design. In this paper, based on tensile test under different strain rates, the constitutive relation of Polypropylene material is studied. Impact simulation tests for head and knee bolster are carried out to meet the regulation of FMVSS 201 and FMVSS 208, respectively. NVH analysis is performed to obtain mainly the natural frequencies and corresponding mode shapes, while the crashworthiness analysis is employed to examine the crash behavior of IP structure. With the consideration of lightweight, NVH, head and knee bolster impact performance, design of experiment(DOE), response surface model(RSM), and collaborative optimization(CO) are applied to realize the determined and reliability-based optimizations, respectively. Furthermore, based on multi-objective genetic algorithm(MOGA), the optimal Pareto sets are completed to solve the multi-objective optimization(MOO) problem. The proposed research ensures the smoothness of Pareto set, enhances the ability of engineers to make a comprehensive decision about multi-objectives and choose the optimal design, and improves the quality and efficiency of MDO.

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Multi-Item Multiperiodic Inventory Control Problem with Variable Demand and Discounts: A Particle Swarm Optimization Algorithm

PubMed Central

Mousavi, Seyed Mohsen; Niaki, S. T. A.; Bahreininejad, Ardeshir; Musa, Siti Nurmaya

2014-01-01

A multi-item multiperiod inventory control model is developed for known-deterministic variable demands under limited available budget. Assuming the order quantity is more than the shortage quantity in each period, the shortage in combination of backorder and lost sale is considered. The orders are placed in batch sizes and the decision variables are assumed integer. Moreover, all unit discounts for a number of products and incremental quantity discount for some other items are considered. While the objectives are to minimize both the total inventory cost and the required storage space, the model is formulated into a fuzzy multicriteria decision making (FMCDM) framework and is shown to be a mixed integer nonlinear programming type. In order to solve the model, a multiobjective particle swarm optimization (MOPSO) approach is applied. A set of compromise solution including optimum and near optimum ones via MOPSO has been derived for some numerical illustration, where the results are compared with those obtained using a weighting approach. To assess the efficiency of the proposed MOPSO, the model is solved using multi-objective genetic algorithm (MOGA) as well. A large number of numerical examples are generated at the end, where graphical and statistical approaches show more efficiency of MOPSO compared with MOGA. PMID:25093195

Genetic algorithm approaches for conceptual design of spacecraft systems including multi-objective optimization and design under uncertainty

NASA Astrophysics Data System (ADS)

Hassan, Rania A.

In the design of complex large-scale spacecraft systems that involve a large number of components and subsystems, many specialized state-of-the-art design tools are employed to optimize the performance of various subsystems. However, there is no structured system-level concept-architecting process. Currently, spacecraft design is heavily based on the heritage of the industry. Old spacecraft designs are modified to adapt to new mission requirements, and feasible solutions---rather than optimal ones---are often all that is achieved. During the conceptual phase of the design, the choices available to designers are predominantly discrete variables describing major subsystems' technology options and redundancy levels. The complexity of spacecraft configurations makes the number of the system design variables that need to be traded off in an optimization process prohibitive when manual techniques are used. Such a discrete problem is well suited for solution with a Genetic Algorithm, which is a global search technique that performs optimization-like tasks. This research presents a systems engineering framework that places design requirements at the core of the design activities and transforms the design paradigm for spacecraft systems to a top-down approach rather than the current bottom-up approach. To facilitate decision-making in the early phases of the design process, the population-based search nature of the Genetic Algorithm is exploited to provide computationally inexpensive---compared to the state-of-the-practice---tools for both multi-objective design optimization and design optimization under uncertainty. In terms of computational cost, those tools are nearly on the same order of magnitude as that of standard single-objective deterministic Genetic Algorithm. The use of a multi-objective design approach provides system designers with a clear tradeoff optimization surface that allows them to understand the effect of their decisions on all the design objectives under consideration simultaneously. Incorporating uncertainties avoids large safety margins and unnecessary high redundancy levels. The focus on low computational cost for the optimization tools stems from the objective that improving the design of complex systems should not be achieved at the expense of a costly design methodology.

A hybrid credibility-based fuzzy multiple objective optimisation to differential pricing and inventory policies with arbitrage consideration

NASA Astrophysics Data System (ADS)

Ghasemy Yaghin, R.; Fatemi Ghomi, S. M. T.; Torabi, S. A.

2015-10-01

In most markets, price differentiation mechanisms enable manufacturers to offer different prices for their products or services in different customer segments; however, the perfect price discrimination is usually impossible for manufacturers. The importance of accounting for uncertainty in such environments spurs an interest to develop appropriate decision-making tools to deal with uncertain and ill-defined parameters in joint pricing and lot-sizing problems. This paper proposes a hybrid bi-objective credibility-based fuzzy optimisation model including both quantitative and qualitative objectives to cope with these issues. Taking marketing and lot-sizing decisions into account simultaneously, the model aims to maximise the total profit of manufacturer and to improve service aspects of retailing simultaneously to set different prices with arbitrage consideration. After applying appropriate strategies to defuzzify the original model, the resulting non-linear multi-objective crisp model is then solved by a fuzzy goal programming method. An efficient stochastic search procedure using particle swarm optimisation is also proposed to solve the non-linear crisp model.

Decision making based on data analysis and optimization algorithm applied for cogeneration systems integration into a grid

NASA Astrophysics Data System (ADS)

Asmar, Joseph Al; Lahoud, Chawki; Brouche, Marwan

2018-05-01

Cogeneration and trigeneration systems can contribute to the reduction of primary energy consumption and greenhouse gas emissions in residential and tertiary sectors, by reducing fossil fuels demand and grid losses with respect to conventional systems. The cogeneration systems are characterized by a very high energy efficiency (80 to 90%) as well as a less polluting aspect compared to the conventional energy production. The integration of these systems into the energy network must simultaneously take into account their economic and environmental challenges. In this paper, a decision-making strategy will be introduced and is divided into two parts. The first one is a strategy based on a multi-objective optimization tool with data analysis and the second part is based on an optimization algorithm. The power dispatching of the Lebanese electricity grid is then simulated and considered as a case study in order to prove the compatibility of the cogeneration power calculated by our decision-making technique. In addition, the thermal energy produced by the cogeneration systems which capacity is selected by our technique shows compatibility with the thermal demand for district heating.

The Impact of Quantitative Data Provided by a Multi-spectral Digital Skin Lesion Analysis Device on Dermatologists'Decisions to Biopsy Pigmented Lesions.

PubMed

Farberg, Aaron S; Winkelmann, Richard R; Tucker, Natalie; White, Richard; Rigel, Darrell S

2017-09-01

BACKGROUND: Early diagnosis of melanoma is critical to survival. New technologies, such as a multi-spectral digital skin lesion analysis (MSDSLA) device [MelaFind, STRATA Skin Sciences, Horsham, Pennsylvania] may be useful to enhance clinician evaluation of concerning pigmented skin lesions. Previous studies evaluated the effect of only the binary output. OBJECTIVE: The objective of this study was to determine how decisions dermatologists make regarding pigmented lesion biopsies are impacted by providing both the underlying classifier score (CS) and associated probability risk provided by multi-spectral digital skin lesion analysis. This outcome was also compared against the improvement reported with the provision of only the binary output. METHODS: Dermatologists attending an educational conference evaluated 50 pigmented lesions (25 melanomas and 25 benign lesions). Participants were asked if they would biopsy the lesion based on clinical images, and were asked this question again after being shown multi-spectral digital skin lesion analysis data that included the probability graphs and classifier score. RESULTS: Data were analyzed from a total of 160 United States board-certified dermatologists. Biopsy sensitivity for melanoma improved from 76 percent following clinical evaluation to 92 percent after quantitative multi-spectral digital skin lesion analysis information was provided ( p <0.0001). Specificity improved from 52 percent to 79 percent ( p <0.0001). The positive predictive value increased from 61 percent to 81 percent ( p <0.01) when the quantitative data were provided. Negative predictive value also increased (68% vs. 91%, p<0.01), and overall biopsy accuracy was greater with multi-spectral digital skin lesion analysis (64% vs. 86%, p <0.001). Interrater reliability improved (intraclass correlation 0.466 before, 0.559 after). CONCLUSION: Incorporating the classifier score and probability data into physician evaluation of pigmented lesions led to both increased sensitivity and specificity, thereby resulting in more accurate biopsy decisions.

Coding Theory Information Theory and Radar

DTIC Science & Technology

2005-01-01

the design and synthesis of artificial multiagent systems and for the understanding of human decision-making processes. This... altruism that may exist in a complex society. SGT derives its ability to account simultaneously for both group and individual interests from the structure of ...satisficing decision theory as a model of human decision mak- ing. 2 Multi-Attribute Decision Making Many decision problems involve the consideration of

Biomarkers for Early Detection of Clinically Relevant Prostate Cancer. A Multi-Institutional Validation Trial

DTIC Science & Technology

2016-10-01

Study (PASS). We are in the process of evaluating these three biomarker panels in tissue, blood, and urine samples with well annotated clinical and...impacting both the initial choice of therapy and decision-making during AS. The objective of the study is to utilize analytically validated assays that...predict reclassification from Gleason 6 cancer to Gleason 7 or greater. The analysis plan was determined before specimens were selected for the study

Biomarkers for Early Detection of Clinically Relevant Prostate Cancer. A Multi-Institutional Validation Trial

DTIC Science & Technology

2016-10-01

Study (PASS). We are in the process of evaluating these three biomarker panels in tissue, blood, and urine samples with well annotated clinical and...choice of therapy and decision-making during AS. The objective of the study is to utilize analytically validated assays that take into account tumor...Gleason 6 cancer to Gleason 7 or greater. The analysis plan was determined before specimens were selected for the study , and included 7 breaking

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.

A multi-valued neutrosophic qualitative flexible approach based on likelihood for multi-criteria decision-making problems

NASA Astrophysics Data System (ADS)

Peng, Juan-juan; Wang, Jian-qiang; Yang, Wu-E.

2017-01-01

In this paper, multi-criteria decision-making (MCDM) problems based on the qualitative flexible multiple criteria method (QUALIFLEX), in which the criteria values are expressed by multi-valued neutrosophic information, are investigated. First, multi-valued neutrosophic sets (MVNSs), which allow the truth-membership function, indeterminacy-membership function and falsity-membership function to have a set of crisp values between zero and one, are introduced. Then the likelihood of multi-valued neutrosophic number (MVNN) preference relations is defined and the corresponding properties are also discussed. Finally, an extended QUALIFLEX approach based on likelihood is explored to solve MCDM problems where the assessments of alternatives are in the form of MVNNs; furthermore an example is provided to illustrate the application of the proposed method, together with a comparison analysis.

The conceptualisation of health-related quality of life in decision-making by intensive care physicians: A qualitative inquiry.

PubMed

Haines, Dr Kimberley J; Remedios, Louisa; Berney, Sue C; Knott, Dr Cameron; Denehy, Linda

2017-05-01

To explore how intensive care physicians conceptualise and prioritise patient health-related quality of life in their decision-making. General qualitative inquiry using elements of Grounded Theory. Six ICU physicians participated. A large, closed, mixed ICU at a university-affiliated hospital, Australia. Three themes emerged: (1) Multi-dimensionality of HRQoL-HRQoL was described as difficult to understand; the patient was viewed as the best informant. Proxy information on HRQoL and health preferences was used to direct clinical care, despite not always being trusted. (2) Prioritisation of HRQoL within decision-making-this varied across the patient's health care trajectory. Premorbid HRQoL was prioritised when making admission decisions and used to predict future HRQoL. (3) Role of physician in decision-making-the physicians described their role as representing society with peers influencing their decision-making. All participants considered their practice to be similar to their peers, referring to their practice as the "middle of the road". This is a novel finding, emphasising other important influences in high-stakes decision-making. Critical care physicians conceptualised HRQoL as a multi-dimensional subjective construct. Patient (or proxy) voice was integral in establishing patient HRQoL and future health preferences. HRQoL was important in high stakes decision-making including initiating invasive and burdensome therapies or in redirecting therapeutic goals. Copyright © 2016 Australian College of Critical Care Nurses Ltd. All rights reserved.

Integration of environmental aspects in modelling and optimisation of water supply chains.

PubMed

Koleva, Mariya N; Calderón, Andrés J; Zhang, Di; Styan, Craig A; Papageorgiou, Lazaros G

2018-04-26

Climate change becomes increasingly more relevant in the context of water systems planning. Tools are necessary to provide the most economic investment option considering the reliability of the infrastructure from technical and environmental perspectives. Accordingly, in this work, an optimisation approach, formulated as a spatially-explicit multi-period Mixed Integer Linear Programming (MILP) model, is proposed for the design of water supply chains at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, and raw water trading schemes. The objective is to minimise the total cost incurring from capital and operating expenditures. Assessment of available resources for withdrawal is performed based on hydrological balances, governmental rules and sustainable limits. In the light of the increasing importance of reliability of water supply, a second objective, seeking to maximise the reliability of the supply chains, is introduced. The epsilon-constraint method is used as a solution procedure for the multi-objective formulation. Nash bargaining approach is applied to investigate the fair trade-offs between the two objectives and find the Pareto optimality. The models' capability is addressed through a case study based on Australia. The impact of variability in key input parameters is tackled through the implementation of a rigorous global sensitivity analysis (GSA). The findings suggest that variations in water demand can be more disruptive for the water supply chain than scenarios in which rainfalls are reduced. The frameworks can facilitate governmental multi-aspect decision making processes for the adequate and strategic investments of regional water supply infrastructure. Copyright © 2018. Published by Elsevier B.V.

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

Assessment, evaluation, and testing of technologies for environmental restoration, decontamination, and decommissioning and high level waste management. Progress report

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

Uzochukwu, G.A.

1997-12-31

Nuclear and commercial non-nuclear technologies that have the potential of meeting the environmental restoration, decontamination and decommissioning, and high-level waste management objectives are being assessed and evaluated. A detailed comparison of innovative technologies available will be performed to determine the safest and most economical technology for meeting these objectives. Information derived from this effort will be matched with the multi-objectives of the environmental restoration, decontamination and decommissioning, and high-level waste management effort to ensure that the best, most economical, and the safest technologies are used in decision making at USDOE-SRS. Technology-related variables will be developed and the resulting data formattedmore » and computerized for multimedia systems. The multimedia system will be made available to technology developers and evaluators to ensure that the best, most economical, and the safest technologies are used in decision making at USDOE-SRS. Technology-related variables will be developed and the resulting data formatted and computerized for multimedia systems. The multimedia system will be made available to technology developers and evaluators to ensure that the safest and most economical technologies are developed for use at SRS and other DOE sites.« less

To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task

PubMed Central

Lamb, Maurice; Kallen, Rachel W.; Harrison, Steven J.; Di Bernardo, Mario; Minai, Ali; Richardson, Michael J.

2017-01-01

Humans commonly engage in tasks that require or are made more efficient by coordinating with other humans. In this paper we introduce a task dynamics approach for modeling multi-agent interaction and decision making in a pick and place task where an agent must move an object from one location to another and decide whether to act alone or with a partner. Our aims were to identify and model (1) the affordance related dynamics that define an actor's choice to move an object alone or to pass it to their co-actor and (2) the trajectory dynamics of an actor's hand movements when moving to grasp, relocate, or pass the object. Using a virtual reality pick and place task, we demonstrate that both the decision to pass or not pass an object and the movement trajectories of the participants can be characterized in terms of a behavioral dynamics model. Simulations suggest that the proposed behavioral dynamics model exhibits features observed in human participants including hysteresis in decision making, non-straight line trajectories, and non-constant velocity profiles. The proposed model highlights how the same low-dimensional behavioral dynamics can operate to constrain multiple (and often nested) levels of human activity and suggests that knowledge of what, when, where and how to move or act during pick and place behavior may be defined by these low dimensional task dynamics and, thus, can emerge spontaneously and in real-time with little a priori planning. PMID:28701975

Collaborative Response and Recovery from a Foot-and-Mouth Disease Animal Health Emergency: Supporting Decision Making in a Complex Environment with Multiple Stakeholders

DTIC Science & Technology

2013-12-01

RESPONSE AND RECOVERY FROM A FOOT-AND- MOUTH DISEASE ANIMAL HEALTH EMERGENCY: SUPPORTING DECISION MAKING IN A COMPLEX ENVIRONMENT WITH MULTIPLE...Thesis 4. TITLE AND SUBTITLE COLLABORATIVE RESPONSE AND RECOVERY FROM A FOOT-AND- MOUTH DISEASE ANIMAL HEALTH EMERGENCY: SUPPORTING DECISION MAKING...200 words ) This thesis recommends ways to support decision makers who must operate within the multi-stakeholder complex situation of response and

Multi-alternative decision-making with non-stationary inputs.

PubMed

Nunes, Luana F; Gurney, Kevin

2016-08-01

One of the most widely implemented models for multi-alternative decision-making is the multihypothesis sequential probability ratio test (MSPRT). It is asymptotically optimal, straightforward to implement, and has found application in modelling biological decision-making. However, the MSPRT is limited in application to discrete ('trial-based'), non-time-varying scenarios. By contrast, real world situations will be continuous and entail stimulus non-stationarity. In these circumstances, decision-making mechanisms (like the MSPRT) which work by accumulating evidence, must be able to discard outdated evidence which becomes progressively irrelevant. To address this issue, we introduce a new decision mechanism by augmenting the MSPRT with a rectangular integration window and a transparent decision boundary. This allows selection and de-selection of options as their evidence changes dynamically. Performance was enhanced by adapting the window size to problem difficulty. Further, we present an alternative windowing method which exponentially decays evidence and does not significantly degrade performance, while greatly reducing the memory resources necessary. The methods presented have proven successful at allowing for the MSPRT algorithm to function in a non-stationary environment.

Single-photon decision maker

NASA Astrophysics Data System (ADS)

Naruse, Makoto; Berthel, Martin; Drezet, Aurélien; Huant, Serge; Aono, Masashi; Hori, Hirokazu; Kim, Song-Ju

2015-08-01

Decision making is critical in our daily lives and for society in general and is finding evermore practical applications in information and communication technologies. Herein, we demonstrate experimentally that single photons can be used to make decisions in uncertain, dynamically changing environments. Using a nitrogen-vacancy in a nanodiamond as a single-photon source, we demonstrate the decision-making capability by solving the multi-armed bandit problem. This capability is directly and immediately associated with single-photon detection in the proposed architecture, leading to adequate and adaptive autonomous decision making. This study makes it possible to create systems that benefit from the quantum nature of light to perform practical and vital intelligent functions.

Achieving realistic performance and decison-making capabilities in computer-generated air forces

NASA Astrophysics Data System (ADS)

Banks, Sheila B.; Stytz, Martin R.; Santos, Eugene, Jr.; Zurita, Vincent B.; Benslay, James L., Jr.

1997-07-01

For a computer-generated force (CGF) system to be useful in training environments, it must be able to operate at multiple skill levels, exhibit competency at assigned missions, and comply with current doctrine. Because of the rapid rate of change in distributed interactive simulation (DIS) and the expanding set of performance objectives for any computer- generated force, the system must also be modifiable at reasonable cost and incorporate mechanisms for learning. Therefore, CGF applications must have adaptable decision mechanisms and behaviors and perform automated incorporation of past reasoning and experience into its decision process. The CGF must also possess multiple skill levels for classes of entities, gracefully degrade its reasoning capability in response to system stress, possess an expandable modular knowledge structure, and perform adaptive mission planning. Furthermore, correctly performing individual entity behaviors is not sufficient. Issues related to complex inter-entity behavioral interactions, such as the need to maintain formation and share information, must also be considered. The CGF must also be able to acceptably respond to unforeseen circumstances and be able to make decisions in spite of uncertain information. Because of the need for increased complexity in the virtual battlespace, the CGF should exhibit complex, realistic behavior patterns within the battlespace. To achieve these necessary capabilities, an extensible software architecture, an expandable knowledge base, and an adaptable decision making mechanism are required. Our lab has addressed these issues in detail. The resulting DIS-compliant system is called the automated wingman (AW). The AW is based on fuzzy logic, the common object database (CODB) software architecture, and a hierarchical knowledge structure. We describe the techniques we used to enable us to make progress toward a CGF entity that satisfies the requirements presented above. We present our design and implementation of an adaptable decision making mechanism that uses multi-layered, fuzzy logic controlled situational analysis. Because our research indicates that fuzzy logic can perform poorly under certain circumstances, we combine fuzzy logic inferencing with adversarial game tree techniques for decision making in strategic and tactical engagements. We describe the approach we employed to achieve this fusion. We also describe the automated wingman's system architecture and knowledge base architecture.

A stochastic conflict resolution model for trading pollutant discharge permits in river systems.

PubMed

Niksokhan, Mohammad Hossein; Kerachian, Reza; Amin, Pedram

2009-07-01

This paper presents an efficient methodology for developing pollutant discharge permit trading in river systems considering the conflict of interests of involving decision-makers and the stakeholders. In this methodology, a trade-off curve between objectives is developed using a powerful and recently developed multi-objective genetic algorithm technique known as the Nondominated Sorting Genetic Algorithm-II (NSGA-II). The best non-dominated solution on the trade-off curve is defined using the Young conflict resolution theory, which considers the utility functions of decision makers and stakeholders of the system. These utility functions are related to the total treatment cost and a fuzzy risk of violating the water quality standards. The fuzzy risk is evaluated using the Monte Carlo analysis. Finally, an optimization model provides the trading discharge permit policies. The practical utility of the proposed methodology in decision-making is illustrated through a realistic example of the Zarjub River in the northern part of Iran.

[Decision making in the elderly: which tools for its evaluation by the clinician?].

PubMed

Hommet, Caroline; Constans, Thierry; Atanasova, Boriana; Mondon, Karl

2010-09-01

Numerous decision-making situations occur in the activities of daily living. The consequences of the decision-making capacity disturbances may have a great impact on the patient's autonomy, financial management, and his or her reaction to a diagnosis as well as the ability to accept a therapeutic option or give informed consent. Decision-making is a complex and multi-dimensional process and brings into play attention, memory and executive functions, which are processed in the prefrontal cortex, particularly vulnerable in aging. A better comprehension of the mechanisms of decision-making, and of the resulting social consequences of their dysfunction may improve autonomy of the elderly. Unfortunately, we still lack appropriate tools to explore decision-making in routine practice.

Decision-making Strategies and Performance among Seniors1

PubMed Central

Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

2011-01-01

Using paper and pencil experiments administered in senior centers, we examine decision-making performance in multi-attribute decision problems. We differentiate the effects of declining cognitive performance and changing cognitive process on decision-making performance of seniors as they age. We find a significant decline in performance with age due to reduced reliance on common heuristics and increased decision-making randomness among our oldest subjects. However, we find that increasing the number of options in a decision problem increases the number of heuristics brought to the task. This challenges the choice overload view that people give up when confronted with too much choice. PMID:22408282

A multi-layered governance framework for incorporating social science insights into adapting to the health impacts of climate change

PubMed Central

Bowen, Kathryn J.; Ebi, Kristie; Friel, Sharon; McMichael, Anthony J.

2013-01-01

Background Addressing climate change and its associated effects is a multi-dimensional and ongoing challenge. This includes recognizing that climate change will affect the health and wellbeing of all populations over short and longer terms, albeit in varied ways and intensities. That recognition has drawn attention to the need to take adaptive actions to lessen adverse impacts over the next few decades from unavoidable climate change, particularly in developing country settings. A range of sectors is responsible for appropriate adaptive policies and measures to address the health risks of climate change, including health services, water and sanitation, trade, agriculture, disaster management, and development. Objectives To broaden the framing of governance and decision-making processes by using innovative methods and assessments to illustrate the multi-sectoral nature of health-related adaptation to climate change. This is a shift from sector-specific to multi-level systems encompassing sectors and actors, across temporal and spatial scales. Design A review and synthesis of the current knowledge in the areas of health and climate change adaptation governance and decision-making processes. Results A novel framework is presented that incorporates social science insights into the formulation and implementation of adaptation activities and policies to lessen the health risks posed by climate change. Conclusion Clarification of the roles that different sectors, organizations, and individuals occupy in relation to the development of health-related adaptation strategies will facilitate the inclusion of health and wellbeing within multi-sector adaptation policies, thereby strengthening the overall set of responses to minimize the adverse health effects of climate change. PMID:24028938

Evaluation of water security in Jordan using a multi-agent, hydroeconomic model: Initial model results from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Medellin-Azuara, J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.; Zhang, H.

2016-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for water policy evaluation in Jordan. Jordan ranks among the most water-scarce countries in the world, a situation exacerbated due to a recent influx of refugees escaping the ongoing civil war in neighboring Syria. The modular, multi-agent model is used to evaluate interventions for enhancing Jordan's water security, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the multi-agent model, we explicitly account for human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. Human agents are implemented as autonomous entities in the model that make decisions in relation to one another and in response to hydrologic and socioeconomic conditions. The integrated model is programmed in Python using Pynsim, a generalizable, open-source object-oriented software framework for modeling network-based water resource systems. The modeling time periods include historical (2006-2014) and future (present-2050) time spans. For the historical runs, the model performance is validated against historical data for several observations that reflect the interacting dynamics of both the hydrologic and human components of the system. A historical counterfactual scenario is also constructed to isolate and identify the impacts of the recent Syrian civil war and refugee crisis on Jordan's water system. For the future period, model runs are conducted to evaluate potential supply, demand, and institutional interventions over a wide range of plausible climate and socioeconomic scenarios. In addition, model sensitivity analysis is conducted revealing the hydrologic and human aspects of the system that most strongly influence water security outcomes, providing insight into coupled human-water system dynamics as well as priority areas of focus for continued model improvement.

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.

Structured decision making for managing pneumonia epizootics in bighorn sheep

USGS Publications Warehouse

Sells, Sarah N.; Mitchell, Michael S.; Edwards, Victoria L.; Gude, Justin A.; Anderson, Neil J.

2016-01-01

Good decision-making is essential to conserving wildlife populations. Although there may be multiple ways to address a problem, perfect solutions rarely exist. Managers are therefore tasked with identifying decisions that will best achieve desired outcomes. Structured decision making (SDM) is a method of decision analysis used to identify the most effective, efficient, and realistic decisions while accounting for values and priorities of the decision maker. The stepwise process includes identifying the management problem, defining objectives for solving the problem, developing alternative approaches to achieve the objectives, and formally evaluating which alternative is most likely to accomplish the objectives. The SDM process can be more effective than informal decision-making because it provides a transparent way to quantitatively evaluate decisions for addressing multiple management objectives while incorporating science, uncertainty, and risk tolerance. To illustrate the application of this process to a management need, we present an SDM-based decision tool developed to identify optimal decisions for proactively managing risk of pneumonia epizootics in bighorn sheep (Ovis canadensis) in Montana. Pneumonia epizootics are a major challenge for managers due to long-term impacts to herds, epistemic uncertainty in timing and location of future epizootics, and consequent difficulty knowing how or when to manage risk. The decision tool facilitates analysis of alternative decisions for how to manage herds based on predictions from a risk model, herd-specific objectives, and predicted costs and benefits of each alternative. Decision analyses for 2 example herds revealed that meeting management objectives necessitates specific approaches unique to each herd. The analyses showed how and under what circumstances the alternatives are optimal compared to other approaches and current management. Managers can be confident that these decisions are effective, efficient, and realistic because they explicitly account for important considerations managers implicitly weigh when making decisions, including competing management objectives, uncertainty in potential outcomes, and risk tolerance.

Development of a Support Tool for Complex Decision-Making in the Provision of Rural Maternity Care

PubMed Central

Hearns, Glen; Klein, Michael C.; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-01-01

Context: Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. Objective: To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Design: Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Setting: Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Participants: Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). Results: We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Conclusions: Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology. PMID:21286270

A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions.

PubMed

Turrini, Enrico; Carnevale, Claudio; Finzi, Giovanna; Volta, Marialuisa

2018-04-15

This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO 2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

NASA Astrophysics Data System (ADS)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

Decision Making Under Objective Risk Conditions-a Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences.

PubMed

Schiebener, Johannes; Brand, Matthias

2015-06-01

While making decisions under objective risk conditions, the probabilities of the consequences of the available options are either provided or calculable. Brand et al. (Neural Networks 19:1266-1276, 2006) introduced a model describing the neuro-cognitive processes involved in such decisions. In this model, executive functions associated with activity in the fronto-striatal loop are important for developing and applying decision-making strategies, and for verifying, adapting, or revising strategies according to feedback. Emotional rewards and punishments learned from such feedback accompany these processes. In this literature review, we found support for the role of executive functions, but also found evidence for the importance of further cognitive abilities in decision making. Moreover, in addition to reflective processing (driven by cognition), decisions can be guided by impulsive processing (driven by anticipation of emotional reward and punishment). Reflective and impulsive processing may interact during decision making, affecting the evaluation of available options, as both processes are affected by feedback. Decision-making processes are furthermore modulated by individual attributes (e.g., age), and external influences (e.g., stressors). Accordingly, we suggest a revised model of decision making under objective risk conditions.

Study on the coal mixing ratio optimization for a power plant

NASA Astrophysics Data System (ADS)

Jin, Y. A.; Cheng, J. W.; Bai, Q.; Li, W. B.

2017-12-01

For coal-fired power plants, the application of blended coal combustion has been a great issue due to the shortage and rising prices of high-rank coal. This paper describes the optimization of blending methods between Xing'an lignite coal, Shaltala lignite coal, Ura lignite coal, and Inner Mongolia bituminous coal. The multi-objective decision-making method based on fuzzy mathematics was used to determine the optimal blending ratio to improve the power plant coal-fired economy.

Multi-Objective, Auto-Optimization Modeling for Resource Allocation Decision Making in the Military Health System

DTIC Science & Technology

2014-01-22

FTEs would need to be reduced by 12.16, expenses reduced by $184.63K, and the number of interns adjusted by 7.67. The reference set for DMU D includes...efficiency: concept, measurement techniques and review of hospital efficiency studies. Malaysian Journal of Public Health Medicine, 10(2), 35-43...REPORT DOCUMENTATION PAGE Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 Form Approved OMB No. 0704-0188 The public reporting burden

TIES for Dummies 3rd Edition (Technology Identification, Evaluation, and Selection) Basic how to's to implement the TIES method

NASA Technical Reports Server (NTRS)

Kirby, Michelle R.

2002-01-01

The TIES method is a forecasting environment whereby the decision-maker has the ability to easily assess and trade-off the impact of various technologies without sophisticated and time-consuming mathematical formulations. TIES provides a methodical approach where technically feasible alternatives can be identified with accuracy and speed to reduce design cycle time, and subsequently, life cycle costs, and was achieved through the use of various probabilistic methods, such as Response Surface Methodology and Monte Carlo Simulations. Furthermore, structured and systematic techniques are utilized from other fields to identify possible concepts and evaluation criteria by which comparisons can be made. This objective is achieved by employing the use of Morphological Matrices and Multi-Attribute Decision Making techniques. Through the execution of each step, a family of design alternatives for a given set of customer requirements can be identified and assessed subjectively or objectively. This methodology allows for more information (knowledge) to be brought into the earlier phases of the design process and will have direct implications on the affordability of the system. The increased knowledge allows for optimum allocation of company resources and quantitative justification for program decisions. Finally, the TIES method provided novel results and quantitative justification to facilitate decision making in the early stages of design so as to produce affordable and quality products.

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...

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.

A Framework of Multi Objectives Negotiation for Dynamic Supply Chain Model

NASA Astrophysics Data System (ADS)

Chai, Jia Yee; Sakaguchi, Tatsuhiko; Shirase, Keiichi

Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain utilizes these advances to enable more flexibility in business cooperation. This research proposes a concurrent decision making framework for a three echelons dynamic supply chain model. The dynamic supply chain is formed by autonomous negotiation among agents based on multi agents approach. Instead of generating negotiation aspects (such as amount, price and due date) arbitrary, this framework proposes to utilize the information available at operational level of an organization in order to generate realistic negotiation aspect. The effectiveness of the proposed model is demonstrated by various case studies.

Multispectral Photogrammetric Data Acquisition and Processing Forwall Paintings Studies

NASA Astrophysics Data System (ADS)

Pamart, A.; Guillon, O.; Faraci, S.; Gattet, E.; Genevois, M.; Vallet, J. M.; De Luca, L.

2017-02-01

In the field of wall paintings studies different imaging techniques are commonly used for the documentation and the decision making in term of conservation and restoration. There is nowadays some challenging issues to merge scientific imaging techniques in a multimodal context (i.e. multi-sensors, multi-dimensions, multi-spectral and multi-temporal approaches). For decades those CH objects has been widely documented with Technical Photography (TP) which gives precious information to understand or retrieve the painting layouts and history. More recently there is an increasing demand of the use of digital photogrammetry in order to provide, as one of the possible output, an orthophotomosaic which brings a possibility for metrical quantification of conservators/restorators observations and actions planning. This paper presents some ongoing experimentations of the LabCom MAP-CICRP relying on the assumption that those techniques can be merged through a common pipeline to share their own benefits and create a more complete documentation.

How do persons with dementia participate in decision making related to health and daily care? A multi-case study

PubMed Central

2012-01-01

Background Many countries have passed laws giving patients the right to participate in decisions about health care. People with dementia cannot be assumed to be incapable of making decisions on their diagnosis alone as they may have retained cognitive abilities. The purpose of this study was to gain a better understanding of how persons with dementia participated in making decisions about health care and how their family carers and professional caregivers influenced decision making. Methods This Norwegian study had a qualitative multi-case design. The triad in each of the ten cases consisted of the person with dementia, the family carer and the professional caregiver, in all 30 participants. Inclusion criteria for the persons with dementia were: (1) 67 years or older (2) diagnosed with dementia (3) Clinical Dementia Rating score 2, moderate dementia; (3) able to communicate verbally. The family carers and professional caregivers were then asked to participate. A semi-structured interview guide was used in interviews with family carers and professional caregivers. Field notes were written after participant observation of interactions between persons with dementia and professional caregivers during morning care or activities at a day centre. How the professional caregivers facilitated decision making was the focus of the observations that varied in length from 30 to 90 minutes. The data were analyzed using framework analysis combined with a hermeneutical interpretive approach. Results Professional caregivers based their assessment of mental competence on experience and not on standardized tests. Persons with dementia demonstrated variability in how they participated in decision making. Pseudo-autonomous decision making and delegating decision making were new categories that emerged. Autonomous decision making did occur but shared decision making was the most typical pattern. Reduced mental capacity, lack of available choices or not being given the opportunity to participate led to non-involvement. Not all decisions were based on logic; personal values and relationships were also considered. Conclusions Persons with moderate dementia demonstrated variability in how they participated in decision making. Optimal involvement was facilitated by positioning them as capable of influencing decisions, assessing decision-specific competence, clarifying values and understanding the significance of relationships and context. PMID:22870952

More Heads Are Better than One: School-Based Decision-Making in Varied School Environments

ERIC Educational Resources Information Center

Mokoena, Sello; Machaisa, Rebotile

2018-01-01

In this multi-case qualitative study the degree to which school-based decision-making (SBDM) is understood and conceptualised by the members of school governing bodies (SGBs)--educators, chairpersons of SGBs, principals, and learner representative councils-as well the extent to which decisions were shared among the various groups represented on…

Application of Grey Relational Analysis to Decision-Making during Product Development

ERIC Educational Resources Information Center

Hsiao, Shih-Wen; Lin, Hsin-Hung; Ko, Ya-Chuan

2017-01-01

A multi-attribute decision-making (MADM) approach was proposed in this study as a prediction method that differs from the conventional production and design methods for a product. When a client has different dimensional requirements, this approach can quickly provide a company with design decisions for each product. The production factors of a…

The influence of the dorsolateral prefrontal cortex on attentional behavior and decision making. A t-DCS study on emotionally vs. functionally designed objects.

PubMed

Colombo, Barbara; Balzarotti, Stefania; Mazzucchelli, Nicla

2016-04-01

Prior research has shown that right dorsolateral prefrontal cortex may be crucial in cognitive control of affective impulses during decision making. The present study examines whether modulation of r-DLPFC with transcranial direct current stimulation influences attentional behavior and decision-making in a purchase task requiring participants to choose either emotional/attractive or functional/useful objects. 30 participants were shown sixteen pairs of emotionally or functionally designed products while their eye-movements were recorded. Participants were asked to judge aesthetics and usefulness of each object, and to decide which object of each pair they would buy. Results revealed that participants decided to buy the functionally designed objects more often regardless of condition; however, participants receiving anodal stimulation were faster in decision making. Although stimulation of r-DLPFC did not affect the actual purchasing choice and had little effect on visual exploration during decision making, it influenced perceived usefulness and attractiveness, with temporary inhibition of r-DLPFC leading to evaluate functional objects as less attractive. Finally, anodal stimulation led to judge the objects as more useful. The implications of these results are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Multi-objective optimization in spatial planning: Improving the effectiveness of multi-objective evolutionary algorithms (non-dominated sorting genetic algorithm II)

NASA Astrophysics Data System (ADS)

Karakostas, Spiros

2015-05-01

The multi-objective nature of most spatial planning initiatives and the numerous constraints that are introduced in the planning process by decision makers, stakeholders, etc., synthesize a complex spatial planning context in which the concept of solid and meaningful optimization is a unique challenge. This article investigates new approaches to enhance the effectiveness of multi-objective evolutionary algorithms (MOEAs) via the adoption of a well-known metaheuristic: the non-dominated sorting genetic algorithm II (NSGA-II). In particular, the contribution of a sophisticated crossover operator coupled with an enhanced initialization heuristic is evaluated against a series of metrics measuring the effectiveness of MOEAs. Encouraging results emerge for both the convergence rate of the evolutionary optimization process and the occupation of valuable regions of the objective space by non-dominated solutions, facilitating the work of spatial planners and decision makers. Based on the promising behaviour of both heuristics, topics for further research are proposed to improve their effectiveness.

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.

Chronic Heart Failure Follow-up Management Based on Agent Technology

PubMed Central

Safdari, Reza

2015-01-01

Objectives Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. Methods This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Results Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. Conclusions The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making. PMID:26618038

Strategic Technology Investment Analysis: An Integrated System Approach

NASA Technical Reports Server (NTRS)

Adumitroaie, V.; Weisbin, C. R.

2010-01-01

Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce. This paper describes an approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis. The evaluation of the degree of robustness of the recommended portfolio provides the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy nontechnical constraints. The methodology is presented in the context of assessing capability development portfolios for NASA technology programs.

"Nature Does Things Well, Why Should We Interfere?": Vaccine Hesitancy Among Mothers.

PubMed

Dubé, Eve; Vivion, Maryline; Sauvageau, Chantal; Gagneur, Arnaud; Gagnon, Raymonde; Guay, Maryse

2016-02-01

Parents' decision to use vaccination services is complex and multi-factorial. Of particular interest are "vaccine-hesitant" parents who are in the middle of the continuum between vaccine acceptance and refusal. The objective of this qualitative longitudinal study was to better understand why mothers choose to vaccinate-or not-their newborns. Fifty-six pregnant mothers living in different areas of Quebec (Canada) were interviewed. These interviews gathered information on mothers' views about health and vaccination. Almost half of the mothers were categorized as vaccine-hesitant. A second interview was conducted with these mothers 3 to 11 months after birth to look at their actual decision and behavior concerning vaccination. Our results show the heterogeneity of factors influencing vaccine decision making. Although the majority of vaccine-hesitant mothers finally chose to follow the recommended vaccine schedule for their child, they were still ambivalent and they continued to question their decision. © The Author(s) 2015.

Decision Making in Adults with ADHD

ERIC Educational Resources Information Center

Montyla, Timo; Still, Johanna; Gullberg, Stina; Del Missier, Fabio

2012-01-01

Objectives: This study examined decision-making competence in ADHD by using multiple decision tasks with varying demands on analytic versus affective processes. Methods: Adults with ADHD and healthy controls completed two tasks of analytic decision making, as measured by the Adult Decision-Making Competence (A-DMC) battery, and two affective…

An evaluation of treatment decisions at a colorectal cancer multi-disciplinary team.

PubMed

Wood, J J; Metcalfe, C; Paes, A; Sylvester, P; Durdey, P; Thomas, M G; Blazeby, J M

2008-10-01

It is mandatory for treatment decisions for patients with colorectal cancer to be made within the context of a multi-disciplinary team (MDT) meeting. It is currently uncertain, however, how to best evaluate the quality of MDT decision-making. This study examined MDT decision-making by studying whether MDT treatment decisions were implemented and investigated the reasons why some decisions changed after the meeting. Consecutive MDT treatment decisions were prospectively recorded. Implementation of decisions was studied by examining hospital records. Reasons for changes in MDT decisions were identified. In all, 201 consecutive treatment decisions were analysed, concerning 157 patients. Twenty decisions (10.0%, 95% confidence interval 6.3-15.2%) were not implemented. Looking at the reasons for nonimplementation, nine (40%) related to co-morbidity, seven (35%) to patient choice, two changed in light of new clinical information, one doctor changed a decision and for one changed decision, no reason was apparent. When decisions changed, the final treatment was always more conservative than was originally planned and decisions were more likely to change for colon rather than rectal cancer (P = 0.024). The vast majority of colorectal MDT decisions were implemented and when decisions changed, it mostly related to patient factors that had not been taken into account. Analysis of the implementation of team decisions is an informative process to monitor the quality of MDT decision-making.

Prioritizing Project Risks Using AHP

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

Thibadeau, Barbara M

2007-01-01

This essay introduces the Analytic Hierarchy Process (AHP) as a method by which to rank project risks, in terms of importance as well as likelihood. AHP is way to handle quantifiable and/or intangible criteria in the decision making process. It is a multi-objective multi-criteria decision-making approach that is based on the idea of pair-wise comparisons of alternatives with respect to a given criterion (e.g., which alternative, A or B, is preferred and by how much more is it preferred) or with respect to an objective (e.g., which is more important, A or B, and by how much more is itmore » important). This approach was pioneered by Thomas Saaty in the late 1970's. It has been suggested that a successful project is one that successfully manages risk and that project management is the management of uncertainty. Risk management relies on the quantification of uncertainty which, in turn, is predicated upon the accuracy of probabilistic approaches (in terms of likelihood as well as magnitude). In many cases, the appropriate probability distribution (or probability value) is unknown. And, researchers have shown that probability values are not made very accurately, that the use of verbal expressions is not a suitable alternative, that there is great variability in the use and interpretation of these values and that there is a great reluctance to assign them in the first place. Data from an ongoing project is used to show that AHP can be used to obtain these values, thus overcoming some of the problems associated with the direct assignment of discrete probability values. A novel method by which to calculate the consistency of the data is introduced. The AHP approach is easily implemented and, typically, offers results that are consistent with the decision maker's intuition.« less

Multi-objective Optimization for the Robust Performance of Drinking Water Treatment Plants under Climate Change and Climate Extremes

NASA Astrophysics Data System (ADS)

Raseman, W. J.; Kasprzyk, J. R.; Rosario-Ortiz, F.; Summers, R. S.; Stewart, J.; Livneh, B.

2016-12-01

To promote public health, the United States Environmental Protection Agency (US EPA), and similar entities around the world enact strict laws to regulate drinking water quality. These laws, such as the Stage 1 and 2 Disinfectants and Disinfection Byproducts (D/DBP) Rules, come at a cost to water treatment plants (WTPs) which must alter their operations and designs to meet more stringent standards and the regulation of new contaminants of concern. Moreover, external factors such as changing influent water quality due to climate extremes and climate change, may force WTPs to adapt their treatment methods. To grapple with these issues, decision support systems (DSSs) have been developed to aid WTP operation and planning. However, there is a critical need to better address long-term decision making for WTPs. In this poster, we propose a DSS framework for WTPs for long-term planning, which improves upon the current treatment of deep uncertainties within the overall potable water system including the impact of climate on influent water quality and uncertainties in treatment process efficiencies. We present preliminary results exploring how a multi-objective evolutionary algorithm (MOEA) search can be coupled with models of WTP processes to identify high-performing plans for their design and operation. This coupled simulation-optimization technique uses Borg MOEA, an auto-adaptive algorithm, and the Water Treatment Plant Model, a simulation model developed by the US EPA to assist in creating the D/DBP Rules. Additionally, Monte Carlo sampling methods were used to study the impact of uncertainty of influent water quality on WTP decision-making and generate plans for robust WTP performance.

Selection of adequate site location during early stages of construction project management: A multi-criteria decision analysis approach

NASA Astrophysics Data System (ADS)

Marović, Ivan; Hanak, Tomaš

2017-10-01

In the management of construction projects special attention should be given to the planning as the most important phase of decision-making process. Quality decision-making based on adequate and comprehensive collaboration of all involved stakeholders is crucial in project’s early stages. Fundamental reasons for existence of this problem arise from: specific conditions of construction industry (final products are inseparable from the location i.e. location has a strong influence of building design and its structural characteristics as well as technology which will be used during construction), investors’ desires and attitudes, and influence of socioeconomic and environment aspects. Considering all mentioned reasons one can conclude that selection of adequate construction site location for future investment is complex, low structured and multi-criteria problem. To take into account all the dimensions, the proposed model for selection of adequate site location is devised. The model is based on AHP (for designing the decision-making hierarchy) and PROMETHEE (for pairwise comparison of investment locations) methods. As a result of mixing basis feature of both methods, operational synergies can be achieved in multi-criteria decision analysis. Such gives the decision-maker a sense of assurance, knowing that if the procedure proposed by the presented model has been followed, it will lead to a rational decision, carefully and systematically thought out.

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

Developpement energetique par modelisation et intelligence territoriale: Un outil de prise de decision participative pour le developpement durable des projets eoliens

NASA Astrophysics Data System (ADS)

Vazquez Rascon, Maria de Lourdes

This thesis focuses on the implementation of a participatory and transparent decision making tool about the wind farm projects. This tool is based on an (argumentative) framework that reflects the stakeholder's values systems involved in these projects and it employs two multicriteria methods: the multicriteria decision aide and the participatory geographical information systems, making it possible to represent this value systems by criteria and indicators to be evaluated. The stakeholder's values systems will allow the inclusion of environmental, economic and social-cultural aspects of wind energy projects and, thus, a sustainable development wind projects vision. This vision will be analyzed using the 16 sustainable principles included in the Quebec's Sustainable Development Act. Four specific objectives have been instrumented to favor a logical completion work, and to ensure the development of a successfultool : designing a methodology to couple the MCDA and participatory GIS, testing the developed methodology by a case study, making a robustness analysis to address strategic issues and analyzing the strengths, weaknesses, opportunities and threads of the developed methodology. Achieving the first goal allowed us to obtain a decision-making tool called Territorial Intelligence Modeling for Energy Development (TIMED approach). The TIMED approach is visually represented by a figure expressing the idea of a co-construction decision and where ail stakeholders are the focus of this methodology. TIMED is composed of four modules: Multi-Criteria decision analysis, participatory geographic Information systems, active involvement of the stakeholders and scientific knowledge/local knowledge. The integration of these four modules allows for the analysis of different implementation scenarios of wind turbines in order to choose the best one based on a participatory and transparent decision-making process that takes into account stakeholders' concerns. The second objective enabled the testing of TIMED in an ex-post experience of a wind farm in operation since 2006. In this test, II people participated representing four stakeholder' categories: the private sector, the public sector, experts and civil society. This test allowed us to analyze the current situation in which wind projects are currently developed in Quebec. The concerns of some stakeholders regarding situations that are not considered in the current context were explored through a third goal. This third objective allowed us to make simulations taking into account the assumptions of strategic levels. Examples of the strategic level are the communication tools used to approach the host community and the park property type. Finally, the fourth objective, a SWOT analysis with the participation of eight experts, allowed us to verify the extent to which TIMED approach succeeded in constructing four fields for participatory decision-making: physical, intellectual, emotional and procedural. From these facts, 116 strengths, 28 weaknesses, 32 constraints and 54 opportunities were identified. Contributions, applications, limitations and extensions of this research are based on giving a participatory decision-making methodology taking into account socio-cultural, environmental and economic variables; making reflection sessions on a wind farm in operation; acquiring MCDA knowledge for participants involved in testing the proposed methodology; taking into account the physical, intellectual, emotional and procedural spaces to al1iculate a participatory decision; using the proposed methodology in renewable energy sources other than wind; the need to an interdisciplinary team for the methodology application; access to quality data; access to information technologies; the right to public participation; the neutrality of experts; the relationships between experts and non-experts; cultural constraints; improvement of designed indicators; the implementation of a Web platform for participatory decision-making and writing a manual on the use of the developed methodology. Keywords: wind farm, multicriteria decision, geographic information systems, TIMED approach, sustainable wind energy projects development, renewable energy, social participation, robustness concern, SWOT analysis.

Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2017-04-01

Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

Goal-Proximity Decision-Making

ERIC Educational Resources Information Center

Veksler, Vladislav D.; Gray, Wayne D.; Schoelles, Michael J.

2013-01-01

Reinforcement learning (RL) models of decision-making cannot account for human decisions in the absence of prior reward or punishment. We propose a mechanism for choosing among available options based on goal-option association strengths, where association strengths between objects represent previously experienced object proximity. The proposed…

Knowledge, perceptions, and decision-making about human papillomavirus vaccination among Korean American women: A focus group study

PubMed Central

Kim, Kyounghae; Kim, Boyoung; Choi, Eunsuk; Song, Youngshin; Han, Hae-Ra

2014-01-01

Objective As one of the fastest growing ethnic minority groups in the United States, Korean American (KA) women experience a heightened cervical cancer burden. The advent of the human papillomavirus (HPV) vaccine offers an unprecedented opportunity to eliminate cervical cancer disparities in KA women. Yet, the uptake of HPV vaccine among KA adolescents remains suboptimal. Hence, we set out to explore knowledge, perceptions, and decision-making about HPV vaccination among KA women. Methods We conducted four focus groups of 26 KA women who participated in a community-based randomized controlled trial to promote breast and cervical cancer screening. Focus group data were analyzed using qualitative content analysis. Results Four main themes emerged from the focus groups: (1) limited awareness and knowledge of HPV vaccine, (2) perceptions and beliefs about HPV vaccination (acceptance, negative perceptions, ambivalence), (3) patterns of decision-making about HPV vaccination (hierarchical, peer-influenced, autonomous, and collaborative), and (4) promoting HPV education and information-sharing in the Korean community. Conclusion KA women are generally favorable toward HPV vaccination but lack awareness and knowledge about HPV. Culturally tailored HPV education programs based on KA women’s decision-making patterns and effective information-sharing by trustworthy sources in comfortable environments are suggested strategies to promote HPV vaccination in the KA community. The findings point to the need for a multi-level approach to addressing linguistic, cultural, and system barriers that the recent immigrant community faces in promoting HPV vaccinations. In the development of targeted interventions for KA women, educational strategies and patterns of decision-making need to be considered. PMID:25747518

What is adaptive about adaptive decision making? A parallel constraint satisfaction account.

PubMed

Glöckner, Andreas; Hilbig, Benjamin E; Jekel, Marc

2014-12-01

There is broad consensus that human cognition is adaptive. However, the vital question of how exactly this adaptivity is achieved has remained largely open. Herein, we contrast two frameworks which account for adaptive decision making, namely broad and general single-mechanism accounts vs. multi-strategy accounts. We propose and fully specify a single-mechanism model for decision making based on parallel constraint satisfaction processes (PCS-DM) and contrast it theoretically and empirically against a multi-strategy account. To achieve sufficiently sensitive tests, we rely on a multiple-measure methodology including choice, reaction time, and confidence data as well as eye-tracking. Results show that manipulating the environmental structure produces clear adaptive shifts in choice patterns - as both frameworks would predict. However, results on the process level (reaction time, confidence), in information acquisition (eye-tracking), and from cross-predicting choice consistently corroborate single-mechanisms accounts in general, and the proposed parallel constraint satisfaction model for decision making in particular. Copyright © 2014 Elsevier B.V. All rights reserved.

A fuzzy multi-objective linear programming approach for integrated sheep farming and wildlife in land management decisions: a case study in the Patagonian rangelands

NASA Astrophysics Data System (ADS)

Metternicht, Graciela; Blanco, Paula; del Valle, Hector; Laterra, Pedro; Hardtke, Leonardo; Bouza, Pablo

2015-04-01

Wildlife is part of the Patagonian rangelands sheep farming environment, with the potential of providing extra revenue to livestock owners. As sheep farming became less profitable, farmers and ranchers could focus on sustainable wildlife harvesting. It has been argued that sustainable wildlife harvesting is ecologically one of the most rational forms of land use because of its potential to provide multiple products of high value, while reducing pressure on ecosystems. The guanaco (Lama guanicoe) is the most conspicuous wild ungulate of Patagonia. Guanaco ?bre, meat, pelts and hides are economically valuable and have the potential to be used within the present Patagonian context of production systems. Guanaco populations in South America, including Patagonia, have experienced a sustained decline. Causes for this decline are related to habitat alteration, competition for forage with sheep, and lack of reasonable management plans to develop livelihoods for ranchers. In this study we propose an approach to explicitly determinate optimal stocking rates based on trade-offs between guanaco density and livestock grazing intensity on rangelands. The focus of our research is on finding optimal sheep stocking rates at paddock level, to ensure the highest production outputs while: a) meeting requirements of sustainable conservation of guanacos over their minimum viable population; b) maximizing soil carbon sequestration, and c) minimizing soil erosion. In this way, determination of optimal stocking rate in rangelands becomes a multi-objective optimization problem that can be addressed using a Fuzzy Multi-Objective Linear Programming (MOLP) approach. Basically, this approach converts multi-objective problems into single-objective optimizations, by introducing a set of objective weights. Objectives are represented using fuzzy set theory and fuzzy memberships, enabling each objective function to adopt a value between 0 and 1. Each objective function indicates the satisfaction of the decision maker towards the respective objective. Fuzzy logic is closer to intuitive thinking used by decision makers, making it a user-friendly approach for them to select alternatives. The proposed approach was applied in a study area of approximately 40,000 hectares in semiarid Patagonian rangelands where extensive, continuous sheep grazing for wool production is the main land use. Multi- and hyper-spectral data were combined with ancillary data within a GIS environment, and used to derive maps of forage production, guanacos density, soil organic carbon and soil erosion. Different scenarios, with different objectives weights were evaluated. Results showed that under scenario 1, where livestock production is predicted to have the highest values, guanaco numbers decrease substantially as well as soil carbon sequestration, and soil erosion exhibit the highest values. On the other hand, when guanaco population is prioritized, livestock production has the lowest value. A compromise alternative resulted from a scenario where variables are assigned same weight; under this condition, high livestock production is predicted, while conservation of guanaco population is sustainable, carbon sequestration is maximized and soil erosion minimized.

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

DTIC Science & Technology

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement...learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable...shall be subject to any oenalty for failing to comply with a collection of information if it does not display a currently valid OMB control number

The Rational Patient and Beyond: Implications for Treatment Adherence in People with Psychiatric Disabilities

PubMed Central

Corrigan, Patrick W.; Rüsch, Nicolas; Ben-Zeev, Dror; Sher, Tamara

2014-01-01

Purpose/Objective Many people with psychiatric disabilities do not benefit from evidence-based practices because they often do not seek out or fully adhere to them. One way psychologists have made sense of this rehabilitation and health decision process and subsequent behaviors (of which adherence might be viewed as one) is by proposing a “rational patient;” namely, that decisions are made deliberatively by weighing perceived costs and benefits of intervention options. Social psychological research, however, suggests limitations to a rational patient theory that impact models of health decision making. Design The research literature was reviewed for studies of rational patient models and alternative theories with empirical support. Special focus was on models specifically related to decisions about rehabilitation strategies for psychiatric disability. Results Notions of the rational patient evolved out of several psychological models including the health belief model, protection motivation theory, and theory of planned behavior. A variety of practice strategies evolved to promote rational decision making. However, research also suggests limitations to rational deliberations of health. (1) Rather than carefully and consciously considered, many health decisions are implicit, potentially occurring outside awareness. (2) Decisions are not always planful; often it is the immediate exigencies of a context rather than an earlier balance of costs and benefits that has the greatest effects. (3) Cool cognitions often do not dictate the process; emotional factors have an important role in health decisions. Each of these limitations suggests additional practice strategies that facilitate a person’s health decisions. Conclusions/Implications Old models of rational decision making need to be supplanted by multi-process models that explain supra-deliberative factors in health decisions and behaviors. PMID:24446671

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

Iowa pavement asset management decision-making framework.

DOT National Transportation Integrated Search

2015-10-01

Most local agencies in Iowa currently make their pavement treatment decisions based on their limited experience due primarily to : lack of a systematic decision-making framework and a decision-aid tool. The lack of objective condition assessment data...

Balancing emotion and cognition: a case for decision aiding in conservation efforts.

PubMed

Wilson, Robyn S

2008-12-01

Despite advances in the quality of participatory decision making for conservation, many current efforts still suffer from an inability to bridge the gap between science and policy. Judgment and decision-making research suggests this gap may result from a person's reliance on affect-based shortcuts in complex decision contexts. I examined the results from 3 experiments that demonstrate how affect (i.e., the instantaneous reaction one has to a stimulus) influences individual judgments in these contexts and identified techniques from the decision-aiding literature that help encourage a balance between affect-based emotion and cognition in complex decision processes. In the first study, subjects displayed a lack of focus on their stated conservation objectives and made decisions that reflected their initial affective impressions. Value-focused approaches may help individuals incorporate all the decision-relevant objectives by making the technical and value-based objectives more salient. In the second study, subjects displayed a lack of focus on statistical risk and again made affect-based decisions. Trade-off techniques may help individuals incorporate relevant technical data, even when it conflicts with their initial affective impressions or other value-based objectives. In the third study, subjects displayed a lack of trust in decision-making authorities when the decision involved a negatively affect-rich outcome (i.e., a loss). Identifying shared salient values and increasing procedural fairness may help build social trust in both decision-making authorities and the decision process.

Deciding how to decide: ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making.

PubMed

Fellows, Lesley K

2006-04-01

Ventromedial frontal lobe (VMF) damage is associated with impaired decision making. Recent efforts to understand the functions of this brain region have focused on its role in tracking reward, punishment and risk. However, decision making is complex, and frontal lobe damage might be expected to affect it at other levels. This study used process-tracing techniques to explore the effect of VMF damage on multi-attribute decision making under certainty. Thirteen subjects with focal VMF damage were compared with 11 subjects with frontal damage that spared the VMF and 21 demographically matched healthy control subjects. Participants chose rental apartments in a standard information board task drawn from the literature on normal decision making. VMF subjects performed the decision making task in a way that differed markedly from all other groups, favouring an 'alternative-based' information acquisition strategy (i.e. they organized their information search around individual apartments). In contrast, both healthy control subjects and subjects with damage predominantly involving dorsal and/or lateral prefrontal cortex pursued primarily 'attribute-based' search strategies (in which information was acquired about categories such as rent and noise level across several apartments). This difference in the pattern of information acquisition argues for systematic differences in the underlying decision heuristics and strategies employed by subjects with VMF damage, which in turn may affect the quality of their choices. These findings suggest that the processes supported by ventral and medial prefrontal cortex need to be conceptualized more broadly, to account for changes in decision making under conditions of certainty, as well as uncertainty, following damage to these areas.

Nicotine replacement therapy decision based on fuzzy multi-criteria analysis

NASA Astrophysics Data System (ADS)

Tarmudi, Zamali; Matmali, Norfazillah; Abdullah, Mohd Lazim

2017-08-01

It has been observed that Nicotine Replacement Therapy (NRT) is one of the alternatives to control and reduce smoking addiction among smokers. Since the decision to choose the best NRT alternative involves uncertainty, ambiguity factors and diverse input datasets, thus, this paper proposes a fuzzy multi-criteria analysis (FMA) to overcome these issues. It focuses on how the fuzzy approach can unify the diversity of datasets based on NRT's decision-making problem. The analysis done employed the advantage of the cost-benefit criterion to unify the mixture of dataset input. The performance matrix was utilised to derive the performance scores. An empirical example regarding the NRT's decision-making problem was employed to illustrate the proposed approach. Based on the calculations, this analytical approach was found to be highly beneficial in terms of usability. It was also very applicable and efficient in dealing with the mixture of input datasets. Hence, the decision-making process can easily be used by experts and patients who are interested to join the therapy/cessation program.

Patchy 'coherence': using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC).

PubMed

Lloyd, Amy; Joseph-Williams, Natalie; Edwards, Adrian; Rix, Andrew; Elwyn, Glyn

2013-09-05

Implementing shared decision making into routine practice is proving difficult, despite considerable interest from policy-makers, and is far more complex than merely making decision support interventions available to patients. Few have reported successful implementation beyond research studies. MAking Good Decisions In Collaboration (MAGIC) is a multi-faceted implementation program, commissioned by The Health Foundation (UK), to examine how best to put shared decision making into routine practice. In this paper, we investigate healthcare professionals' perspectives on implementing shared decision making during the MAGIC program, to examine the work required to implement shared decision making and to inform future efforts. The MAGIC program approached implementation of shared decision making by initiating a range of interventions including: providing workshops; facilitating development of brief decision support tools (Option Grids); initiating a patient activation campaign ('Ask 3 Questions'); gathering feedback using Decision Quality Measures; providing clinical leads meetings, learning events, and feedback sessions; and obtaining executive board level support. At 9 and 15 months (May and November 2011), two rounds of semi-structured interviews were conducted with healthcare professionals in three secondary care teams to explore views on the impact of these interventions. Interview data were coded by two reviewers using a framework derived from the Normalization Process Theory. A total of 54 interviews were completed with 31 healthcare professionals. Partial implementation of shared decision making could be explained using the four components of the Normalization Process Theory: 'coherence,' 'cognitive participation,' 'collective action,' and 'reflexive monitoring.' Shared decision making was integrated into routine practice when clinical teams shared coherent views of role and purpose ('coherence'). Shared decision making was facilitated when teams engaged in developing and delivering interventions ('cognitive participation'), and when those interventions fit with existing skill sets and organizational priorities ('collective action') resulting in demonstrable improvements to practice ('reflexive monitoring'). The implementation process uncovered diverse and conflicting attitudes toward shared decision making; 'coherence' was often missing. The study showed that implementation of shared decision making is more complex than the delivery of patient decision support interventions to patients, a portrayal that often goes unquestioned. Normalizing shared decision making requires intensive work to ensure teams have a shared understanding of the purpose of involving patients in decisions, and undergo the attitudinal shifts that many health professionals feel are required when comprehension goes beyond initial interpretations. Divergent views on the value of engaging patients in decisions remain a significant barrier to implementation.

Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC)

PubMed Central

2013-01-01

Background Implementing shared decision making into routine practice is proving difficult, despite considerable interest from policy-makers, and is far more complex than merely making decision support interventions available to patients. Few have reported successful implementation beyond research studies. MAking Good Decisions In Collaboration (MAGIC) is a multi-faceted implementation program, commissioned by The Health Foundation (UK), to examine how best to put shared decision making into routine practice. In this paper, we investigate healthcare professionals’ perspectives on implementing shared decision making during the MAGIC program, to examine the work required to implement shared decision making and to inform future efforts. Methods The MAGIC program approached implementation of shared decision making by initiating a range of interventions including: providing workshops; facilitating development of brief decision support tools (Option Grids); initiating a patient activation campaign (‘Ask 3 Questions’); gathering feedback using Decision Quality Measures; providing clinical leads meetings, learning events, and feedback sessions; and obtaining executive board level support. At 9 and 15 months (May and November 2011), two rounds of semi-structured interviews were conducted with healthcare professionals in three secondary care teams to explore views on the impact of these interventions. Interview data were coded by two reviewers using a framework derived from the Normalization Process Theory. Results A total of 54 interviews were completed with 31 healthcare professionals. Partial implementation of shared decision making could be explained using the four components of the Normalization Process Theory: ‘coherence,’ ‘cognitive participation,’ ‘collective action,’ and ‘reflexive monitoring.’ Shared decision making was integrated into routine practice when clinical teams shared coherent views of role and purpose (‘coherence’). Shared decision making was facilitated when teams engaged in developing and delivering interventions (‘cognitive participation’), and when those interventions fit with existing skill sets and organizational priorities (‘collective action’) resulting in demonstrable improvements to practice (‘reflexive monitoring’). The implementation process uncovered diverse and conflicting attitudes toward shared decision making; ‘coherence’ was often missing. Conclusions The study showed that implementation of shared decision making is more complex than the delivery of patient decision support interventions to patients, a portrayal that often goes unquestioned. Normalizing shared decision making requires intensive work to ensure teams have a shared understanding of the purpose of involving patients in decisions, and undergo the attitudinal shifts that many health professionals feel are required when comprehension goes beyond initial interpretations. Divergent views on the value of engaging patients in decisions remain a significant barrier to implementation. PMID:24006959

Moving towards ecosystem-based fisheries management: Options for parameterizing multi-species biological reference points

NASA Astrophysics Data System (ADS)

Moffitt, Elizabeth A.; Punt, André E.; Holsman, Kirstin; Aydin, Kerim Y.; Ianelli, James N.; Ortiz, Ivonne

2016-12-01

Multi-species models can improve our understanding of the effects of fishing so that it is possible to make informed and transparent decisions regarding fishery impacts. Broad application of multi-species assessment models to support ecosystem-based fisheries management (EBFM) requires the development and testing of multi-species biological reference points (MBRPs) for use in harvest-control rules. We outline and contrast several possible MBRPs that range from those that can be readily used in current frameworks to those belonging to a broader EBFM context. We demonstrate each of the possible MBRPs using a simple two species model, motivated by walleye pollock (Gadus chalcogrammus) and Pacific cod (Gadus macrocephalus) in the eastern Bering Sea, to illustrate differences among methods. The MBRPs we outline each differ in how they approach the multiple, potentially conflicting management objectives and trade-offs of EBFM. These options for MBRPs allow multi-species models to be readily adapted for EBFM across a diversity of management mandates and approaches.

A Multi-Objective Optimization Technique to Model the Pareto Front of Organic Dielectric Polymers

NASA Astrophysics Data System (ADS)

Gubernatis, J. E.; Mannodi-Kanakkithodi, A.; Ramprasad, R.; Pilania, G.; Lookman, T.

Multi-objective optimization is an area of decision making that is concerned with mathematical optimization problems involving more than one objective simultaneously. Here we describe two new Monte Carlo methods for this type of optimization in the context of their application to the problem of designing polymers with more desirable dielectric and optical properties. We present results of applying these Monte Carlo methods to a two-objective problem (maximizing the total static band dielectric constant and energy gap) and a three objective problem (maximizing the ionic and electronic contributions to the static band dielectric constant and energy gap) of a 6-block organic polymer. Our objective functions were constructed from high throughput DFT calculations of 4-block polymers, following the method of Sharma et al., Nature Communications 5, 4845 (2014) and Mannodi-Kanakkithodi et al., Scientific Reports, submitted. Our high throughput and Monte Carlo methods of analysis extend to general N-block organic polymers. This work was supported in part by the LDRD DR program of the Los Alamos National Laboratory and in part by a Multidisciplinary University Research Initiative (MURI) Grant from the Office of Naval Research.

Strategic biopharmaceutical portfolio development: an analysis of constraint-induced implications.

PubMed

George, Edmund D; Farid, Suzanne S

2008-01-01

Optimizing the structure and development pathway of biopharmaceutical drug portfolios are core concerns to the developer that come with several attached complexities. These include strategic decisions for the choice of drugs, the scheduling of critical activities, and the possible involvement of third parties for development and manufacturing at various stages for each drug. Additional complexities that must be considered include the impact of making such decisions in an uncertain environment. Presented here is the development of a stochastic multi-objective optimization framework designed to address these issues. The framework harnesses the ability of Bayesian networks to characterize the probabilistic structure of superior decisions via machine learning and evolve them to multi-objective optimality. Case studies that entailed three- and five-drug portfolios alongside a range of cash flow constraints were constructed to derive insight from the framework where results demonstrate that a variety of options exist for formulating nondominated strategies in the objective space considered, giving the manufacturer a range of pursuable options. In all cases limitations on cash flow reduce the potential for generating profits for a given probability of success. For the sizes of portfolio considered, results suggest that naïvely applying strategies optimal for a particular size of portfolio to a portfolio of another size is inappropriate. For the five-drug portfolio the most preferred means for development across the set of optimized strategies is to fully integrate development and commercial activities in-house. For the three-drug portfolio, the preferred means of development involves a mixture of in-house, outsourced, and partnered activities. Also, the size of the portfolio appears to have a larger impact on strategy and the quality of objectives than the magnitude of cash flow constraint.

ASSESSING THE EFFECTS OF DICHLOROACETIC ACID (DCA) USING A MULTI-ENDPOINT MEDAKA ASSAY

EPA Science Inventory

In regulating the safety of water, EPA makes decisions on what chemical contaminants to regulate and at what levels. To make these decisions, the EPA needs hazard identification and dose-response information. Current rodent methods for generating required information have limita...

TESTING MULTI-CRITERIA DECISION ANALYSIS FOR MORE TRANSPARENT RESOURCE-ALLOCATION DECISION MAKING IN COLOMBIA.

PubMed

Castro Jaramillo, Hector Eduardo; Goetghebeur, Mireille; Moreno-Mattar, Ornella

2016-01-01

In 2012, Colombia experienced an important institutional transformation after the establishment of the Health Technology Assessment Institute (IETS), the disbandment of the Regulatory Commission for Health and the reassignment of reimbursement decision-making powers to the Ministry of Health and Social Protection (MoHSP). These dynamic changes provided the opportunity to test Multi-Criteria Decision Analysis (MCDA) for systematic and more transparent resource-allocation decision-making. During 2012 and 2013, the MCDA framework Evidence and Value: Impact on Decision Making (EVIDEM) was tested in Colombia. This consisted of a preparatory stage in which the investigators conducted literature searches and produced HTA reports for four interventions of interest, followed by a panel session with decision makers. This method was contrasted with a current approach used in Colombia for updating the publicly financed benefits package (POS), where narrative health technology assessment (HTA) reports are presented alongside comprehensive budget impact analyses (BIAs). Disease severity, size of population, and efficacy ranked at the top among fifteen preselected relevant criteria. MCDA estimates of technologies of interest ranged between 71 to 90 percent of maximum value. The ranking of technologies was sensitive to the methods used. Participants considered that a two-step approach including an MCDA template, complemented by a detailed BIA would be the best approach to assist decision-making in this context. Participants agreed that systematic priority setting should take place in Colombia. This work may serve as the basis to the MoHSP on its interest of setting up a systematic and more transparent process for resource-allocation decision-making.

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.

A priori discretization error metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar

2016-12-01

Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under candidate discretization schemes validate the strong correlation between the proposed discretization error metrics and hydrologic simulation responses. Discretization decision-making results show that the common and convenient approach of making uniform discretization decisions across the watershed performs worse than the proposed non-uniform discretization approach in terms of preserving spatial heterogeneity under the same computational cost.

Uncertainty analysis for effluent trading planning using a Bayesian estimation-based simulation-optimization modeling approach.

PubMed

Zhang, J L; Li, Y P; Huang, G H; Baetz, B W; Liu, J

2017-06-01

In this study, a Bayesian estimation-based simulation-optimization modeling approach (BESMA) is developed for identifying effluent trading strategies. BESMA incorporates nutrient fate modeling with soil and water assessment tool (SWAT), Bayesian estimation, and probabilistic-possibilistic interval programming with fuzzy random coefficients (PPI-FRC) within a general framework. Based on the water quality protocols provided by SWAT, posterior distributions of parameters can be analyzed through Bayesian estimation; stochastic characteristic of nutrient loading can be investigated which provides the inputs for the decision making. PPI-FRC can address multiple uncertainties in the form of intervals with fuzzy random boundaries and the associated system risk through incorporating the concept of possibility and necessity measures. The possibility and necessity measures are suitable for optimistic and pessimistic decision making, respectively. BESMA is applied to a real case of effluent trading planning in the Xiangxihe watershed, China. A number of decision alternatives can be obtained under different trading ratios and treatment rates. The results can not only facilitate identification of optimal effluent-trading schemes, but also gain insight into the effects of trading ratio and treatment rate on decision making. The results also reveal that decision maker's preference towards risk would affect decision alternatives on trading scheme as well as system benefit. Compared with the conventional optimization methods, it is proved that BESMA is advantageous in (i) dealing with multiple uncertainties associated with randomness and fuzziness in effluent-trading planning within a multi-source, multi-reach and multi-period context; (ii) reflecting uncertainties existing in nutrient transport behaviors to improve the accuracy in water quality prediction; and (iii) supporting pessimistic and optimistic decision making for effluent trading as well as promoting diversity of decision alternatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of land suitability for olive mill wastewater disposal site selection by integrating fuzzy logic, AHP, and WLC in a GIS.

PubMed

Aydi, Abdelwaheb; Abichou, Tarek; Nasr, Imen Hamdi; Louati, Mourad; Zairi, Moncef

2016-01-01

This paper presents a geographic information system-based multi-criteria site selection tool of an olive mill wastewater (OMW) disposal site in Sidi Bouzid Region, Tunisia. The multi-criteria decision framework integrates ten constraints and six factors that relate to environmental and economic concerns, and builds a hierarchy model for OMW disposal site suitability. The methodology is used for preliminary assessment of the most suitable OMW disposal sites by combining fuzzy set theory and analytic hierarchy process (AHP). The fuzzy set theory is used to standardize factors using different fuzzy membership functions while the AHP is used to establish the relative importance of the criteria. The AHP makes pairwise comparisons of relative importance between hierarchy elements grouped by both environmental and economic decision criteria. The OMW disposal site suitability is achieved by applying a weighted linear combination that uses a comparison matrix to aggregate different importance scenarios associated with environmental and economic objectives. Three different scenarios generated by different weights applied to the two objectives. The scenario (a) assigns a weight of 0.75 to the environmental and 0.25 to the economic objective, scenario (b) has equal weights, and scenario (c) features weights of 0.25 and 0.75 for environmental and economic objectives, respectively. The results from this study assign the least suitable OMW disposal site of 2.5 % when environmental and economic objectives are rated equally, while a more suitable OMW disposal site of 1.0 % is generated when the economic objective is rated higher.

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.

Healthcare managers' decision making: findings of a small scale exploratory study.

PubMed

Macdonald, Jackie; Bath, Peter A; Booth, Andrew

2008-12-01

Managers who work in publicly funded healthcare organizations are an understudied group. Some of the influences on their decisions may be unique to healthcare. This study considers how to integrate research knowledge effectively into healthcare managers' decision making, and how to manage and integrate information that will include community data. This first phase in a two-phase mixed methods research study used a qualitative, multiple case studies design. Nineteen semi-structured interviews were undertaken using the critical incident technique. Interview transcripts were analysed using the NatCen Framework. One theme represented ;information and decisions'. Cases were determined to involve complex multi-level, multi-situational decisions with participants in practical rather than ceremonial work roles. Most considered organizational knowledge in the first two decision phases and external knowledge, including research, in the third phase. All participants engaged in satisficing to some degree.

Decision Making Under Uncertainty

DTIC Science & Technology

2010-11-01

A sound approach to rational decision making requires a decision maker to establish decision objectives, identify alternatives, and evaluate those...often violate the axioms of rationality when making decisions under uncertainty. The systematic description of such observations may lead to the...which leads to “anchoring” on the initial value. The fact that individuals have been shown to deviate from rationality when making decisions

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.

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

PubMed

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Two Validated Ways of Improving the Ability of Decision-Making in Emergencies; Results from a Literature Review

PubMed Central

Khorram-Manesh, Amir; Berlin, Johan; Carlström, Eric

2016-01-01

The aim of the current review wasto study the existing knowledge about decision-making and to identify and describe validated training tools.A comprehensive literature review was conducted by using the following keywords: decision-making, emergencies, disasters, crisis management, training, exercises, simulation, validated, real-time, command and control, communication, collaboration, and multi-disciplinary in combination or as an isolated word. Two validated training systems developed in Sweden, 3 level collaboration (3LC) and MacSim, were identified and studied in light of the literature review in order to identify how decision-making can be trained. The training models fulfilled six of the eight identified characteristics of training for decision-making.Based on the results, these training models contained methods suitable to train for decision-making. PMID:27878123

Application of construal level and value-belief norm theories to undergraduate decision-making on a wildlife socio-scientific issue

NASA Astrophysics Data System (ADS)

Sutter, A. McKinzie; Dauer, Jenny M.; Forbes, Cory T.

2018-06-01

One aim of science education is to develop scientific literacy for decision-making in daily life. Socio-scientific issues (SSI) and structured decision-making frameworks can help students reach these objectives. This research uses value belief norm (VBN) theory and construal level theory (CLT) to explore students' use of personal values in their decision-making processes and the relationship between abstract and concrete problematization and their decision-making. Using mixed methods, we conclude that the level of abstraction with which students problematise a prairie dog agricultural production and ecosystem preservation issue has a significant relationship to the values students used in the decision-making process. However, neither abstraction of the problem statement nor students' surveyed value orientations were significantly related to students' final decisions. These results may help inform teachers' understanding of students and their use of a structured-decision making tool in a classroom, and aid researchers in understanding if these tools help students remain objective in their analyses of complex SSIs.

Impaired Decision Making in Adolescent Suicide Attempters

ERIC Educational Resources Information Center

Bridge, Jeffrey A.; McBee-Strayer, Sandra M.; Cannon, Elizabeth A.; Sheftall, Arielle H.; Reynolds, Brady; Campo, John V.; Pajer, Kathleen A.; Barbe, Remy P.; Brent, David A.

2012-01-01

Objective: Decision-making deficits have been linked to suicidal behavior in adults. However, it remains unclear whether impaired decision making plays a role in the etiopathogenesis of youth suicidal behavior. The purpose of this study was to examine decision-making processes in adolescent suicide attempters and never-suicidal comparison…

Development of a support tool for complex decision-making in the provision of rural maternity care.

PubMed

Hearns, Glen; Klein, Michael C; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-02-01

Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology.

Multi-objective optimization of riparian buffer networks; valuing present and future benefits

EPA Science Inventory

Multi-objective optimization has emerged as a popular approach to support water resources planning and management. This approach provides decision-makers with a suite of management options which are generated based on metrics that represent different social, economic, and environ...

Battling Arrow's Paradox to Discover Robust Water Management Alternatives

NASA Astrophysics Data System (ADS)

Kasprzyk, J. R.; Reed, P. M.; Hadka, D.

2013-12-01

This study explores whether or not Arrow's Impossibility Theorem, a theory of social choice, affects the formulation of water resources systems planning problems. The theorem discusses creating an aggregation function for voters choosing from more than three alternatives for society. The Impossibility Theorem is also called Arrow's Paradox, because when trying to add more voters, a single individual's preference will dictate the optimal group decision. In the context of water resources planning, our study is motivated by recent theoretical work that has generalized the insights for Arrow's Paradox to the design of complex engineered systems. In this framing of the paradox, states of society are equivalent to water planning or design alternatives, and the voters are equivalent to multiple planning objectives (e.g. minimizing cost or maximizing performance). Seen from this point of view, multi-objective water planning problems are functionally equivalent to the social choice problem described above. Traditional solutions to such multi-objective problems aggregate multiple performance measures into a single mathematical objective. The Theorem implies that a subset of performance concerns will inadvertently dictate the overall design evaluations in unpredictable ways using such an aggregation. We suggest that instead of aggregation, an explicit many-objective approach to water planning can help overcome the challenges posed by Arrow's Paradox. Many-objective planning explicitly disaggregates measures of performance while supporting the discovery of the planning tradeoffs, employing multiobjective evolutionary algorithms (MOEAs) to find solutions. Using MOEA-based search to address Arrow's Paradox requires that the MOEAs perform robustly with increasing problem complexity, such as adding additional objectives and/or decisions. This study uses comprehensive diagnostic evaluation of MOEA search performance across multiple problem formulations (both aggregated and many-objective) to show whether or not aggregating performance measures biases decision making. In this study, we explore this hypothesis using an urban water portfolio management case study in the Lower Rio Grande Valley. The diagnostic analysis shows that modern self-adaptive MOEA search is efficient, effective, and reliable for the more complex many-objective LRGV planning formulations. Results indicate that although many classical water systems planning frameworks seek to account for multiple objectives, the common practice of reducing the problem into one or more highly aggregated performance measures can severely and negatively bias planning decisions.

Using structured decision making with landowners to address private forest management and parcelization: balancing multiple objectives and incorporating uncertainty

Treesearch

Paige F. B. Ferguson; Michael J. Conroy; John F. Chamblee; Jeffrey Hepinstall-Cymerman

2015-01-01

Parcelization and forest fragmentation are of concern for ecological, economic, and social reasons. Efforts to keep large, private forests intact may be supported by a decision-making process that incorporates landowners’ objectives and uncertainty. We used structured decision making (SDM) with owners of large, private forests in Macon County, North Carolina....

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.

Consensus oriented fuzzified decision support for oil spill contingency management.

PubMed

Liu, Xin; Wirtz, Kai W

2006-06-30

Studies on multi-group multi-criteria decision-making problems for oil spill contingency management are in their infancy. This paper presents a second-order fuzzy comprehensive evaluation (FCE) model to resolve decision-making problems in the area of contingency management after environmental disasters such as oil spills. To assess the performance of different oil combat strategies, second-order FCE allows for the utilization of lexical information, the consideration of ecological and socio-economic criteria and the involvement of a variety of stakeholders. On the other hand, the new approach can be validated by using internal and external checks, which refer to sensitivity tests regarding its internal setups and comparisons with other methods, respectively. Through a case study, the Pallas oil spill in the German Bight in 1998, it is demonstrated that this approach can help decision makers who search for an optimal strategy in multi-thread contingency problems and has a wider application potential in the field of integrated coastal zone management.

Real-Time Analysis of a Sensor's Data for Automated Decision Making in an IoT-Based Smart Home.

PubMed

Khan, Nida Saddaf; Ghani, Sayeed; Haider, Sajjad

2018-05-25

IoT devices frequently generate large volumes of streaming data and in order to take advantage of this data, their temporal patterns must be learned and identified. Streaming data analysis has become popular after being successfully used in many applications including forecasting electricity load, stock market prices, weather conditions, etc. Artificial Neural Networks (ANNs) have been successfully utilized in understanding the embedded interesting patterns/behaviors in the data and forecasting the future values based on it. One such pattern is modelled and learned in the present study to identify the occurrence of a specific pattern in a Water Management System (WMS). This prediction aids in making an automatic decision support system, to switch OFF a hydraulic suction pump at the appropriate time. Three types of ANN, namely Multi-Input Multi-Output (MIMO), Multi-Input Single-Output (MISO), and Recurrent Neural Network (RNN) have been compared, for multi-step-ahead forecasting, on a sensor's streaming data. Experiments have shown that RNN has the best performance among three models and based on its prediction, a system can be implemented to make the best decision with 86% accuracy.

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.

A Framework for Multi-Stakeholder Decision-Making and ...

EPA Pesticide Factsheets

This contribution describes the implementation of the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. It is observed that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as random variables. We thus shape the dissatisfaction distribution and find an optimal compromise solution by solving a CVaR minimization problem parameterized in the probability level. This enables us to generalize multi-stakeholder settings previously proposed in the literature that minimizes average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework. We demonstrate the framework in a bio-waste processing facility location case study, where we seek compromise solutions (facility locations) that balance stakeholder priorities on transportation, safety, water quality, and capital costs. This conference presentation abstract explains a new decision-making framework that computes compromise solution alternatives (reach consensus) by mitigating dissatisfactions among stakeholders as needed for SHC Decision Science and Support Tools project.

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.

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.

Shared Decision-Making in the Management of Congenital Vascular Malformations.

PubMed

Horbach, Sophie E R; Ubbink, Dirk T; Stubenrouch, Fabienne E; Koelemay, Mark J W; van der Vleuten, Carine J M; Verhoeven, Bas H; Reekers, Jim A; Schultze Kool, Leo J; van der Horst, Chantal M A M

2017-03-01

In shared decision-making, clinicians and patients arrive at a joint treatment decision, by incorporating best available evidence and the patients' personal values and preferences. Little is known about the role of shared decision-making in managing patients with congenital vascular malformations, for which preference-sensitive decision-making seems obvious. The authors investigated preferences regarding decision-making and current shared decision-making behavior during physician-patient encounters. In two Dutch university hospitals, adults and children with congenital vascular malformations facing a treatment-related decision were enrolled. Before the consultation, patients (or parents of children) expressed their preference regarding decision-making (Control Preferences Scale). Afterward, participants completed shared decision-making-specific questionnaires (nine-item Shared Decision-Making Questionnaire, CollaboRATE, and satisfaction), and physicians completed the Shared Decision-Making Questionnaire-Physician questionnaire. Consultations were audiotaped and patient involvement was scored by two independent researchers using the five-item Observing Patient Involvement instrument. All questionnaire results were expressed on a scale of 0 to 100 (optimum shared decision-making). Fifty-five participants (24 parents and 31 adult patients) were included. Two-thirds preferred the shared decision-making approach (Control Preferences Scale). Objective five-item Observing Patient Involvement scores were low (mean ± SD, 31 ± 15), whereas patient and physician Shared Decision-Making Questionnaire scores were high, with means of 68 ± 18 and 68 ± 19, respectively. The median CollaboRATE score was 93. There was no clear relationship between shared decision-making and satisfaction scores. Although adults and parents of children with vascular malformations express a strong desire for shared decision-making, objective shared decision-making behavior is still lacking, most likely because of poor awareness of the shared decision-making concept among patients, parents, and physicians. To improve shared decision-making practice, targeted interventions (e.g., decision aids, staff training) are essential.

Multi-Agent Many-Objective Robust Decision Making: Supporting Cooperative Regional Water Portfolio Planning in the Eastern United States

NASA Astrophysics Data System (ADS)

Herman, J. D.; Zeff, H. B.; Reed, P. M.; Characklis, G. W.

2013-12-01

In the Eastern United States, water infrastructure and institutional frameworks have evolved in a historically water-rich environment. However, large regional droughts over the past decade combined with continuing population growth have marked a transition to a state of water scarcity, for which current planning paradigms are ill-suited. Significant opportunities exist to improve the efficiency of water infrastructure via regional coordination, namely, regional 'portfolios' of water-related assets such as reservoirs, conveyance, conservation measures, and transfer agreements. Regional coordination offers the potential to improve reliability, cost, and environmental impact in the expected future state of the world, and, with informed planning, to improve robustness to future uncertainty. In support of this challenge, this study advances a multi-agent many-objective robust decision making (multi-agent MORDM) framework that blends novel computational search and uncertainty analysis tools to discover flexible, robust regional portfolios. Our multi-agent MORDM framework is demonstrated for four water utilities in the Research Triangle region of North Carolina, USA. The utilities supply nearly two million customers and have the ability to interact with one another via transfer agreements and shared infrastructure. We show that strategies for this region which are Pareto-optimal in the expected future state of the world remain vulnerable to performance degradation under alternative scenarios of deeply uncertain hydrologic and economic factors. We then apply the Patient Rule Induction Method (PRIM) to identify which of these uncertain factors drives the individual and collective vulnerabilities for the four cooperating utilities. Our results indicate that clear multi-agent tradeoffs emerge for attaining robustness across the utilities. Furthermore, the key factor identified for improving the robustness of the region's water supply is cooperative demand reduction. This type of approach is critically important given the risks and challenges posed by rising supply development costs, limits on new infrastructure, growing water demands and the underlying uncertainties associated with climate change. The proposed framework serves as a planning template for other historically water-rich regions which must now confront the reality of impending water scarcity.

Supporting multi-stakeholder environmental decisions.

PubMed

Hajkowicz, Stefan A

2008-09-01

This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.

Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

PubMed Central

2014-01-01

This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions). PMID:25152926

A Curriculum To Improve Decision-Making for School Psychologists.

ERIC Educational Resources Information Center

Davidow, Joseph R.

School psychologists are often asked to make significant decisions about students, but there has been a lack of research on how psychologists make such decisions. Obtaining the objective that school psychologists make sound decisions is an important goal, which involves training in how to minimize the adverse impact of predictable biases in human…

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.

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale

PubMed Central

Diao, Yuzhu; Hu, Aqin

2018-01-01

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation. PMID:29498699

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

PubMed

Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

2018-03-02

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

[Treatment Decision-Making Process of Cancer Patients].

PubMed

Lee, Shiu-Yu C Katie

2016-10-01

The decision-making process that is used by cancer patients to determine their treatment has become more multi-foci, difficult and complicated in recent years. This has in part been attributed to the increasing incidence rate of cancer in Taiwan and the rapid development of medical technologies and treatment modalities. Oncology nurses must assist patients and family to make informed and value-based treatment decisions. Decision-making is an information process that involves appraising one's own expectation and values based on his/her knowledge on cancer and treatment options. Because cancer treatment involves risks and uncertainties, and impacts quality of life, the treatment decision-making for cancer is often stressful, or even conflicting. This paper discusses the decision-making behaviors of cancer patients and the decisional conflict, participation, and informational needs that are involved in cancer treatment. The trend toward shared decision-making and decisional support will be also explored in order to facilitate the future development of appropriate clinical interventions and research.

Evaluating a Web-Based MMR Decision Aid to Support Informed Decision-Making by UK Parents: A Before-and-After Feasibility Study

ERIC Educational Resources Information Center

Jackson, Cath; Cheater, Francine M.; Peacock, Rose; Leask, Julie; Trevena, Lyndal

2010-01-01

Objective: The objective of this feasibility study was to evaluate the acceptability and potential effectiveness of a web-based MMR decision aid in supporting informed decision-making for the MMR vaccine. Design: This was a prospective before-and-after evaluation. Setting: Thirty parents of children eligible for MMR vaccination were recruited from…

Distinction between Externally vs. Internally Guided Decision-Making: Operational Differences, Meta-Analytical Comparisons and Their Theoretical Implications

PubMed Central

Nakao, Takashi; Ohira, Hideki; Northoff, Georg

2012-01-01

Most experimental studies of decision-making have specifically examined situations in which a single less-predictable correct answer exists (externally guided decision-making under uncertainty). Along with such externally guided decision-making, there are instances of decision-making in which no correct answer based on external circumstances is available for the subject (internally guided decision-making). Such decisions are usually made in the context of moral decision-making as well as in preference judgment, where the answer depends on the subject’s own, i.e., internal, preferences rather than on external, i.e., circumstantial, criteria. The neuronal and psychological mechanisms that allow guidance of decisions based on more internally oriented criteria in the absence of external ones remain unclear. This study was undertaken to compare decision-making of these two kinds empirically and theoretically. First, we reviewed studies of decision-making to clarify experimental–operational differences between externally guided and internally guided decision-making. Second, using multi-level kernel density analysis, a whole-brain-based quantitative meta-analysis of neuroimaging studies was performed. Our meta-analysis revealed that the neural network used predominantly for internally guided decision-making differs from that for externally guided decision-making under uncertainty. This result suggests that studying only externally guided decision-making under uncertainty is insufficient to account for decision-making processes in the brain. Finally, based on the review and results of the meta-analysis, we discuss the differences and relations between decision-making of these two types in terms of their operational, neuronal, and theoretical characteristics. PMID:22403525

Comparison of Multi-Criteria Decision Support Methods (AHP, TOPSIS, SAW & PROMENTHEE) for Employee Placement

NASA Astrophysics Data System (ADS)

Widianta, M. M. D.; Rizaldi, T.; Setyohadi, D. P. S.; Riskiawan, H. Y.

2018-01-01

The right decision in placing employees in an appropriate position in a company will support the quality of management and will have an impact on improving the quality of human resources of the company. Such decision-making can be assisted by an approach through the Decision Support System (DSS) to improve accuracy in the employee placement process. The purpose of this paper is to compare the four methods of Multi Criteria Decision Making (MCDM), ie Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Of Evaluations (PROMETHEE) for the application of employee placement in accordance with predetermined criteria. The ranking results and the accuracy level obtained from each method are different depending on the different scaling and weighting processes in each method.

Models of expert assessments and their study in problems of choice and decision-making in management of motor transport processes

NASA Astrophysics Data System (ADS)

Belokurov, V. P.; Belokurov, S. V.; Korablev, R. A.; Shtepa, A. A.

2018-05-01

The article deals with decision making concerning transport tasks on search iterations in the management of motor transport processes. An optimal selection of the best option for specific situations is suggested in the management of complex multi-criteria transport processes.

Putting Bandits into Context: How Function Learning Supports Decision Making

ERIC Educational Resources Information Center

Schulz, Eric; Konstantinidis, Emmanouil; Speekenbrink, Maarten

2018-01-01

The authors introduce the contextual multi-armed bandit task as a framework to investigate learning and decision making in uncertain environments. In this novel paradigm, participants repeatedly choose between multiple options in order to maximize their rewards. The options are described by a number of contextual features which are predictive of…

Decision Making for Pap Testing among Pacific Islander Women

ERIC Educational Resources Information Center

Weiss, Jie W.; Mouttapa, Michele; Sablan-Santos, Lola; DeGuzman Lacsamana, Jasmine; Quitugua, Lourdes; Park Tanjasiri, Sora

2016-01-01

This study employed a Multi-Attribute Utility (MAU) model to examine the Pap test decision-making process among Pacific Islanders (PI) residing in Southern California. A total of 585 PI women were recruited through social networks from Samoan and Tongan churches, and Chamorro family clans. A questionnaire assessed Pap test knowledge, beliefs and…

Integrating land cover modeling and adaptive management to conserve endangered species and reduce catastrophic fire risk

USGS Publications Warehouse

Breininger, David; Duncan, Brean; Eaton, Mitchell J.; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process, where science informs how management alternatives can influence resources, and then, decision makers can use this information to make decisions. A more efficient process is to directly integrate science and decision-making, where science allows us to learn in order to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by the specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuel monitoring with decision-making focused on the dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy; other conditions require tradeoffs between objectives. Knowledge about system responses to actions can be informed by developing hypotheses based on ideas about fire behavior and then applying competing management actions to different land units in the same system state. Monitoring and management integration is important to optimize state-specific management decisions and to increase knowledge about system responses. We believe this approach has broad utility and identifies a clear role for land cover modeling programs intended to inform decision-making.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

PubMed

Tučník, Petr; Bureš, Vladimír

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

Multi-criteria decision making in flood risk management: research progress and the challenge of handling uncertainty and stakeholder participation

NASA Astrophysics Data System (ADS)

Madruga de Brito, Mariana; Evers, Mariele

2016-04-01

Multi-Criteria Decision Making (MCDM) methods have received much attention from researchers and practitioners for solving flood risk management problems in the last decades due to its capacity to deal with multiple criteria, conflicting objectives as well as the knowledge arising from the participation of several actors. In order to consolidate recent research conducted in this area, this study presents a state-of-the-art literature review of MCDM applications to flood risk management, seeking to provide a better understanding of the current status of how participatory MCDM is being conducted and the way uncertainties are included in the decision-making process. Totally, 128 peer-reviewed papers published from 1995 to June 2015 in 72 different journals were systematically analyzed. Results indicated that the number of flood MCDM publications has exponentially grown during this period, with over 82% of all papers published since 2009. A wide range of application areas was identified, with most papers focusing on ranking alternatives for flood mitigation (22.78% of the total) followed by risk (21.11%) and vulnerability assessment (15%). The Analytical Hierarchy Process (AHP) was the most popular MCDM method (42.72%) followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) (13.33%) and Weighted Sum Method (WSM) (12.73%). Although significant improvements have been made over the last decades, shortcomings remain in handling the uncertainty. Only eight papers (6.25%) have conducted uncertainty analysis, suggesting that a general procedure for performing it in MCDM does not yet exist. Researchers have applied the Monte Carlo simulation, Taylor's series error propagation method or assessed the uncertainty in qualitative ways, by describing its main sources or analyzing the stakeholders' degree of confidence. In addition, 35 articles (27.34%) have performed a sensitivity analysis of the criteria weights. Three distinct approaches were identified: one-way, global, and probabilistic sensitivity analysis. About half of the studies have acknowledged the involvement of multiple stakeholders. However, participation was fragmented and focused on particular stages of the decision-making process such as the elicitation of criteria weights. This segmentation may be related to methodological and time constraints since participatory decision making is time-consuming and costly. Policy makers and experts were the most participated stakeholders, with few papers considering the involvement of local community members. Another issue is that only four studies seek to obtain consensus and that decisions were often made by majority vote or averaging approaches. Therefore, greater rigor in addressing the uncertainties around stakeholders' judgments as well as in endorsing an active participation in all stages of the decision-making process should be undertaken in future applications. This could help to increase the quality of decisions and subsequent implementation of chosen measures.

Decision Making in Liver Transplant Selection Committees

PubMed Central

Volk, Michael L; Biggins, Scott W; Huang, Mary Ann; Argo, Curtis K; Fontana, Robert J; Anspach, Renee R

2011-01-01

Background In order to receive a liver transplant, patients must first be placed on the waiting list – a decision made in most transplant centers by a multidisciplinary committee. The function of these committees has never been studied. Objectives To describe decision making in liver transplant committees and identify opportunities for process improvement. Design Observational multi-center Setting We observed 63 meetings and interviewed 50 committee members at 4 liver transplant centers. Study Subjects Transplant committee members. Measurements Recorded transcripts and field notes were analyzed using standard qualitative sociological methods. Results While the structure of meetings varied by center, the process was uniform and involved reviewing possible reasons for patient exclusion using primarily inductive reasoning. Stated justifications for excluding patients were a) too well, b) non-hepatic comorbidities or advanced age, c) too sick in the setting of advanced liver disease, d) substance abuse, or e) other psychosocial barriers. Dominant themes identified included members’ angst over deciding who lives and dies, a high correlation between psychosocial barriers to transplant and patients’ socioeconomic status, and the influence of external forces on decision making. Consistently identified barriers to effective group decision making were: 1) unwritten center policies, and 2) confusion regarding advocacy versus stewardship roles. Limitations The use of qualitative methods provides broad understanding but limits specific inferences. These four centers may not be reflective of every transplant center nationwide. Conclusion The difficult decisions made by these committees are reasonably consistent and always well-intentioned, but might be improved by more explicit written policies and clarifying roles. This process may help inform resource allocation in other areas of medicine. Primary funding source The Greenwall Foundation. PMID:22007044

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

NASA Technical Reports Server (NTRS)

Breininger, David; Duncan, Brean; Eaton, Mitchell; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process where science informs how management alternatives can influence resources and then decision makers can use this to make decisions. A more efficient process is to directly integrate science and decision making, where science allows us to learn to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuels monitoring with decision making focused on dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy, but habitat trajectories suggest tradeoffs. Knowledge about system responses to actions can be informed by applying competing management actions to different land units in the same system state and by ideas about fire behavior. Monitoring and management integration is important to optimize state-specific management decisions and increase knowledge about system responses. We believe this approach has broad utility for and cover modeling programs intended to inform decision making.

Capacity planning for electronic waste management facilities under uncertainty: multi-objective multi-time-step model development.

PubMed

Poonam Khanijo Ahluwalia; Nema, Arvind K

2011-07-01

Selection of optimum locations for locating new facilities and decision regarding capacities at the proposed facilities is a major concern for municipal authorities/managers. The decision as to whether a single facility is preferred over multiple facilities of smaller capacities would vary with varying priorities to cost and associated risks such as environmental or health risk or risk perceived by the society. Currently management of waste streams such as that of computer waste is being done using rudimentary practices and is flourishing as an unorganized sector, mainly as backyard workshops in many cities of developing nations such as India. Uncertainty in the quantification of computer waste generation is another major concern due to the informal setup of present computer waste management scenario. Hence, there is a need to simultaneously address uncertainty in waste generation quantities while analyzing the tradeoffs between cost and associated risks. The present study aimed to address the above-mentioned issues in a multi-time-step, multi-objective decision-support model, which can address multiple objectives of cost, environmental risk, socially perceived risk and health risk, while selecting the optimum configuration of existing and proposed facilities (location and capacities).

Reducing uncertainty about objective functions in adaptive management

USGS Publications Warehouse

Williams, B.K.

2012-01-01

This paper extends the uncertainty framework of adaptive management to include uncertainty about the objectives to be used in guiding decisions. Adaptive decision making typically assumes explicit and agreed-upon objectives for management, but allows for uncertainty as to the structure of the decision process that generates change through time. Yet it is not unusual for there to be uncertainty (or disagreement) about objectives, with different stakeholders expressing different views not only about resource responses to management but also about the appropriate management objectives. In this paper I extend the treatment of uncertainty in adaptive management, and describe a stochastic structure for the joint occurrence of uncertainty about objectives as well as models, and show how adaptive decision making and the assessment of post-decision monitoring data can be used to reduce uncertainties of both kinds. Different degrees of association between model and objective uncertainty lead to different patterns of learning about objectives. ?? 2011.

The Rational Adolescent: Strategic Information Processing during Decision Making Revealed by Eye Tracking.

PubMed

Kwak, Youngbin; Payne, John W; Cohen, Andrew L; Huettel, Scott A

2015-01-01

Adolescence is often viewed as a time of irrational, risky decision-making - despite adolescents' competence in other cognitive domains. In this study, we examined the strategies used by adolescents (N=30) and young adults (N=47) to resolve complex, multi-outcome economic gambles. Compared to adults, adolescents were more likely to make conservative, loss-minimizing choices consistent with economic models. Eye-tracking data showed that prior to decisions, adolescents acquired more information in a more thorough manner; that is, they engaged in a more analytic processing strategy indicative of trade-offs between decision variables. In contrast, young adults' decisions were more consistent with heuristics that simplified the decision problem, at the expense of analytic precision. Collectively, these results demonstrate a counter-intuitive developmental transition in economic decision making: adolescents' decisions are more consistent with rational-choice models, while young adults more readily engage task-appropriate heuristics.

The Rational Adolescent: Strategic Information Processing during Decision Making Revealed by Eye Tracking

PubMed Central

Kwak, Youngbin; Payne, John W.; Cohen, Andrew L.; Huettel, Scott A.

2015-01-01

Adolescence is often viewed as a time of irrational, risky decision-making – despite adolescents' competence in other cognitive domains. In this study, we examined the strategies used by adolescents (N=30) and young adults (N=47) to resolve complex, multi-outcome economic gambles. Compared to adults, adolescents were more likely to make conservative, loss-minimizing choices consistent with economic models. Eye-tracking data showed that prior to decisions, adolescents acquired more information in a more thorough manner; that is, they engaged in a more analytic processing strategy indicative of trade-offs between decision variables. In contrast, young adults' decisions were more consistent with heuristics that simplified the decision problem, at the expense of analytic precision. Collectively, these results demonstrate a counter-intuitive developmental transition in economic decision making: adolescents' decisions are more consistent with rational-choice models, while young adults more readily engage task-appropriate heuristics. PMID:26388664

The development of a multi-criteria decision analysis aid to help with contraceptive choices: My Contraception Tool.

PubMed

French, Rebecca S; Cowan, Frances M; Wellings, Kaye; Dowie, Jack

2014-04-01

My Contraception Tool (MCT) applies the principles of multi-criteria decision analysis to the choice of contraceptive method. Its purpose is to make the decision-making process transparent to the user and to suggest a method to them based on their own preferences. The contraceptive option that emerges as optimal from the analysis takes account of the probability of a range of outcomes and the relative weight ascribed to them by the user. The development of MCT was a collaborative project between London School of Hygiene & Tropical Medicine, Brook, FPA and Maldaba Ltd. MCT is available online via the Brook and FPA websites. In this article we describe MCT's development and how it works. Further work is needed to assess the impact it has on decision quality and contraceptive behaviour.

Evaluation of multiple muscle loads through multi-objective optimization with prediction of subjective satisfaction level: illustration by an application to handrail position for standing.

PubMed

Chihara, Takanori; Seo, Akihiko

2014-03-01

Proposed here is an evaluation of multiple muscle loads and a procedure for determining optimum solutions to ergonomic design problems. The simultaneous muscle load evaluation is formulated as a multi-objective optimization problem, and optimum solutions are obtained for each participant. In addition, one optimum solution for all participants, which is defined as the compromise solution, is also obtained. Moreover, the proposed method provides both objective and subjective information to support the decision making of designers. The proposed method was applied to the problem of designing the handrail position for the sit-to-stand movement. The height and distance of the handrails were the design variables, and surface electromyograms of four muscles were measured. The optimization results suggest that the proposed evaluation represents the impressions of participants more completely than an independent use of muscle loads. In addition, the compromise solution is determined, and the benefits of the proposed method are examined. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

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

Jin, Xin; Baker, Kyri A.; Christensen, Dane T.

This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility andmore » reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.« less

User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response

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

Jin, Xin; Baker, Kyri A; Isley, Steven C

This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility andmore » reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.« less

An object-relational model for structured representation of medical knowledge.

PubMed

Koch, S; Risch, T; Schneider, W; Wagner, I V

2006-07-01

Domain specific knowledge is often not static but continuously evolving. This is especially true for the medical domain. Furthermore, the lack of standardized structures for presenting knowledge makes it difficult or often impossible to assess new knowledge in the context of existing knowledge. Possibilities to compare knowledge easily and directly are often not given. It is therefore of utmost importance to create a model that allows for comparability, consistency and quality assurance of medical knowledge in specific work situations. For this purpose, we have designed on object-relational model based on structured knowledge elements that are dynamically reusable by different multi-media-based tools for case-based documentation, disease course simulation, and decision support. With this model, high-level components, such as patient case reports or simulations of the course of a disease, and low-level components (e.g., diagnoses, symptoms or treatments) as well as the relationships between these components are modeled. The resulting schema has been implemented in AMOS II, on object-relational multi-database system supporting different views with regard to search and analysis depending on different work situations.

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.

DRUG EVALUATION AND DECISION MAKING IN CATALONIA: DEVELOPMENT AND VALIDATION OF A METHODOLOGICAL FRAMEWORK BASED ON MULTI-CRITERIA DECISION ANALYSIS (MCDA) FOR ORPHAN DRUGS.

PubMed

Gilabert-Perramon, Antoni; Torrent-Farnell, Josep; Catalan, Arancha; Prat, Alba; Fontanet, Manel; Puig-Peiró, Ruth; Merino-Montero, Sandra; Khoury, Hanane; Goetghebeur, Mireille M; Badia, Xavier

2017-01-01

The aim of this study was to adapt and assess the value of a Multi-Criteria Decision Analysis (MCDA) framework (EVIDEM) for the evaluation of Orphan drugs in Catalonia (Catalan Health Service). The standard evaluation and decision-making procedures of CatSalut were compared with the EVIDEM methodology and contents. The EVIDEM framework was adapted to the Catalan context, focusing on the evaluation of Orphan drugs (PASFTAC program), during a Workshop with sixteen PASFTAC members. The criteria weighting was done using two different techniques (nonhierarchical and hierarchical). Reliability was assessed by re-test. The EVIDEM framework and methodology was found useful and feasible for Orphan drugs evaluation and decision making in Catalonia. All the criteria considered for the development of the CatSalut Technical Reports and decision making were considered in the framework. Nevertheless, the framework could improve the reporting of some of these criteria (i.e., "unmet needs" or "nonmedical costs"). Some Contextual criteria were removed (i.e., "Mandate and scope of healthcare system", "Environmental impact") or adapted ("population priorities and access") for CatSalut purposes. Independently of the weighting technique considered, the most important evaluation criteria identified for orphan drugs were: "disease severity", "unmet needs" and "comparative effectiveness", while the "size of the population" had the lowest relevance for decision making. Test-retest analysis showed weight consistency among techniques, supporting reliability overtime. MCDA (EVIDEM framework) could be a useful tool to complement the current evaluation methods of CatSalut, contributing to standardization and pragmatism, providing a method to tackle ethical dilemmas and facilitating discussions related to decision making.

76 FR 77300 - Alaska Federal Lands Long Range Transportation Plan

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-12

... of and actions for coordinated planning and decision making among federal land management agencies... consolidate efforts through long-term coordination in transportation planning and decision-making processes... implementing projects; facilitating objective decision making for the transportation system; and developing...

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review.

PubMed

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh; Sadiq, Rehan

2015-01-01

Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, and finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Structured approach to incidental take decision making

USGS Publications Warehouse

McGowan, Conor P.

2013-01-01

Decision making related to incidental take of endangered species under U.S. law lends itself well to a structured decision making approach. Incidental take is the permitted killing, harming, or harassing of a protected species under the law as long as that harm is incidental to an otherwise lawful activity and does not “reduce appreciably the probability of survival and recovery in the wild.” There has been inconsistency in the process used for determining incidental take allowances across species and across time for the same species, and structured decision making has been proposed to improve decision making. I use an example decision analysis to demonstrate the process and its applicability to incidental take decisions, even under significant demographic uncertainty and multiple, competing objectives. I define the example problem, present an objectives statement and a value function, use a simulation model to assess the consequences of a set of management actions, and evaluate the tradeoffs among the different actions. The approach results in transparent and repeatable decisions.

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review

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

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh

2015-01-15

Highlights: • We review Municipal Solid Waste Management studies with focus on multiple stakeholders. • We focus on studies with multi-criteria decision analysis methods and discover their trends. • Most studies do not offer solutions for situations where stakeholders compete for more benefits or have unequal voting powers. • Governments and experts are the most participated stakeholders and AHP is the most dominant method. - Abstract: Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, andmore » finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies.« less

Current Scientific Approaches to Decision Making in Complex Systems. 3. Volume 2. Conference Position Papers

DTIC Science & Technology

1980-01-01

Search: Traffic on a Multi- dimensional Structure R. i. Atkin, University of Essex, England b. Annex. Volume 3: Decision: Foundation and Practice Brian R...Gaines, University of Essex, England Volume 4: Competing Modes of Cognition and Communication in Simulated and Self-Reflective Systems Stein Braten... University of Oslo, Norway Volume 5: On the Spontaneous Emergence of Decision Making Constraints in Communicating Hierarchical Structure John S

A SMALL FISH MULTI-ENDPOINT BIOASSAY FOR ASSESSING THE EFFECTS OF WATER CONTAMINANTS PRESENT IN LOW CONCENTRATIONS: MEDAKA AND DICHLOROACETIC ACID

EPA Science Inventory

In regulating the safety of water under SDWA and the CWA, the EPA makes decisions on what chemical contaminants to regulate and at what levels. To make these decisions the EPA needs hazard identification and dose-response information. Current methods that rely on rodent models fo...

Decision Making Methods in Space Economics and Systems Engineering

NASA Technical Reports Server (NTRS)

Shishko, Robert

2006-01-01

This viewgraph presentation reviews various methods of decision making and the impact that they have on space economics and systems engineering. Some of the methods discussed are: Present Value and Internal Rate of Return (IRR); Cost-Benefit Analysis; Real Options; Cost-Effectiveness Analysis; Cost-Utility Analysis; Multi-Attribute Utility Theory (MAUT); and Analytic Hierarchy Process (AHP).

Concise evaluation of decision aids.

PubMed

Stalmeier, Peep F M; Roosmalen, Marielle S

2009-01-01

Decision aids purport to help patients make treatment related choices. Several instruments exist to evaluate decision aids. Our aim is to compare the responsiveness of several instruments. Two different decision aids were randomized in patients at high risk for breast and ovarian cancer. Treatment choices were between prophylactic surgery and screening. Effect sizes were calculated to compare the responsiveness of the measures. One decision aid was randomized in 390 women, the other in 91 ensuing mutation carriers. Three factors were identified related to Information, Well-being and Decision Making. Within each factor, single item measures were as responsive as multi-item measures. Four single items, 'the amount of information received for decision making,' 'strength of preference,' 'I weighed the pros and cons,' and 'General Health,' were adequately responsive to the decision aids. These items might be considered for inclusion in questionnaires to evaluate decision aids.

Counterfactual reasoning in surrogate decision making -- another look.

PubMed

Johansson, Mats; Broström, Linus

2011-06-01

Incompetent patients need to have someone else make decisions on their behalf. According to the Substituted Judgment Standard the surrogate decision maker ought to make the decision that the patient would have made, had he or she been competent. Objections have been raised against this traditional construal of the standard on the grounds that it involves flawed counterfactual reasoning, and amendments have been suggested within the framework of possible worlds semantics. The paper shows that while this approach may circumvent the alleged problem, the way it has so far been elaborated reflects insufficient understanding of the moral underpinnings of the idea of substituted judgment. Proper recognition of these moral underpinnings has potentially far-reaching implications for our normative assumptions about accuracy and objectivity in surrogate decision making.

40 CFR 25.3 - Policy and objectives.

Code of Federal Regulations, 2010 CFR

2010-07-01

... governmental and educational associations. (b) Public participation is that part of the decision-making process... the decision-making process, seeking input from and conducting dialogue with the public, assimilating... considered by the decision-making official. Disagreement on significant issues is to be expected among...

Multi-criteria decision analysis for waste management in Saharawi refugee camps

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

Garfi, M.; Tondelli, S.; Bonoli, A.

2009-10-15

The aim of this paper is to compare different waste management solutions in Saharawi refugee camps (Algeria) and to test the feasibility of a decision-making method developed to be applied in particular conditions in which environmental and social aspects must be considered. It is based on multi criteria analysis, and in particular on the analytic hierarchy process (AHP), a mathematical technique for multi-criteria decision making (Saaty, T.L., 1980. The Analytic Hierarchy Process. McGraw-Hill, New York, USA; Saaty, T.L., 1990. How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operational Research; Saaty, T.L., 1994. Decision Making for Leaders:more » The Analytic Hierarchy Process in a Complex World. RWS Publications, Pittsburgh, PA), and on participatory approach, focusing on local community's concerns. The research compares four different waste collection and management alternatives: waste collection by using three tipper trucks, disposal and burning in an open area; waste collection by using seven dumpers and disposal in a landfill; waste collection by using seven dumpers and three tipper trucks and disposal in a landfill; waste collection by using three tipper trucks and disposal in a landfill. The results show that the second and the third solutions provide better scenarios for waste management. Furthermore, the discussion of the results points out the multidisciplinarity of the approach, and the equilibrium between social, environmental and technical impacts. This is a very important aspect in a humanitarian and environmental project, confirming the appropriateness of the chosen method.« less

Multi-criteria decision analysis in environmental sciences: ten years of applications and trends.

PubMed

Huang, Ivy B; Keisler, Jeffrey; Linkov, Igor

2011-09-01

Decision-making in environmental projects requires consideration of trade-offs between socio-political, environmental, and economic impacts and is often complicated by various stakeholder views. Multi-criteria decision analysis (MCDA) emerged as a formal methodology to face available technical information and stakeholder values to support decisions in many fields and can be especially valuable in environmental decision making. This study reviews environmental applications of MCDA. Over 300 papers published between 2000 and 2009 reporting MCDA applications in the environmental field were identified through a series of queries in the Web of Science database. The papers were classified by their environmental application area, decision or intervention type. In addition, the papers were also classified by the MCDA methods used in the analysis (analytic hierarchy process, multi-attribute utility theory, and outranking). The results suggest that there is a significant growth in environmental applications of MCDA over the last decade across all environmental application areas. Multiple MCDA tools have been successfully used for environmental applications. Even though the use of the specific methods and tools varies in different application areas and geographic regions, our review of a few papers where several methods were used in parallel with the same problem indicates that recommended course of action does not vary significantly with the method applied. Published by Elsevier B.V.

Mission, Margin, and the Role of Consumer Governance in Decision-Making at Community Health Centers

PubMed Central

Wright, Brad; Martin, Graham P.

2017-01-01

Objective We explore the role of consumer trustees in decision-making as community health centers (CHCs) work to navigate the tension between pursuing their mission to provide primary care to all regardless of ability to pay and maintaining their limited finances. Methods We interviewed 30 trustees from 16 CHCs in 14 different states, asking extensively about decision-making processes at their CHC related to services and finances, as well as perceived advantages and disadvantages of consumer governance. Results Respondents described mission-dominant, margin-dominant, and balanced decision-making philosophies, and different decision-making pathways for service provision and finances. Consumer trustees were lauded for their role in informing the board of service quality and community needs, but criticized for being professionally unskilled and exhibiting a lack of objective decision-making. Conclusions While CHC boards do play a role in navigating the tension between mission and margin, executive directors and staff appear to be more influential. PMID:24858895

Choices, choices: the application of multi-criteria decision analysis to a food safety decision-making problem.

PubMed

Fazil, A; Rajic, A; Sanchez, J; McEwen, S

2008-11-01

In the food safety arena, the decision-making process can be especially difficult. Decision makers are often faced with social and fiscal pressures when attempting to identify an appropriate balance among several choices. Concurrently, policy and decision makers in microbial food safety are under increasing pressure to demonstrate that their policies and decisions are made using transparent and accountable processes. In this article, we present a multi-criteria decision analysis approach that can be used to address the problem of trying to select a food safety intervention while balancing various criteria. Criteria that are important when selecting an intervention were determined, as a result of an expert consultation, to include effectiveness, cost, weight of evidence, and practicality associated with the interventions. The multi-criteria decision analysis approach we present is able to consider these criteria and arrive at a ranking of interventions. It can also provide a clear justification for the ranking as well as demonstrate to stakeholders, through a scenario analysis approach, how to potentially converge toward common ground. While this article focuses on the problem of selecting food safety interventions, the range of applications in the food safety arena is truly diverse and can be a significant tool in assisting decisions that need to be coherent, transparent, and justifiable. Most importantly, it is a significant contributor when there is a need to strike a fine balance between various potentially competing alternatives and/or stakeholder groups.

Multi-criteria decision-making for flood risk management: a survey of the current state of the art

NASA Astrophysics Data System (ADS)

Madruga de Brito, Mariana; Evers, Mariele

2016-04-01

This paper provides a review of multi-criteria decision-making (MCDM) applications to flood risk management, seeking to highlight trends and identify research gaps. A total of 128 peer-reviewed papers published from 1995 to June 2015 were systematically analysed. Results showed that the number of flood MCDM publications has exponentially grown during this period, with over 82 % of all papers published since 2009. A wide range of applications were identified, with most papers focusing on ranking alternatives for flood mitigation, followed by risk, hazard, and vulnerability assessment. The analytical hierarchy process (AHP) was the most popular method, followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Simple Additive Weighting (SAW). Although there is greater interest in MCDM, uncertainty analysis remains an issue and was seldom applied in flood-related studies. In addition, participation of multiple stakeholders has been generally fragmented, focusing on particular stages of the decision-making process, especially on the definition of criteria weights. Therefore, addressing the uncertainties around stakeholders' judgments and endorsing an active participation in all steps of the decision-making process should be explored in future applications. This could help to increase the quality of decisions and the implementation of chosen measures.

An export coefficient based inexact fuzzy bi-level multi-objective programming model for the management of agricultural nonpoint source pollution under uncertainty

NASA Astrophysics Data System (ADS)

Cai, Yanpeng; Rong, Qiangqiang; Yang, Zhifeng; Yue, Wencong; Tan, Qian

2018-02-01

In this research, an export coefficient based inexact fuzzy bi-level multi-objective programming (EC-IFBLMOP) model was developed through integrating export coefficient model (ECM), interval parameter programming (IPP) and fuzzy parameter programming (FPP) within a bi-level multi-objective programming framework. The proposed EC-IFBLMOP model can effectively deal with the multiple uncertainties expressed as discrete intervals and fuzzy membership functions. Also, the complexities in agricultural systems, such as the cooperation and gaming relationship between the decision makers at different levels, can be fully considered in the model. The developed model was then applied to identify the optimal land use patterns and BMP implementing levels for agricultural nonpoint source (NPS) pollution management in a subcatchment in the upper stream watershed of the Miyun Reservoir in north China. The results of the model showed that the desired optimal land use patterns and implementing levels of best management of practices (BMPs) would be obtained. It is the gaming result between the upper- and lower-level decision makers, when the allowable discharge amounts of NPS pollutants were limited. Moreover, results corresponding to different decision scenarios could provide a set of decision alternatives for the upper- and lower-level decision makers to identify the most appropriate management strategy. The model has a good applicability and can be effectively utilized for agricultural NPS pollution management.

Equity trade-offs in conservation decision making.

PubMed

Law, Elizabeth A; Bennett, Nathan J; Ives, Christopher D; Friedman, Rachel; Davis, Katrina J; Archibald, Carla; Wilson, Kerrie A

2018-04-01

Conservation decisions increasingly involve multiple environmental and social objectives, which result in complex decision contexts with high potential for trade-offs. Improving social equity is one such objective that is often considered an enabler of successful outcomes and a virtuous ideal in itself. Despite its idealized importance in conservation policy, social equity is often highly simplified or ill-defined and is applied uncritically. What constitutes equitable outcomes and processes is highly normative and subject to ethical deliberation. Different ethical frameworks may lead to different conceptions of equity through alternative perspectives of what is good or right. This can lead to different and potentially conflicting equity objectives in practice. We promote a more transparent, nuanced, and pluralistic conceptualization of equity in conservation decision making that particularly recognizes where multidimensional equity objectives may conflict. To help identify and mitigate ethical conflicts and avoid cases of good intentions producing bad outcomes, we encourage a more analytical incorporation of equity into conservation decision making particularly during mechanistic integration of equity objectives. We recommend that in conservation planning motivations and objectives for equity be made explicit within the problem context, methods used to incorporate equity objectives be applied with respect to stated objectives, and, should objectives dictate, evaluation of equity outcomes and adaptation of strategies be employed during policy implementation. © 2017 Society for Conservation Biology.

A prospective analysis of implementation of multi-disciplinary team decisions in breast cancer.

PubMed

English, Rachel; Metcalfe, Chris; Day, James; Rayter, Zenon; Blazeby, Jane M

2012-09-01

Multi-disciplinary teams (MDTs) management of patients with cancer is mandatory in the United Kingdom, and auditing team decision-making by examining rates of decision implementation and reasons for nonimplementation may inform this practice. Consecutive breast cancer MDT decisions, subsequent decision implementation, and reasons for nonimplementation were prospectively recorded. Factors associated with nonimplementation of the MDT decision were analyzed with logistic regression. Of 289 consecutive MDT decisions involving 210 women, 20 (6.9%, 95% CIs 4.3%-10.5%) were not implemented. Most changed MDT decisions did so because of patient preferences (n = 13, 65%), with the discovery of new clinical information (n = 3) and individual doctor's views (n = 4) also leading to decision nonimplementation. MDT decisions were significantly less likely to be adhered to in patients with confirmed malignant disease compared to those with benign or 'unknown' disease categories (p < 0.001) and MDT decisions in older patients were significantly more likely not to be implemented than in younger patients (p = 0.002). Auditing nonimplementation of MDT recommendations and examining reasons for changed decisions is a useful process to monitor team performance and to identify factors that need more attention during the MDT meeting to ensure that the process makes optimal patient centered decisions. © 2012 Wiley Periodicals, Inc.

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,...

Developing a Software for Fuzzy Group Decision Support System: A Case Study

ERIC Educational Resources Information Center

Baba, A. Fevzi; Kuscu, Dincer; Han, Kerem

2009-01-01

The complex nature and uncertain information in social problems required the emergence of fuzzy decision support systems in social areas. In this paper, we developed user-friendly Fuzzy Group Decision Support Systems (FGDSS) software. The software can be used for multi-purpose decision making processes. It helps the users determine the main and…

Ostracism Reduces Reliance on Poor Advice from Others during Decision Making.

PubMed

Byrne, Kaileigh A; Tibbett, Thomas P; Laserna, Lauren N; Carter-Sowell, Adrienne R; Worthy, Darrell A

2016-10-01

Decision-making is rarely context-free, and often both social information and non-social information are weighed into one's decisions. Incorporating information into a decision can be influenced by previous experiences. Ostracism has extensive effects, including taxing cognitive resources and increasing social monitoring. In decision-making situations, individuals are often faced with both objective and social information and must choose which information to include or filter out. How will ostracism affect the reliance on objective and social information during decision-making? Participants ( N =245) in Experiment 1 were randomly assigned to be included or ostracized in a standardized, group task. They then performed a dynamic decision-making task that involved the presentation of either non-social (i.e. biased reward feedback) or social (i.e., poor advice from a previous participant) misleading information. In Experiment 2, participants ( N =105) completed either the ostracism non-social condition or social misleading information condition with explicit instructions stating that the advice given was from an individual who did not partake in the group task. Ostracized individuals relied more on non-social misleading information and performed worse than included individuals. However, ostracized individuals discounted misleading social information and outperformed included individuals. Results of Experiment 2 replicated the findings of Experiment 1. Across two experiments, ostracized individuals were more critical of advice from others, both individuals who may have ostracized them and unrelated individuals. In other words, compared to included individuals, ostracized individuals underweighted advice from another individual, but overweighted non-social information during decision-making. We conclude that when deceptive objective information is present, ostracism results in disadvantageous decision-making.

Measuring Shared Decision Making in Psychiatric Care

PubMed Central

Salyers, Michelle P.; Matthias, Marianne S.; Fukui, Sadaaki; Holter, Mark C.; Collins, Linda; Rose, Nichole; Thompson, John; Coffman, Melinda; Torrey, William C.

2014-01-01

Objective Shared decision making is widely recognized to facilitate effective health care; tools are needed to measure the level of shared decision making in psychiatric practice. Methods A coding scheme assessing shared decision making in medical settings (1) was adapted, including creation of a manual. Trained raters analyzed 170 audio recordings of psychiatric medication check-up visits. Results Inter-rater reliability among three raters for a subset of 20 recordings ranged from 67% to 100% agreement for the presence of each of nine elements of shared decision making and 100% for the overall agreement between provider and consumer. Just over half of the decisions met minimum criteria for shared decision making. Shared decision making was not related to length of visit after controlling for complexity of decision. Conclusions The shared decision making rating scale appears to reliably assess shared decision making in psychiatric practice and could be helpful for future research, training, and implementation efforts. PMID:22854725

Building a Predictive Capability for Decision-Making that Supports MultiPEM

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

Carmichael, Joshua Daniel

Multi-phenomenological explosion monitoring (multiPEM) is a developing science that uses multiple geophysical signatures of explosions to better identify and characterize their sources. MultiPEM researchers seek to integrate explosion signatures together to provide stronger detection, parameter estimation, or screening capabilities between different sources or processes. This talk will address forming a predictive capability for screening waveform explosion signatures to support multiPEM.

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.

The Influence of Organizational Image on College Selection: What Students Seek in Institutions of Higher Education

ERIC Educational Resources Information Center

Pampaloni, Andrea M.

2010-01-01

Colleges and universities rely on their image to attract new members. This study focuses on the decision-making process of students preparing to apply to college. High school students were surveyed at college open houses to identify the factors most influential to their college application decision-making. A multi-methods analysis found that…

Seven Reliability Indices for High-Stakes Decision Making: Description, Selection, and Simple Calculation

ERIC Educational Resources Information Center

Smith, Stacey L.; Vannest, Kimberly J.; Davis, John L.

2011-01-01

The reliability of data is a critical issue in decision-making for practitioners in the school. Percent Agreement and Cohen's kappa are the two most widely reported indices of inter-rater reliability, however, a recent Monte Carlo study on the reliability of multi-category scales found other indices to be more trustworthy given the type of data…

Aeromedical Disposition and Waiver Consideration for ISS Crewmembers

NASA Technical Reports Server (NTRS)

Taddeo, Terrance

2012-01-01

Aeromedical certification of astronauts and cosmonauts traveling to the International Space Station is a multi?-tiered process that involv es standards agreed to by the partner agencies, and participation by the individual agency aeromedical boards and a multilateral space medi cine board. Medical standards are updated continually by a multilater al working group. The boards operate by consensus and strive to achie ve effective decision making through experience, medical judgment, medical evidence and risk modeling. The aim of the certification process is to minimize the risk to the ISS program of loss of mission object ives due to human health issues.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations

PubMed Central

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the–server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models. PMID:27806061

Applying multi-criteria decision-making to improve the waste reduction policy in Taiwan.

PubMed

Su, Jun-Pin; Hung, Ming-Lung; Chao, Chia-Wei; Ma, Hwong-wen

2010-01-01

Over the past two decades, the waste reduction problem has been a major issue in environmental protection. Both recycling and waste reduction policies have become increasingly important. As the complexity of decision-making has increased, it has become evident that more factors must be considered in the development and implementation of policies aimed at resource recycling and waste reduction. There are many studies focused on waste management excluding waste reduction. This study paid more attention to waste reduction. Social, economic, and management aspects of waste treatment policies were considered in this study. Further, a life-cycle assessment model was applied as an evaluation system for the environmental aspect. Results of both quantitative and qualitative analyses on the social, economic, and management aspects were integrated via the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method into the comprehensive decision-making support system of multi-criteria decision-making (MCDM). A case study evaluating the waste reduction policy in Taoyuan County is presented to demonstrate the feasibility of this model. In the case study, reinforcement of MSW sorting was shown to be the best practice. The model in this study can be applied to other cities faced with the waste reduction problems.

Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

NASA Astrophysics Data System (ADS)

Vatcha, Rashna; Lee, Seok-Won; Murty, Ajeet; Tolone, William; Wang, Xiaoyu; Dou, Wenwen; Chang, Remco; Ribarsky, William; Liu, Wanqiu; Chen, Shen-en; Hauser, Edd

2009-05-01

Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to make efficient and effective informed decisions. The management involves a multi-faceted operation that requires the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical assets, we present our on-going multi-disciplinary large-scale project that establishes the Integrated Remote Sensing and Visualization (IRSV) system with a focus on supporting bridge structure inspection and management. This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world practitioners from industry, local and federal government agencies. IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding and enforcement of complex inspection process that can bridge the gap between evidence gathering and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation, representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented Architecture (SOA) framework to compose and provide services on-demand. IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme events.

Assessment and evaluation of technologies for environmental restoration. Progress report

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

Uzochukwu, G.A.

1999-01-15

Nuclear and commercial non-nuclear technologies that have the potential of meeting the environmental restoration objectives of the Department of Energy are being evaluated. A detailed comparison of innovative technologies available will be performed to determine the safest and most economical technology for meeting these objectives. Information derived from this effort will be matched with the multi-objective of the environmental restoration effort to ensure that the best, most economical, and the safest technologies are used in decision making at USDOE-SRS. Technology-related variables will be developed and the resulting data formatted and computerized for multimedia systems. The multimedia system will be mademore » available to technology developers and evaluators to ensure that the safest and most economical technologies are developed for use at SRS and other DOE sites.« less

Assessment and evaluation of technologies for environmental restoration. Progress report

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

Uzochukwu, G. A.

2000-06-30

Nuclear and commercial non-nuclear technologies that have the potential of meeting the environmental restoration objectives of the Department of Energy are being evaluated. A detailed comparison of innovative technologies available will be performed to determine the safest and most economical technology for meeting these objectives. Information derived from this effort will be matched with the multi-objective of the environmental restoration effort to ensure that the best, most economical, and the safest technologies are used in decision making at USDOE-SRS. Technology-related variables will be developed and the resulting data formatted and computerized for multimedia systems. The multimedia system will be mademore » available to technology developers and evaluators to ensure that the safest and most economical technologies are developed for use at SRS and other DOE sites.« less

Social Sensors (S2ensors): A Kind of Hardware-Software-Integrated Mediators for Social Manufacturing Systems Under Mass Individualization

NASA Astrophysics Data System (ADS)

Ding, Kai; Jiang, Ping-Yu

2017-09-01

Currently, little work has been devoted to the mediators and tools for multi-role production interactions in the mass individualization environment. This paper proposes a kind of hardware-software-integrated mediators called social sensors (S2ensors) to facilitate the production interactions among customers, manufacturers, and other stakeholders in the social manufacturing systems (SMS). The concept, classification, operational logics, and formalization of S2ensors are clarified. S2ensors collect subjective data from physical sensors and objective data from sensory input in mobile Apps, merge them into meaningful information for decision-making, and finally feed the decisions back for reaction and execution. Then, an S2ensors-Cloud platform is discussed to integrate different S2ensors to work for SMSs in an autonomous way. A demonstrative case is studied by developing a prototype system and the results show that S2ensors and S2ensors-Cloud platform can assist multi-role stakeholders interact and collaborate for the production tasks. It reveals the mediator-enabled mechanisms and methods for production interactions among stakeholders in SMS.

Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers

NASA Technical Reports Server (NTRS)

Tumer, K.; Lawson, J.

2003-01-01

Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.

Do neurocognitive deficits in decision making differentiate conduct disorder subtypes?

PubMed

Fanti, Kostas A; Kimonis, Eva R; Hadjicharalambous, Maria-Zoe; Steinberg, Laurence

2016-09-01

The present study aimed to test whether neurocognitive deficits involved in decision making underlie subtypes of conduct-disorder (CD) differentiated on the basis of callous-unemotional (CU) traits. Eighty-five participants (M age = 10.94 years) were selected from a sample of 1200 children based on repeated assessment of CD and CU traits. Participants completed a multi-method battery of well-validated measures of risky decision making and associated constructs of selective attention and future orientation (Stroop, Stoplight, and Delay-Discounting Tasks). Findings indicated that impaired decision making, selective attention, and future orientation contribute to the antisocial presentations displayed by children with CD, irrespective of level of CU traits. Youth high on CU traits without CD showed less risky decision making, as indicated by their performance on the Stoplight laboratory task, than those high on both CD and CU traits, suggesting a potential protective factor against the development of antisocial behavior.

Impact of Robotic Surgery on Decision Making: Perspectives of Surgical Teams

PubMed Central

Randell, Rebecca; Alvarado, Natasha; Honey, Stephanie; Greenhalgh, Joanne; Gardner, Peter; Gill, Arron; Jayne, David; Kotze, Alwyn; Pearman, Alan; Dowding, Dawn

2015-01-01

There has been rapid growth in the purchase of surgical robots in both North America and Europe in recent years. Whilst this technology promises many benefits for patients, the introduction of such a complex interactive system into healthcare practice often results in unintended consequences that are difficult to predict. Decision making by surgeons during an operation is affected by variables including tactile perception, visual perception, motor skill, and instrument complexity, all of which are changed by robotic surgery, yet the impact of robotic surgery on decision making has not been previously studied. Drawing on the approach of realist evaluation, we conducted a multi-site interview study across nine hospitals, interviewing 44 operating room personnel with experience of robotic surgery to gather their perspectives on how robotic surgery impacts surgeon decision making. The findings reveal both potential benefits and challenges of robotic surgery for decision making. PMID:26958244

Impact of Robotic Surgery on Decision Making: Perspectives of Surgical Teams.

PubMed

Randell, Rebecca; Alvarado, Natasha; Honey, Stephanie; Greenhalgh, Joanne; Gardner, Peter; Gill, Arron; Jayne, David; Kotze, Alwyn; Pearman, Alan; Dowding, Dawn

2015-01-01

There has been rapid growth in the purchase of surgical robots in both North America and Europe in recent years. Whilst this technology promises many benefits for patients, the introduction of such a complex interactive system into healthcare practice often results in unintended consequences that are difficult to predict. Decision making by surgeons during an operation is affected by variables including tactile perception, visual perception, motor skill, and instrument complexity, all of which are changed by robotic surgery, yet the impact of robotic surgery on decision making has not been previously studied. Drawing on the approach of realist evaluation, we conducted a multi-site interview study across nine hospitals, interviewing 44 operating room personnel with experience of robotic surgery to gather their perspectives on how robotic surgery impacts surgeon decision making. The findings reveal both potential benefits and challenges of robotic surgery for decision making.

A multi-objective programming model for assessment the GHG emissions in MSW management

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

Mavrotas, George, E-mail: mavrotas@chemeng.ntua.gr; Skoulaxinou, Sotiria; Gakis, Nikos

2013-09-15

Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty yearsmore » they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH{sub 4} generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application of the model in a Greek region.« less

Treatment decision-making among Canadian youth with severe haemophilia: a qualitative approach.

PubMed

Lane, S J; Walker, I; Chan, A K; Heddle, N M; Poon, M-C; Minuk, L; Jardine, L; Arnold, E; Sholapur, N; Webert, K E

2015-03-01

The first generation of young men using primary prophylaxis is coming of age. Important questions regarding the management of severe haemophilia with prophylaxis persist: Can prophylaxis be stopped? At what age? To what effect? Can the regimen be individualized? The reasons why some individuals discontinue or poorly comply with prophylaxis are not well understood. These issues have been explored using predominantly quantitative research approaches, yielding little insight into treatment decision-making from the perspectives of persons with haemophilia (PWH). Positioning the PWH as a source of expertise about their condition and its management, we undertook a qualitative study: (i) to explore and understand the lived experience of young men with severe haemophilia A or B and (ii) to identify the factors and inter-relationships between factors that affect young men's treatment decision-making. This manuscript reports primarily on the second objective. A modified Straussian, grounded theory methodology was used for data collection (interviews) and preliminary analysis. The study sample, youth aged 15-29, with severe haemophilia A or B, was chosen selectively and recruited through three Canadian Haemophilia Treatment Centres. We found treatment decision-making to be multi-factorial and used the Framework method to analyze the inter-relationships between factors. A typology of four distinct approaches to treatment was identified: lifestyle routine prophylaxis, situational prophylaxis, strict routine prophylaxis and no prophylaxis. Standardized treatment definitions (i.e.: 'primary' and 'secondary', 'prophylaxis') do not adequately describe the ways participants treat. Naming the variation of approaches documented in this study can improve PWH/provider communication, treatment planning and education. © 2014 John Wiley & Sons Ltd.

A guide to multi-objective optimization for ecological problems with an application to cackling goose management

USGS Publications Warehouse

Williams, Perry J.; Kendall, William L.

2017-01-01

Choices in ecological research and management are the result of balancing multiple, often competing, objectives. Multi-objective optimization (MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including engineering, economics, and operations research. However, its application for solving ecological problems has been sparse, perhaps due to a lack of widespread understanding. Thus, our objective was to provide an accessible primer on MOO, including a review of methods common in other fields, a review of their application in ecology, and a demonstration to an applied resource management problem.A large class of methods for solving MOO problems can be separated into two strategies: modelling preferences pre-optimization (the a priori strategy), or modelling preferences post-optimization (the a posteriori strategy). The a priori strategy requires describing preferences among objectives without knowledge of how preferences affect the resulting decision. In the a posteriori strategy, the decision maker simultaneously considers a set of solutions (the Pareto optimal set) and makes a choice based on the trade-offs observed in the set. We describe several methods for modelling preferences pre-optimization, including: the bounded objective function method, the lexicographic method, and the weighted-sum method. We discuss modelling preferences post-optimization through examination of the Pareto optimal set. We applied each MOO strategy to the natural resource management problem of selecting a population target for cackling goose (Branta hutchinsii minima) abundance. Cackling geese provide food security to Native Alaskan subsistence hunters in the goose's nesting area, but depredate crops on private agricultural fields in wintering areas. We developed objective functions to represent the competing objectives related to the cackling goose population target and identified an optimal solution first using the a priori strategy, and then by examining trade-offs in the Pareto set using the a posteriori strategy. We used four approaches for selecting a final solution within the a posteriori strategy; the most common optimal solution, the most robust optimal solution, and two solutions based on maximizing a restricted portion of the Pareto set. We discuss MOO with respect to natural resource management, but MOO is sufficiently general to cover any ecological problem that contains multiple competing objectives that can be quantified using objective functions.

Multicriteria decision analysis: Overview and implications for environmental decision making

USGS Publications Warehouse

Hermans, Caroline M.; Erickson, Jon D.; Erickson, Jon D.; Messner, Frank; Ring, Irene

2007-01-01

Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

ℓ0 -based sparse hyperspectral unmixing using spectral information and a multi-objectives formulation

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei; Pan, Bin

2018-07-01

Sparse unmixing aims at recovering pure materials from hyperpspectral images and estimating their abundance fractions. Sparse unmixing is actually ℓ0 problem which is NP-h ard, and a relaxation is often used. In this paper, we attempt to deal with ℓ0 problem directly via a multi-objective based method, which is a non-convex manner. The characteristics of hyperspectral images are integrated into the proposed method, which leads to a new spectra and multi-objective based sparse unmixing method (SMoSU). In order to solve the ℓ0 norm optimization problem, the spectral library is encoded in a binary vector, and a bit-wise flipping strategy is used to generate new individuals in the evolution process. However, a multi-objective method usually produces a number of non-dominated solutions, while sparse unmixing requires a single solution. How to make the final decision for sparse unmixing is challenging. To handle this problem, we integrate the spectral characteristic of hyperspectral images into SMoSU. By considering the spectral correlation in hyperspectral data, we improve the Tchebycheff decomposition function in SMoSU via a new regularization item. This regularization item is able to enforce the individual divergence in the evolution process of SMoSU. In this way, the diversity and convergence of population is further balanced, which is beneficial to the concentration of individuals. In the experiments part, three synthetic datasets and one real-world data are used to analyse the effectiveness of SMoSU, and several state-of-art sparse unmixing algorithms are compared.

Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making

PubMed Central

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2016-01-01

Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019

How can multi criteria decision analysis support value assessment of pharmaceuticals? - Findings from a systematic literature review.

PubMed

Kolasa, Katarzyna; Zah, Vladimir; Kowalczyk, Marta

2018-04-29

As budget constraints become more and more visible, there is growing recognition for greater transparency and greater stakeholders' engagement in the pharmaceuticals' pric-ing&reimbursement (P&R) decision making. New frameworks of drugs' value assessments are searched for. Among them, the multi-criteria decision analysis (MCDA) receives more and more attention. In 2014, ISPOR established Task Force to provide methodological recommendations for MCDA utilization in the health care decision making. Still, there is not so much knowledge about the real life experience with MCDA's adaptation to the P&R processes. Areas covered: A systematic literature review was performed to understand the rationale for MCDA adaptation, methodology used as well as its impact on P&R outcomes. Expert commentary: In total 102 hits were found through the search of databases, out of which 18 publications were selected. Although limited in scope, the review highlighted how MCDA can im-prove the decision making processes not only regarding pricing & reimbursement but also contribute to the the risk benefit assessment as well as optimization of treatment outcomes. Still none of re-viewed studies did report how MCDA results actually impacted the real life settings.

Cognitive Development Effects of Teaching Probabilistic Decision Making to Middle School Students

ERIC Educational Resources Information Center

Mjelde, James W.; Litzenberg, Kerry K.; Lindner, James R.

2011-01-01

This study investigated the comprehension and effectiveness of teaching formal, probabilistic decision-making skills to middle school students. Two specific objectives were to determine (1) if middle school students can comprehend a probabilistic decision-making approach, and (2) if exposure to the modeling approaches improves middle school…

Data Driven Decision Making in the Social Studies

ERIC Educational Resources Information Center

Ediger, Marlow

2010-01-01

Data driven decision making emphasizes the importance of the teacher using objective sources of information in developing the social studies curriculum. Too frequently, decisions of teachers have been made based on routine and outdated methods of teaching. Valid and reliable tests used to secure results from pupil learning make for better…

Visualization-based decision support for value-driven system design

NASA Astrophysics Data System (ADS)

Tibor, Elliott

In the past 50 years, the military, communication, and transportation systems that permeate our world, have grown exponentially in size and complexity. The development and production of these systems has seen ballooning costs and increased risk. This is particularly critical for the aerospace industry. The inability to deal with growing system complexity is a crippling force in the advancement of engineered systems. Value-Driven Design represents a paradigm shift in the field of design engineering that has potential to help counteract this trend. The philosophy of Value-Driven Design places the desires of the stakeholder at the forefront of the design process to capture true preferences and reveal system alternatives that were never previously thought possible. Modern aerospace engineering design problems are large, complex, and involve multiple levels of decision-making. To find the best design, the decision-maker is often required to analyze hundreds or thousands of combinations of design variables and attributes. Visualization can be used to support these decisions, by communicating large amounts of data in a meaningful way. Understanding the design space, the subsystem relationships, and the design uncertainties is vital to the advancement of Value-Driven Design as an accepted process for the development of more effective, efficient, robust, and elegant aerospace systems. This research investigates the use of multi-dimensional data visualization tools to support decision-making under uncertainty during the Value-Driven Design process. A satellite design system comprising a satellite, ground station, and launch vehicle is used to demonstrate effectiveness of new visualization methods to aid in decision support during complex aerospace system design. These methods are used to facilitate the exploration of the feasible design space by representing the value impact of system attribute changes and comparing the results of multi-objective optimization formulations with a Value-Driven Design formulation. The visualization methods are also used to assist in the decomposition of a value function, by representing attribute sensitivities to aid with trade-off studies. Lastly, visualization is used to enable greater understanding of the subsystem relationships, by displaying derivative-based couplings, and the design uncertainties, through implementation of utility theory. The use of these visualization methods is shown to enhance the decision-making capabilities of the designer by granting them a more holistic view of the complex design space.

Always Gamble on an Empty Stomach: Hunger Is Associated with Advantageous Decision Making

PubMed Central

de Ridder, Denise; Kroese, Floor; Adriaanse, Marieke; Evers, Catharine

2014-01-01

Three experimental studies examined the counterintuitive hypothesis that hunger improves strategic decision making, arguing that people in a hot state are better able to make favorable decisions involving uncertain outcomes. Studies 1 and 2 demonstrated that participants with more hunger or greater appetite made more advantageous choices in the Iowa Gambling Task compared to sated participants or participants with a smaller appetite. Study 3 revealed that hungry participants were better able to appreciate future big rewards in a delay discounting task; and that, in spite of their perception of increased rewarding value of both food and monetary objects, hungry participants were not more inclined to take risks to get the object of their desire. Together, these studies for the first time provide evidence that hot states improve decision making under uncertain conditions, challenging the conventional conception of the detrimental role of impulsivity in decision making. PMID:25340399

Always gamble on an empty stomach: hunger is associated with advantageous decision making.

PubMed

de Ridder, Denise; Kroese, Floor; Adriaanse, Marieke; Evers, Catharine

2014-01-01

Three experimental studies examined the counterintuitive hypothesis that hunger improves strategic decision making, arguing that people in a hot state are better able to make favorable decisions involving uncertain outcomes. Studies 1 and 2 demonstrated that participants with more hunger or greater appetite made more advantageous choices in the Iowa Gambling Task compared to sated participants or participants with a smaller appetite. Study 3 revealed that hungry participants were better able to appreciate future big rewards in a delay discounting task; and that, in spite of their perception of increased rewarding value of both food and monetary objects, hungry participants were not more inclined to take risks to get the object of their desire. Together, these studies for the first time provide evidence that hot states improve decision making under uncertain conditions, challenging the conventional conception of the detrimental role of impulsivity in decision making.

Critical multi-level governance issues of integrated modelling: An example of low-water management in the Adour-Garonne basin (France)

NASA Astrophysics Data System (ADS)

Mazzega, Pierre; Therond, Olivier; Debril, Thomas; March, Hug; Sibertin-Blanc, Christophe; Lardy, Romain; Sant'ana, Daniel

2014-11-01

This paper presents the experience gained related to the development of an integrated simulation model of water policy. Within this context, we analyze particular difficulties raised by the inclusion of multi-level governance that assigns the responsibility of individual or collective decision-making to a variety of actors, regarding measures of which the implementation has significant effects toward the sustainability of socio-hydrosystems. Multi-level governance procedures are compared with the potential of model-based impact assessment. Our discussion is illustrated on the basis of the exploitation of the multi-agent platform MAELIA dedicated to the simulation of social, economic and environmental impacts of low-water management in a context of climate and regulatory changes. We focus on three major decision-making processes occurring in the Adour-Garonne basin, France: (i) the participatory development of the Master Scheme for Water Planning and Management (SDAGE) under the auspices of the Water Agency; (ii) the publication of water use restrictions in situations of water scarcity; and (iii) the determination of the abstraction volumes for irrigation and their allocation. The MAELIA platform explicitly takes into account the mode of decision-making when it is framed by a procedure set beforehand, focusing on the actors' participation and on the nature and parameters of the measures to be implemented. It is observed that in some water organizations decision-making follows patterns that can be represented as rule-based actions triggered by thresholds of resource states. When decisions are resulting from individual choice, endowing virtual agents with bounded rationality allows us to reproduce (in silico) their behavior and decisions in a reliable way. However, the negotiation processes taking place during the period of time simulated by the models in arenas of collective choices are not all reproducible. Outcomes of some collective decisions are very little or not at all predictable. The development and simulation of a priori policy scenarios capturing the most plausible or interesting outcomes of such collective decisions on measures for low-water management allows these difficulties to be overcome. The building of these kind of scenarios requires close collaboration between researchers and stakeholders involved in arenas of collective choice, and implies the integration of the production of model and the analysis of scenarios as one component of the polycentric political process of water management.

Emergent collective decision-making: Control, model and behavior

NASA Astrophysics Data System (ADS)

Shen, Tian

In this dissertation we study emergent collective decision-making in social groups with time-varying interactions and heterogeneously informed individuals. First we analyze a nonlinear dynamical systems model motivated by animal collective motion with heterogeneously informed subpopulations, to examine the role of uninformed individuals. We find through formal analysis that adding uninformed individuals in a group increases the likelihood of a collective decision. Secondly, we propose a model for human shared decision-making with continuous-time feedback and where individuals have little information about the true preferences of other group members. We study model equilibria using bifurcation analysis to understand how the model predicts decisions based on the critical threshold parameters that represent an individual's tradeoff between social and environmental influences. Thirdly, we analyze continuous-time data of pairs of human subjects performing an experimental shared tracking task using our second proposed model in order to understand transient behavior and the decision-making process. We fit the model to data and show that it reproduces a wide range of human behaviors surprisingly well, suggesting that the model may have captured the mechanisms of observed behaviors. Finally, we study human behavior from a game-theoretic perspective by modeling the aforementioned tracking task as a repeated game with incomplete information. We show that the majority of the players are able to converge to playing Nash equilibrium strategies. We then suggest with simulations that the mean field evolution of strategies in the population resemble replicator dynamics, indicating that the individual strategies may be myopic. Decisions form the basis of control and problems involving deciding collectively between alternatives are ubiquitous in nature and in engineering. Understanding how multi-agent systems make decisions among alternatives also provides insight for designing decentralized control laws for engineering applications from mobile sensor networks for environmental monitoring to collective construction robots. With this dissertation we hope to provide additional methodology and mathematical models for understanding the behavior and control of collective decision-making in multi-agent systems.

Incompetent Patients, Substitute Decision Making, and Quality of Life: Some Ethical Considerations

PubMed Central

Kluge, Eike-Henner W.

2008-01-01

One of the most difficult situations facing physicians involves decision making by substitute decision makers for patients who have never been competent. This paper begins with a brief examination of the ethics of substitute decision making for previously competent patients. It then applies the results to substitute decision making for patients who have never been competent, and critically analyzes 5 models of substitute decision making for such patients, showing why each either contravenes basic ethical principles or fails to guarantee the use of ethically appropriate values. It concludes by sketching a modified objective reasonable person standard for substitute decision making that avoids valuational difficulties and allows for a protocol that satisfies ethical principles. PMID:19099031

A New Automated Design Method Based on Machine Learning for CMOS Analog Circuits

NASA Astrophysics Data System (ADS)

Moradi, Behzad; Mirzaei, Abdolreza

2016-11-01

A new simulation based automated CMOS analog circuit design method which applies a multi-objective non-Darwinian-type evolutionary algorithm based on Learnable Evolution Model (LEM) is proposed in this article. The multi-objective property of this automated design of CMOS analog circuits is governed by a modified Strength Pareto Evolutionary Algorithm (SPEA) incorporated in the LEM algorithm presented here. LEM includes a machine learning method such as the decision trees that makes a distinction between high- and low-fitness areas in the design space. The learning process can detect the right directions of the evolution and lead to high steps in the evolution of the individuals. The learning phase shortens the evolution process and makes remarkable reduction in the number of individual evaluations. The expert designer's knowledge on circuit is applied in the design process in order to reduce the design space as well as the design time. The circuit evaluation is made by HSPICE simulator. In order to improve the design accuracy, bsim3v3 CMOS transistor model is adopted in this proposed design method. This proposed design method is tested on three different operational amplifier circuits. The performance of this proposed design method is verified by comparing it with the evolutionary strategy algorithm and other similar methods.

Issues in Developing a Normative Descriptive Model for Dyadic Decision Making

NASA Technical Reports Server (NTRS)

Serfaty, D.; Kleinman, D. L.

1984-01-01

Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.

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.

Use of the AHP methodology in system dynamics: Modelling and simulation for health technology assessments to determine the correct prosthesis choice for hernia diseases.

PubMed

Improta, Giovanni; Russo, Mario Alessandro; Triassi, Maria; Converso, Giuseppe; Murino, Teresa; Santillo, Liberatina Carmela

2018-05-01

Health technology assessments (HTAs) are often difficult to conduct because of the decisive procedures of the HTA algorithm, which are often complex and not easy to apply. Thus, their use is not always convenient or possible for the assessment of technical requests requiring a multidisciplinary approach. This paper aims to address this issue through a multi-criteria analysis focusing on the analytic hierarchy process (AHP). This methodology allows the decision maker to analyse and evaluate different alternatives and monitor their impact on different actors during the decision-making process. However, the multi-criteria analysis is implemented through a simulation model to overcome the limitations of the AHP methodology. Simulations help decision-makers to make an appropriate decision and avoid unnecessary and costly attempts. Finally, a decision problem regarding the evaluation of two health technologies, namely, the evaluation of two biological prostheses for incisional infected hernias, will be analysed to assess the effectiveness of the model. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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.

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.

Ostracism Reduces Reliance on Poor Advice from Others during Decision Making

PubMed Central

Byrne, Kaileigh A.; Tibbett, Thomas P.; Laserna, Lauren N.; Carter-Sowell, Adrienne R.; Worthy, Darrell A.

2016-01-01

Decision-making is rarely context-free, and often both social information and non-social information are weighed into one’s decisions. Incorporating information into a decision can be influenced by previous experiences. Ostracism has extensive effects, including taxing cognitive resources and increasing social monitoring. In decision-making situations, individuals are often faced with both objective and social information and must choose which information to include or filter out. How will ostracism affect the reliance on objective and social information during decision-making? Participants (N=245) in Experiment 1 were randomly assigned to be included or ostracized in a standardized, group task. They then performed a dynamic decision-making task that involved the presentation of either non-social (i.e. biased reward feedback) or social (i.e., poor advice from a previous participant) misleading information. In Experiment 2, participants (N=105) completed either the ostracism non-social condition or social misleading information condition with explicit instructions stating that the advice given was from an individual who did not partake in the group task. Ostracized individuals relied more on non-social misleading information and performed worse than included individuals. However, ostracized individuals discounted misleading social information and outperformed included individuals. Results of Experiment 2 replicated the findings of Experiment 1. Across two experiments, ostracized individuals were more critical of advice from others, both individuals who may have ostracized them and unrelated individuals. In other words, compared to included individuals, ostracized individuals underweighted advice from another individual, but overweighted non-social information during decision-making. We conclude that when deceptive objective information is present, ostracism results in disadvantageous decision-making. PMID:28469290

Complexity of line-seru conversion for different scheduling rules and two improved exact algorithms for the multi-objective optimization.

PubMed

Yu, Yang; Wang, Sihan; Tang, Jiafu; Kaku, Ikou; Sun, Wei

2016-01-01

Productivity can be greatly improved by converting the traditional assembly line to a seru system, especially in the business environment with short product life cycles, uncertain product types and fluctuating production volumes. Line-seru conversion includes two decision processes, i.e., seru formation and seru load. For simplicity, however, previous studies focus on the seru formation with a given scheduling rule in seru load. We select ten scheduling rules usually used in seru load to investigate the influence of different scheduling rules on the performance of line-seru conversion. Moreover, we clarify the complexities of line-seru conversion for ten different scheduling rules from the theoretical perspective. In addition, multi-objective decisions are often used in line-seru conversion. To obtain Pareto-optimal solutions of multi-objective line-seru conversion, we develop two improved exact algorithms based on reducing time complexity and space complexity respectively. Compared with the enumeration based on non-dominated sorting to solve multi-objective problem, the two improved exact algorithms saves computation time greatly. Several numerical simulation experiments are performed to show the performance improvement brought by the two proposed exact algorithms.

Participatory modeling and structured decision making

USGS Publications Warehouse

Robinson, Kelly F.; Fuller, Angela K.

2016-01-01

Structured decision making (SDM) provides a framework for making sound decisions even when faced with uncertainty, and is a transparent, defensible, and replicable method used to understand complex problems. A hallmark of SDM is the explicit incorporation of values and science, which often includes participation from multiple stakeholders, helping to garner trust and ultimately result in a decision that is more likely to be implemented. The core steps in the SDM process are used to structure thinking about natural resources management choices, and include: (1) properly defining the problem and the decision context, (2) determining the objectives that help describe the aspirations of the decision maker, (3) devising management actions or alternatives that can achieve those objectives, (4) evaluating the outcomes or consequences of each alternative on each of the objectives, (5) evaluating trade-offs, and (6) implementing the decision. Participatory modeling for SDM includes engaging stakeholders in some or all of the steps of the SDM process listed above. In addition, participatory modeling often is crucial for creating qualitative and quantitative models of how the system works, providing data for these models, and eliciting expert opinion when data are unavailable. In these ways, SDM provides a framework for decision making in natural resources management that includes participation from stakeholder groups throughout the process, including the modeling phase.

A dataset of human decision-making in teamwork management.

PubMed

Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

2017-01-17

Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.

A dataset of human decision-making in teamwork management

PubMed Central

Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

2017-01-01

Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members’ capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches. PMID:28094787

A dataset of human decision-making in teamwork management

NASA Astrophysics Data System (ADS)

Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

2017-01-01

Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.

Application of an integrated multi-criteria decision making AHP-TOPSIS methodology for ETL software selection.

PubMed

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

2016-01-01

Actually, a set of ETL software (Extract, Transform and Load) is available to constitute a major investment market. Each ETL uses its own techniques for extracting, transforming and loading data into data warehouse, which makes the task of evaluating ETL software very difficult. However, choosing the right software of ETL is critical to the success or failure of any Business Intelligence project. As there are many impacting factors in the selection of ETL software, the same process is considered as a complex multi-criteria decision making (MCDM) problem. In this study, an application of decision-making methodology that employs the two well-known MCDM techniques, namely Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods is designed. In this respect, the aim of using AHP is to analyze the structure of the ETL software selection problem and obtain weights of the selected criteria. Then, TOPSIS technique is used to calculate the alternatives' ratings. An example is given to illustrate the proposed methodology. Finally, a software prototype for demonstrating both methods is implemented.

Theoretical aspects of cellular decision-making and information-processing.

PubMed

Kobayashi, Tetsuya J; Kamimura, Atsushi

2012-01-01

Microscopic biological processes have extraordinary complexity and variety at the sub-cellular, intra-cellular, and multi-cellular levels. In dealing with such complex phenomena, conceptual and theoretical frameworks are crucial, which enable us to understand seemingly different intra- and inter-cellular phenomena from unified viewpoints. Decision-making is one such concept that has attracted much attention recently. Since a number of cellular behavior can be regarded as processes to make specific actions in response to external stimuli, decision-making can cover and has been used to explain a broad range of different cellular phenomena [Balázsi et al. (Cell 144(6):910, 2011), Zeng et al. (Cell 141(4):682, 2010)]. Decision-making is also closely related to cellular information-processing because appropriate decisions cannot be made without exploiting the information that the external stimuli contain. Efficiency of information transduction and processing by intra-cellular networks determines the amount of information obtained, which in turn limits the efficiency of subsequent decision-making. Furthermore, information-processing itself can serve as another concept that is crucial for understanding of other biological processes than decision-making. In this work, we review recent theoretical developments on cellular decision-making and information-processing by focusing on the relation between these two concepts.

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.

Protest Motherhood: Pregnancy Decision-Making Behavior and Attitudes Towards Abortion.

ERIC Educational Resources Information Center

Chesney-Lind, Meda

The document describes research on womens' attitudes toward abortion and their decision-making when pregnant leading to either birth or abortion. The objective was "to explore how womens' perceptions of the option of legal abortion have affected their pregnancy decision-making behavior" and to note the impact of their particular choices on their…

Got risk? risk-centric perspective for spacecraft technology decision-making

NASA Technical Reports Server (NTRS)

Feather, Martin S.; Cornford, Steven L.; Moran, Kelly

2004-01-01

A risk-based decision-making methodology conceived and developed at JPL and NASA has been used to aid in decision making for spacecraft technology assessment, adoption, development and operation. It takes a risk-centric perspective, through which risks are used as a reasoning step to interpose between mission objectives and risk mitigation measures.

Multi-criteria decision analysis and environmental risk assessment for nanomaterials

NASA Astrophysics Data System (ADS)

Linkov, Igor; Satterstrom, F. Kyle; Steevens, Jeffery; Ferguson, Elizabeth; Pleus, Richard C.

2007-08-01

Nanotechnology is a broad and complex discipline that holds great promise for innovations that can benefit mankind. Yet, one must not overlook the wide array of factors involved in managing nanomaterial development, ranging from the technical specifications of the material to possible adverse effects in humans. Other opportunities to evaluate benefits and risks are inherent in environmental health and safety (EHS) issues related to nanotechnology. However, there is currently no structured approach for making justifiable and transparent decisions with explicit trade-offs between the many factors that need to be taken into account. While many possible decision-making approaches exist, we believe that multi-criteria decision analysis (MCDA) is a powerful and scientifically sound decision analytical framework for nanomaterial risk assessment and management. This paper combines state-of-the-art research in MCDA methods applicable to nanotechnology with a hypothetical case study for nanomaterial management. The example shows how MCDA application can balance societal benefits against unintended side effects and risks, and how it can also bring together multiple lines of evidence to estimate the likely toxicity and risk of nanomaterials given limited information on physical and chemical properties. The essential contribution of MCDA is to link this performance information with decision criteria and weightings elicited from scientists and managers, allowing visualization and quantification of the trade-offs involved in the decision-making process.

Control, Contingency and Delegation in Decision-Making.

ERIC Educational Resources Information Center

Michael, Stephen R.

1979-01-01

Proposes a model which emphasizes the delegation of decision-making authority and managerial control of operations. Suggests that risks can be reduced by using (1) a contingency approach to delegation, (2) decision rules for consistency, (3) decision models for specific situations, (4) vital indicator reports, (5) management by objectives, and (6)…

[End-of-life decisions and practices in critically ill patients in the cardiac intensive care unit. A nationwide survey].

PubMed

Schimmer, C; Hamouda, K; Oezkur, M; Sommer, S-P; Leistner, M; Leyh, R

2016-03-01

Ethical and medical criteria in the decision-making process of withholding or withdrawal of life support therapy in critically ill patients present a great challenge in intensive care medicine. The purpose of this work was to assess medical and ethical criteria that influence the decision-making process for changing the aim of therapy in critically ill cardiac surgery patients. A questionnaire was distributed to all German cardiac surgery centers (n = 79). All clinical directors, intensive care unit (ICU) consultants and ICU head nurses were asked to complete questionnaires (n = 237). In all, 86 of 237 (36.3 %) questionnaires were returned. Medical reasons which influence the decision-making process for changing the aim of therapy were cranial computed tomography (cCT) with poor prognosis (91.9 %), multi-organ failure (70.9 %), and failure of assist device therapy (69.8 %). Concerning ethical reasons, poor expected quality of life (48.8 %) and the presumed patient's wishes (40.7 %) were reported. There was a significant difference regarding the perception of the three different professional groups concerning medical and ethical criteria as well as the involvement in the decision-making process. In critically ill cardiac surgery patients, medical reasons which influence the decision-making process for changing the aim of therapy included cCT with poor prognosis, multi-organ failure, and failure of assist device therapy. Further studies are mandatory in order to be able to provide adequate answers to this difficult topic.

Prospect Theory and Interval-Valued Hesitant Set for Safety Evacuation Model

NASA Astrophysics Data System (ADS)

Kou, Meng; Lu, Na

2018-01-01

The study applies the research results of prospect theory and multi attribute decision making theory, combined with the complexity, uncertainty and multifactor influence of the underground mine fire system and takes the decision makers’ psychological behavior of emotion and intuition into full account to establish the intuitionistic fuzzy multiple attribute decision making method that is based on the prospect theory. The model established by this method can explain the decision maker’s safety evacuation decision behavior in the complex system of underground mine fire due to the uncertainty of the environment, imperfection of the information and human psychological behavior and other factors.

Can streamlined multi-criteria decision analysis be used to implement shared decision making for colorectal cancer screening?

PubMed Central

Dolan, James G.; Boohaker, Emily; Allison, Jeroan; Imperiale, Thomas F.

2013-01-01

Background Current US colorectal cancer screening guidelines that call for shared decision making regarding the choice among several recommended screening options are difficult to implement. Multi-criteria decision analysis (MCDA) is an established methodology well suited for supporting shared decision making. Our study goal was to determine if a streamlined form of MCDA using rank order based judgments can accurately assess patients’ colorectal cancer screening priorities. Methods We converted priorities for four decision criteria and three sub-criteria regarding colorectal cancer screening obtained from 484 average risk patients using the Analytic Hierarchy Process (AHP) in a prior study into rank order-based priorities using rank order centroids. We compared the two sets of priorities using Spearman rank correlation and non-parametric Bland-Altman limits of agreement analysis. We assessed the differential impact of using the rank order-based versus the AHP-based priorities on the results of a full MCDA comparing three currently recommended colorectal cancer screening strategies. Generalizability of the results was assessed using Monte Carlo simulation. Results Correlations between the two sets of priorities for the seven criteria ranged from 0.55 to 0.92. The proportions of absolute differences between rank order-based and AHP-based priorities that were more than ± 0.15 ranged from 1% to 16%. Differences in the full MCDA results were minimal and the relative rankings of the three screening options were identical more than 88% of the time. The Monte Carlo simulation results were similar. Conclusion Rank order-based MCDA could be a simple, practical way to guide individual decisions and assess population decision priorities regarding colorectal cancer screening strategies. Additional research is warranted to further explore the use of these methods for promoting shared decision making. PMID:24300851

Use of economic evaluation in decision making: evidence and recommendations for improvement.

PubMed

Simoens, Steven

2010-10-22

Information about the value for money of a medicine as derived from an economic evaluation can be used for decision-making purposes by policy makers, healthcare payers, healthcare professionals and pharmaceutical companies. This article illustrates the use of economic evaluation by decision makers and formulates a number of recommendations to enhance the use of such evaluations for decision-making purposes. Over the last decades, there has been a substantial increase in the number of economic evaluations assessing the value for money of medicines. Economic evaluation is used by policy makers and healthcare payers to inform medicine pricing/reimbursement decisions in more and more countries. It is a suitable tool to evaluate medicines and to present information about their value for money to decision makers in a familiar format. In order to fully exploit the use of economic evaluation for decision-making purposes, researchers need to take care to conduct such economic evaluations according to methodologically sound principles. Additionally, researchers need to take into account the decision-making context. They need to identify the various objectives that decision makers pursue and discuss how decision makers can use study findings to attain these objectives. These issues require further attention from researchers, policy makers, healthcare payers, healthcare professionals and pharmaceutical companies with a view to optimizing the use of economic evaluation in decision making.

Adaptive management in the U.S. National Wildlife Refuge System: Science-management partnerships for conservation delivery

USGS Publications Warehouse

Moore, C.T.; Lonsdorf, E.V.; Knutson, M.G.; Laskowski, H.P.; Lor, S.K.

2011-01-01

Adaptive management is an approach to recurrent decision making in which uncertainty about the decision is reduced over time through comparison of outcomes predicted by competing models against observed values of those outcomes. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service is a large land management program charged with making natural resource management decisions, which often are made under considerable uncertainty, severe operational constraints, and conditions that limit ability to precisely carry out actions as intended. The NWRS presents outstanding opportunities for the application of adaptive management, but also difficult challenges. We describe two cooperative programs between the Fish and Wildlife Service and the U.S. Geological Survey to implement adaptive management at scales ranging from small, single refuge applications to large, multi-refuge, multi-region projects. Our experience to date suggests three important attributes common to successful implementation: a vigorous multi-partner collaboration, practical and informative decision framework components, and a sustained commitment to the process. Administrators in both agencies should consider these attributes when developing programs to promote the use and acceptance of adaptive management in the NWRS. ?? 2010 .

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.

Strategic planning decision making using fuzzy SWOT-TOPSIS with reliability factor

NASA Astrophysics Data System (ADS)

Mohamad, Daud; Afandi, Nur Syamimi; Kamis, Nor Hanimah

2015-10-01

Strategic planning is a process of decision making and action for long-term activities in an organization. The Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis has been commonly used to help organizations in strategizing their future direction by analyzing internal and external environment. However, SWOT analysis has some limitations as it is unable to prioritize appropriately the multiple alternative strategic decisions. Some efforts have been made to solve this problem by incorporating Multi Criteria Decision Making (MCDM) methods. Nevertheless, another important aspect has raised concerns on obtaining the decision that is the reliability of the information. Decision makers evaluate differently depending on their level of confidence or sureness in the evaluation. This study proposes a decision making procedure for strategic planning using SWOT-TOPSIS method by incorporating the reliability factor of the evaluation based on Z-number. An example using a local authority in the east coast of Malaysia is illustrated to determine the strategic options ranking and to prioritize factors in each SWOT category.

ANFIS multi criteria decision making for overseas construction projects: a methodology

NASA Astrophysics Data System (ADS)

Utama, W. P.; Chan, A. P. C.; Zulherman; Zahoor, H.; Gao, R.; Jumas, D. Y.

2018-02-01

A critical part when a company targeting a foreign market is how to make a better decision in connection with potential project selection. Since different attributes of information are often incomplete, imprecise and ill-defined in overseas projects selection, the process of decision making by relying on the experiences and intuition is a risky attitude. This paper aims to demonstrate a decision support method in deciding overseas construction projects (OCPs). An Adaptive Neuro-Fuzzy Inference System (ANFIS), the amalgamation of Neural Network and Fuzzy Theory, was used as decision support tool to decide to go or not go on OCPs. Root mean square error (RMSE) and coefficient of correlation (R) were employed to identify the ANFIS system indicating an optimum and efficient result. The optimum result was obtained from ANFIS network with two input membership functions, Gaussian membership function (gaussmf) and hybrid optimization method. The result shows that ANFIS may help the decision-making process for go/not go decision in OCPs.

A multi-faceted approach to promote knowledge translation platforms in eastern Mediterranean countries: climate for evidence-informed policy

PubMed Central

2012-01-01

Objectives Limited work has been done to promote knowledge translation (KT) in the Eastern Mediterranean Region (EMR). The objectives of this study are to: 1.assess the climate for evidence use in policy; 2.explore views and practices about current processes and weaknesses of health policymaking; 3.identify priorities including short-term requirements for policy briefs; and 4.identify country-specific requirements for establishing KT platforms. Methods Senior policymakers, stakeholders and researchers from Algeria, Bahrain, Egypt, Iran, Jordan, Lebanon, Oman, Sudan, Syria, Tunisia, and Yemen participated in this study. Questionnaires were used to assess the climate for use of evidence and identify windows of opportunity and requirements for policy briefs and for establishing KT platforms. Current processes and weaknesses of policymaking were appraised using case study scenarios. Closed-ended questions were analyzed descriptively. Qualitative data was analyzed using thematic analysis. Results KT activities were not frequently undertaken by policymakers and researchers in EMR countries, research evidence about high priority policy issues was rarely made available, and interaction between policymakers and researchers was limited, and policymakers rarely identified or created places for utilizing research evidence in decision-making processes. Findings emphasized the complexity of policymaking. Donors, political regimes, economic goals and outdated laws were identified as key drivers. Lack of policymakers’ abilities to think strategically, constant need to make quick decisions, limited financial resources, and lack of competent and trained human resources were suggested as main weaknesses. Conclusion Despite the complexity of policymaking processes in countries from this region, the absence of a structured process for decision making, and the limited engagement of policymakers and researchers in KT activities, there are windows of opportunity for moving towards more evidence informed policymaking. PMID:22559007

Managing and learning with multiple models: Objectives and optimization algorithms

USGS Publications Warehouse

Probert, William J. M.; Hauser, C.E.; McDonald-Madden, E.; Runge, M.C.; Baxter, P.W.J.; Possingham, H.P.

2011-01-01

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. ?? 2010 Elsevier Ltd.

Using multi-criteria decision making for selection of the optimal strategy for municipal solid waste management.

PubMed

Jovanovic, Sasa; Savic, Slobodan; Jovicic, Nebojsa; Boskovic, Goran; Djordjevic, Zorica

2016-09-01

Multi-criteria decision making (MCDM) is a relatively new tool for decision makers who deal with numerous and often contradictory factors during their decision making process. This paper presents a procedure to choose the optimal municipal solid waste (MSW) management system for the area of the city of Kragujevac (Republic of Serbia) based on the MCDM method. Two methods of multiple attribute decision making, i.e. SAW (simple additive weighting method) and TOPSIS (technique for order preference by similarity to ideal solution), respectively, were used to compare the proposed waste management strategies (WMS). Each of the created strategies was simulated using the software package IWM2. Total values for eight chosen parameters were calculated for all the strategies. Contribution of each of the six waste treatment options was valorized. The SAW analysis was used to obtain the sum characteristics for all the waste management treatment strategies and they were ranked accordingly. The TOPSIS method was used to calculate the relative closeness factors to the ideal solution for all the alternatives. Then, the proposed strategies were ranked in form of tables and diagrams obtained based on both MCDM methods. As shown in this paper, the results were in good agreement, which additionally confirmed and facilitated the choice of the optimal MSW management strategy. © The Author(s) 2016.

Reactivation of Reward-Related Patterns from Single Past Episodes Supports Memory-Based Decision Making.

PubMed

Wimmer, G Elliott; Büchel, Christian

2016-03-09

Rewarding experiences exert a strong influence on later decision making. While decades of neuroscience research have shown how reinforcement gradually shapes preferences, decisions are often influenced by single past experiences. Surprisingly, relatively little is known about the influence of single learning episodes. Although recent work has proposed a role for episodes in decision making, it is largely unknown whether and how episodic experiences contribute to value-based decision making and how the values of single episodes are represented in the brain. In multiple behavioral experiments and an fMRI experiment, we tested whether and how rewarding episodes could support later decision making. Participants experienced episodes of high reward or low reward in conjunction with incidental, trial-unique neutral pictures. In a surprise test phase, we found that participants could indeed remember the associated level of reward, as evidenced by accurate source memory for value and preferences to re-engage with rewarded objects. Further, in a separate experiment, we found that high-reward objects shown as primes before a gambling task increased financial risk taking. Neurally, re-exposure to objects in the test phase led to significant reactivation of reward-related patterns. Importantly, individual variability in the strength of reactivation predicted value memory performance. Our results provide a novel demonstration that affect-related neural patterns are reactivated during later experience. Reactivation of value information represents a mechanism by which memory can guide decision making. Copyright © 2016 the authors 0270-6474/16/362868-13$15.00/0.

Poor Decision Making Is a Consequence of Cognitive Decline among Older Persons without Alzheimer’s Disease or Mild Cognitive Impairment

PubMed Central

Boyle, Patricia A.; Yu, Lei; Wilson, Robert S.; Gamble, Keith; Buchman, Aron S.; Bennett, David A.

2012-01-01

Objective Decision making is an important determinant of health and well-being across the lifespan but is critical in aging, when many influential decisions are made just as cognitive function declines. Increasing evidence suggests that older adults, even those without dementia, often make poor decisions and are selectively vulnerable to scams. To date, however, the factors associated with poor decision making in old age are unknown. The objective of this study was to test the hypothesis that poor decision making is a consequence of cognitive decline among older persons without Alzheimer’s disease or mild cognitive impairment. Methods Participants were 420 non-demented persons from the Memory and Aging Project, a longitudinal, clinical-pathologic cohort study of aging in the Chicago metropolitan area. All underwent repeated cognitive evaluations and subsequently completed assessments of decision making and susceptibility to scams. Decision making was measured using 12 items from a previously established performance-based measure and a self-report measure of susceptibility to scams. Results Cognitive function data were collected over an average of 5.5 years prior to the decision making assessment. Regression analyses were used to examine whether the prior rate of cognitive decline predicted the level of decision making and susceptibility to scams; analyses controlled for age, sex, education, and starting level of cognition. Among 420 persons without dementia, more rapid cognitive decline predicted poorer decision making and increased susceptibility to scams (p’s<0.001). Further, the relations between cognitive decline, decision making and scams persisted in analyses restricted to persons without any cognitive impairment (i.e., no dementia or even mild cognitive impairment). Conclusions Poor decision making is a consequence of cognitive decline among older persons without Alzheimer’s disease or mild cognitive impairment, those widely considered “cognitively healthy.” These findings suggest that even very subtle age-related changes in cognition have detrimental effects on judgment. PMID:22916287

Help in making fuel management decisions.

Treesearch

Peter J. Roussopoulos; Von J. Johnson

1975-01-01

Describes how to compare predictions of fuel hazard for Northeastern logging slash with a number of fuel hazard "standards." This system provides objective criteria for making fuel management decisions.

Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm

PubMed Central

Tamjidy, Mehran; Baharudin, B. T. Hang Tuah; Paslar, Shahla; Matori, Khamirul Amin; Sulaiman, Shamsuddin; Fadaeifard, Firouz

2017-01-01

The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon’s entropy. PMID:28772893

Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm.

PubMed

Tamjidy, Mehran; Baharudin, B T Hang Tuah; Paslar, Shahla; Matori, Khamirul Amin; Sulaiman, Shamsuddin; Fadaeifard, Firouz

2017-05-15

The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon's entropy.

Aircraft accident investigation: the decision-making in initial action scenario.

PubMed

Barreto, Marcia M; Ribeiro, Selma L O

2012-01-01

In the complex aeronautical environment, the efforts in terms of operational safety involve the adoption of proactive and reactive measures. The process of investigation begins right after the occurrence of the aeronautical accident, through the initial action. Thus, it is in the crisis scenario, that the person responsible for the initial action makes decisions and gathers the necessary information for the subsequent phases of the investigation process. Within this scenario, which is a natural environment, researches have shown the fragility of rational models of decision making. The theoretical perspective of naturalistic decision making constitutes a breakthrough in the understanding of decision problems demanded by real world. The proposal of this study was to verify if the initial action, after the occurrence of an accident, and the decision-making strategies, used by the investigators responsible for this activity, are characteristic of the naturalistic decision making theoretical approach. To attend the proposed objective a descriptive research was undertaken with a sample of professionals that work in this activity. The data collected through individual interviews were analyzed and the results demonstrated that the initial action environment, which includes restricted time, dynamic conditions, the presence of multiple actors, stress and insufficient information is characteristic of the naturalistic decision making. They also demonstrated that, when the investigators make their decisions, they use their experience and the mental simulation, intuition, improvisation, metaphors and analogues cases, as strategies, all of them related to the naturalistic approach of decision making, in order to satisfy the needs of the situation and reach the objectives of the initial action in the accident scenario.

Lessons Learned for Collaborative Clinical Content Development

PubMed Central

Collins, S.A.; Bavuso, K.; Zuccotti, G.; Rocha, R.A.

2013-01-01

Background Site-specific content configuration of vendor-based Electronic Health Records (EHRs) is a vital step in the development of standardized and interoperable content that can be used for clinical decision-support, reporting, care coordination, and information exchange. The multi-site, multi-stakeholder Acute Care Documentation (ACD) project at Partners Healthcare Systems (PHS) aimed to develop highly structured clinical content with adequate breadth and depth to meet the needs of all types of acute care clinicians at two academic medical centers. The Knowledge Management (KM) team at PHS led the informatics and knowledge management effort for the project. Objectives We aimed to evaluate the role, governance, and project management processes and resources for the KM team’s effort as part of the standardized clinical content creation. Methods We employed the Center for Disease Control’s six step Program Evaluation Framework to guide our evaluation steps. We administered a forty-four question, open-ended, semi-structured voluntary survey to gather focused, credible evidence from members of the KM team. Qualitative open-coding was performed to identify themes for lessons learned and concluding recommendations. Results Six surveys were completed. Qualitative data analysis informed five lessons learned and thirty specific recommendations associated with the lessons learned. The five lessons learned are: 1) Assess and meet knowledge needs and set expectations at the start of the project; 2) Define an accountable decision-making process; 3) Increase team meeting moderation skills; 4) Ensure adequate resources and competency training with online asynchronous collaboration tools; 5) Develop focused, goal-oriented teams and supportive, consultative service based teams. Conclusions Knowledge management requirements for the development of standardized clinical content within a vendor-based EHR among multi-stakeholder teams and sites include: 1) assessing and meeting informatics knowledge needs, 2) setting expectations and standardizing the process for decision-making, and 3) ensuring the availability of adequate resources and competency training. PMID:23874366

Evolutionary Agent-based Models to design distributed water management strategies

NASA Astrophysics Data System (ADS)

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

2012-12-01

There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a synthetic case study, representing a Y-shaped system composed by two regulated lakes, whose releases merge just upstream of a city. Each reservoir is operated by an agent in order to prevent floods along the lake shores (local objective). However, the optimal operation of the reservoirs with respect to the local objectives is conflicting with the minimization of floods in the city (global objective). The evolution of the Agent-based Model from individualistic management strategies of the reservoirs toward a global compromise that reduces the costs for the city is analysed.

Application of a Sensemaking Approach to Ethics Training in the Physical Sciences and Engineering

NASA Astrophysics Data System (ADS)

Kligyte, Vykinta; Marcy, Richard T.; Waples, Ethan P.; Sevier, Sydney T.; Godfrey, Elaine S.; Mumford, Michael D.; Hougen, Dean F.

2008-06-01

Integrity is a critical determinant of the effectiveness of research organizations in terms of producing high quality research and educating the new generation of scientists. A number of responsible conduct of research (RCR) training programs have been developed to address this growing organizational concern. However, in spite of a significant body of research in ethics training, it is still unknown which approach has the highest potential to enhance researchers' integrity. One of the approaches showing some promise in improving researchers' integrity has focused on the development of ethical decision-making skills. The current effort proposes a novel curriculum that focuses on broad metacognitive reasoning strategies researchers use when making sense of day-to-day social and professional practices that have ethical implications for the physical sciences and engineering. This sensemaking training has been implemented in a professional sample of scientists conducting research in electrical engineering, atmospheric and computer sciences at a large multi-cultural, multi-disciplinary, and multi-university research center. A pre-post design was used to assess training effectiveness using scenario-based ethical decision-making measures. The training resulted in enhanced ethical decision-making of researchers in relation to four ethical conduct areas, namely data management, study conduct, professional practices, and business practices. In addition, sensemaking training led to researchers' preference for decisions involving the application of the broad metacognitive reasoning strategies. Individual trainee and training characteristics were used to explain the study findings. Broad implications of the findings for ethics training development, implementation, and evaluation in the sciences are discussed.

Application of a sensemaking approach to ethics training in the physical sciences and engineering.

PubMed

Kligyte, Vykinta; Marcy, Richard T; Waples, Ethan P; Sevier, Sydney T; Godfrey, Elaine S; Mumford, Michael D; Hougen, Dean F

2008-06-01

Integrity is a critical determinant of the effectiveness of research organizations in terms of producing high quality research and educating the new generation of scientists. A number of responsible conduct of research (RCR) training programs have been developed to address this growing organizational concern. However, in spite of a significant body of research in ethics training, it is still unknown which approach has the highest potential to enhance researchers' integrity. One of the approaches showing some promise in improving researchers' integrity has focused on the development of ethical decision-making skills. The current effort proposes a novel curriculum that focuses on broad metacognitive reasoning strategies researchers use when making sense of day-to-day social and professional practices that have ethical implications for the physical sciences and engineering. This sensemaking training has been implemented in a professional sample of scientists conducting research in electrical engineering, atmospheric and computer sciences at a large multi-cultural, multi-disciplinary, and multi-university research center. A pre-post design was used to assess training effectiveness using scenario-based ethical decision-making measures. The training resulted in enhanced ethical decision-making of researchers in relation to four ethical conduct areas, namely data management, study conduct, professional practices, and business practices. In addition, sensemaking training led to researchers' preference for decisions involving the application of the broad metacognitive reasoning strategies. Individual trainee and training characteristics were used to explain the study findings. Broad implications of the findings for ethics training development, implementation, and evaluation in the sciences are discussed.

Cooperative Solutions in Multi-Person Quadratic Decision Problems: Finite-Horizon and State-Feedback Cost-Cumulant Control Paradigm

DTIC Science & Technology

2007-01-01

CONTRACT NUMBER Problems: Finite -Horizon and State-Feedback Cost-Cumulant Control Paradigm (PREPRINT) 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...cooperative cost-cumulant control regime for the class of multi-person single-objective decision problems characterized by quadratic random costs and... finite -horizon integral quadratic cost associated with a linear stochastic system . Since this problem formation is parameterized by the number of cost

A risk-based multi-objective model for optimal placement of sensors in water distribution system

NASA Astrophysics Data System (ADS)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value of losses in WDS.

A study protocol of the effectiveness of PEGASUS: a multi-centred study comparing an intervention to promote shared decision making about breast reconstruction with treatment as usual.

PubMed

Harcourt, Diana; Paraskeva, Nicole; White, Paul; Powell, Jane; Clarke, Alex

2017-10-02

Increasingly, women elect breast reconstruction after mastectomy. However, their expectations of surgery are often not met, and dissatisfaction with outcome and ongoing psychosocial concerns and distress are common. We developed a patient-centered intervention, PEGASUS:(Patients' Expectations and Goals: Assisting Shared Understanding of Surgery) which supports shared decision making by helping women clarify their own, individual goals about reconstruction so that they can discuss these with their surgeon. Our acceptability/feasibility work has shown it is well received by patients and health professionals alike. We now need to establish whether PEGASUS improves patients' experiences of breast reconstruction decision making and outcomes. The purpose of this study is, therefore, to examine the effectiveness of PEGASUS, an intervention designed to support shared decision making about breast reconstruction. A multi-centered sequential study will compare the impact of PEGASUS with usual care, in terms of patient reported outcomes (self-reported satisfaction with the outcome of surgery, involvement in decision making and in the consultation) and health economics. Initially we will collect data from our comparison (usual care) group (90 women) who will complete standardized measures (Breast-Q, EQ5D -5 L and ICECAP- A) at the time of decision making, 3, 6 and 12 months after surgery. Health professionals will then be trained to use PEGASUS, which will be delivered to the intervention group (another 90 women completing the same measures at the time of decision making, and 3, 6 and 12 months after surgery). Health professionals and a purposefully selected sample of participants will be interviewed about whether their expectations of reconstruction were met, and their experiences of PEGASUS (if appropriate). PEGASUS may have the potential to provide health professionals with an easily accessible tool aiming to support shared decision making and improve patients' satisfaction with breast reconstruction. Results of this study will be available at the end of 2019. ISRCTN 18000391 (DOI 10.1186/ISRCTN18000391) 27/01/2016.

Decision-making tool for applying adaptive traffic control systems : final report.

DOT National Transportation Integrated Search

2016-03-01

Adaptive traffic signal control technologies have been increasingly deployed in real world situations. The objective of this project was to develop a decision-making tool to guide traffic engineers and decision-makers who must decide whether or not a...

Knowledge translation strategies to improve the use of evidence in public health decision making in local government: intervention design and implementation plan

PubMed Central

2013-01-01

Background Knowledge translation strategies are an approach to increase the use of evidence within policy and practice decision-making contexts. In clinical and health service contexts, knowledge translation strategies have focused on individual behavior change, however the multi-system context of public health requires a multi-level, multi-strategy approach. This paper describes the design of and implementation plan for a knowledge translation intervention for public health decision making in local government. Methods Four preliminary research studies contributed findings to the design of the intervention: a systematic review of knowledge translation intervention effectiveness research, a scoping study of knowledge translation perspectives and relevant theory literature, a survey of the local government public health workforce, and a study of the use of evidence-informed decision-making for public health in local government. A logic model was then developed to represent the putative pathways between intervention inputs, processes, and outcomes operating between individual-, organizational-, and system-level strategies. This formed the basis of the intervention plan. Results The systematic and scoping reviews identified that effective and promising strategies to increase access to research evidence require an integrated intervention of skill development, access to a knowledge broker, resources and tools for evidence-informed decision making, and networking for information sharing. Interviews and survey analysis suggested that the intervention needs to operate at individual and organizational levels, comprising workforce development, access to evidence, and regular contact with a knowledge broker to increase access to intervention evidence; develop skills in appraisal and integration of evidence; strengthen networks; and explore organizational factors to build organizational cultures receptive to embedding evidence in practice. The logic model incorporated these inputs and strategies with a set of outcomes to measure the intervention’s effectiveness based on the theoretical frameworks, evaluation studies, and decision-maker experiences. Conclusion Documenting the design of and implementation plan for this knowledge translation intervention provides a transparent, theoretical, and practical approach to a complex intervention. It provides significant insights into how practitioners might engage with evidence in public health decision making. While this intervention model was designed for the local government context, it is likely to be applicable and generalizable across sectors and settings. Trial registration Australia New Zealand Clinical Trials Register ACTRN12609000953235. PMID:24107358

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

PubMed

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Research on the influence of parking charging strategy based on multi-level extension theory of group decision making

NASA Astrophysics Data System (ADS)

Cheng, Fen; Hu, Wanxin

2017-05-01

Based on analysis of the impact of the experience of parking policy at home and abroad, design the impact analysis process of parking strategy. First, using group decision theory to create a parking strategy index system and calculate its weight. Index system includes government, parking operators and travelers. Then, use a multi-level extension theory to analyze the CBD parking strategy. Assess the parking strategy by calculating the correlation of each indicator. Finally, assess the strategy of parking charges through a case. Provide a scientific and reasonable basis for assessing parking strategy. The results showed that the model can effectively analyze multi-target, multi-property parking policy evaluation.

The Defense Industrial Base: Prescription for a Psychosomatic Ailment

DTIC Science & Technology

1983-08-01

The Decision- Making Process ------------------------- 65 Notes ---------------------------------------- FIGURE 4-1. The Decision [laking Process...the strategy and tactics process to make certain that we can attain out national security objectives. (IFP is also known as mobilization planning or...decision- making model that could improve the capacity and capability-of the military-industrial complex, thereby increasing the probability of success

78 FR 58160 - Certification Process for State Capital Counsel System

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-23

... make such independent assessments in the context of making certification decisions under chapter 154... decisions concerning the objectives of representation,'' ABA Model Rule 1.2(a), making it difficult to... certification procedures. The Attorney General determined that chapter 154 gave him greater discretion in making...

Producing regionally-relevant multiobjective tradeoffs to engage with Colorado water managers

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Basdekas, L.; Dilling, L.

2016-12-01

Disseminating results from water resources systems analysis research can be challenging when there are political or regulatory barriers associated with real-world models, or when a research model does not incorporate management context to which practitioners can relate. As part of a larger transdisciplinary study, we developed a broadly-applicable case study in collaboration with our partners at six diverse water utilities in the Front Range of Colorado, USA. Our model, called the "Eldorado Utility Planning Model", incorporates realistic water management decisions and objectives and achieves a pragmatic balance between system complexity and simplicity. Using the sophisticated modeling platform RiverWare, we modeled a spatially distributed regional network in which, under varying climate scenarios, the Eldorado Utility can meet growing demand from its variety of sources and by interacting with other users in the network. In accordance with complicated Front Range water laws, ownership, priority of use, and restricted uses of water are tracked through RiverWare's accounting functionality. To achieve good system performance, Eldorado can make decisions such as expand/build a reservoir, purchase rights from one or more actors, and enact conservation. This presentation introduces the model, and motivates how it can be used to aid researchers in developing multi-objective evolutionary algorithm (MOEA)-based optimization for similar multi-reservoir systems in Colorado and the Western US. Within the optimization, system performance is quantified by 5 objectives: minimizing time in restrictions; new storage capacity; newly developed supply; and uncaptured water; and maximizing year-end storage. Our results demonstrate critical tradeoffs between the objectives and show how these tradeoffs are affected by several realistic climate change scenarios. These results were used within an interactive workshop that helped demonstrate the application of MOEA-based optimization for water management in the western US.

Fuzzy-based decision strategy in real-time strategic games

NASA Astrophysics Data System (ADS)

Volna, Eva

2017-11-01

The aim of this article is to describe our own gaming artificial intelligence for OpenTTD, which is a real-time building strategy game. A multi-agent system with fuzzy decision-making was used for the proposal itself. The multiagent system was chosen because real-time strategy games achieve great complexity and require decomposition of the problem into individual problems, which are then solved by individual cooperating agents. The system becomes then more stable and easily expandable. The fuzzy approach makes the decision-making process of strategies easier thanks to the use of uncertainty. In the conclusion, own experimental results were compared with other approaches.

A systematic approach for watershed ecological restoration strategy making: An application in the Taizi River Basin in northern China.

PubMed

Li, Mengdi; Fan, Juntao; Zhang, Yuan; Guo, Fen; Liu, Lusan; Xia, Rui; Xu, Zongxue; Wu, Fengchang

2018-05-15

Aiming to protect freshwater ecosystems, river ecological restoration has been brought into the research spotlight. However, it is challenging for decision makers to set appropriate objectives and select a combination of rehabilitation acts from numerous possible solutions to meet ecological, economic, and social demands. In this study, we developed a systematic approach to help make an optimal strategy for watershed restoration, which incorporated ecological security assessment and multi-objectives optimization (MOO) into the planning process to enhance restoration efficiency and effectiveness. The river ecological security status was evaluated by using a pressure-state-function-response (PSFR) assessment framework, and MOO was achieved by searching for the Pareto optimal solutions via Non-dominated Sorting Genetic Algorithm II (NSGA-II) to balance tradeoffs between different objectives. Further, we clustered the searched solutions into three types in terms of different optimized objective function values in order to provide insightful information for decision makers. The proposed method was applied in an example rehabilitation project in the Taizi River Basin in northern China. The MOO result in the Taizi River presented a set of Pareto optimal solutions that were classified into three types: I - high ecological improvement, high cost and high benefits solution; II - medial ecological improvement, medial cost and medial economic benefits solution; III - low ecological improvement, low cost and low economic benefits solution. The proposed systematic approach in our study can enhance the effectiveness of riverine ecological restoration project and could provide valuable reference for other ecological restoration planning. Copyright © 2018 Elsevier B.V. All rights reserved.

Image Mining in Remote Sensing for Coastal Wetlands Mapping: from Pixel Based to Object Based Approach

NASA Astrophysics Data System (ADS)

Farda, N. M.; Danoedoro, P.; Hartono; Harjoko, A.

2016-11-01

The availably of remote sensing image data is numerous now, and with a large amount of data it makes “knowledge gap” in extraction of selected information, especially coastal wetlands. Coastal wetlands provide ecosystem services essential to people and the environment. The aim of this research is to extract coastal wetlands information from satellite data using pixel based and object based image mining approach. Landsat MSS, Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI images located in Segara Anakan lagoon are selected to represent data at various multi temporal images. The input for image mining are visible and near infrared bands, PCA band, invers PCA bands, mean shift segmentation bands, bare soil index, vegetation index, wetness index, elevation from SRTM and ASTER GDEM, and GLCM (Harralick) or variability texture. There is three methods were applied to extract coastal wetlands using image mining: pixel based - Decision Tree C4.5, pixel based - Back Propagation Neural Network, and object based - Mean Shift segmentation and Decision Tree C4.5. The results show that remote sensing image mining can be used to map coastal wetlands ecosystem. Decision Tree C4.5 can be mapped with highest accuracy (0.75 overall kappa). The availability of remote sensing image mining for mapping coastal wetlands is very important to provide better understanding about their spatiotemporal coastal wetlands dynamics distribution.

The role of public communication in decision making for waste management infrastructure.

PubMed

Kirkman, Richard; Voulvoulis, Nikolaos

2017-12-01

Modern waste management provision seeks to meet challenging objectives and strategies while reflecting community aspirations and ensuring cost-effective compliance with statutory obligations. Its social acceptability, which affects both what systems (infrastructure) can be put in place and to what extent their implementation will be successful, is a multi-dimensional phenomenon, often not well understood. In light of the growing evidence that decisions to build new infrastructure are often contested by the public, there is a clear need to understand the role of scientific evidence in public perception, particularly as environmental infrastructure delivery is often objected to by the public on environmental grounds. In this paper the need for waste management infrastructure is reviewed, and the way its delivery in the UK has evolved is used as an example of the role of public perception in the planning and delivery of waste facilities. Findings demonstrate the vital role of public communication in waste management infrastructure delivery. Public perception must be taken into account early in the decision making process, with the public informed and engaged from the start. There is a pressing need for people not simply to accept but to understand and appreciate the need for infrastructure, the nature of infrastructure investments and development, the costs and the benefits involved, and the technological aspects. Scientific evidence and literacy have a critical role to play, facilitating public engagement in a process that empowers people, allowing them to define and handle challenges and influence decisions that will impact their lives. Problem ownership, and an increased probability of any solutions proposed being selected and implemented successfully are potential benefits of such approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

NASA Astrophysics Data System (ADS)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

Family involvement in medical decision-making: Perceptions of nursing and psychology students.

PubMed

Itzhaki, Michal; Hildesheimer, Galya; Barnoy, Sivia; Katz, Michael

2016-05-01

Family members often rely on health care professionals to guide and support them through the decision-making process. Although family involvement in medical decisions should be included in the preservice curriculum for the health care professions, perceptions of students in caring professions on family involvement in medical decision-making have not yet been examined. To examine the perceptions of nursing and psychology students on family involvement in medical decision-making for seriously ill patients. A descriptive cross-sectional design was used. First year undergraduate nursing and psychology students studying for their Bachelor of Arts degree were recruited. Perceptions were assessed with a questionnaire constructed based on the Multi-Attribute Utility Theory (MAUT), which examines decision-maker preferences. The questionnaire consisted of two parts referring to the respondent once as the patient and then as the family caregiver. Questionnaires were completed by 116 nursing students and 156 psychology students. Most were of the opinion that family involvement in decision-making is appropriate, especially when the patient is incapable of making decisions. Nursing students were more inclined than psychology students to think that financial, emotional, and value-based considerations should be part of the family's involvement in decision-making. Both groups of students perceived the emotional consideration as most acceptable, whereas the financial consideration was considered the least acceptable. Nursing and psychology students perceive family involvement in medical decision-making as appropriate. In order to train students to support families in the process of decision-making, further research should examine Shared Decision-Making (SDM) programs, which involve patient and clinician collaboration in health care decisions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Patient involvement in decision-making: a cross-sectional study in a Malaysian primary care clinic

PubMed Central

Ambigapathy, Ranjini; Ng, Chirk Jenn

2016-01-01

Objective Shared decision-making has been advocated as a useful model for patient management. In developing Asian countries such as Malaysia, there is a common belief that patients prefer a passive role in clinical consultation. As such, the objective of this study was to determine Malaysian patients’ role preference in decision-making and the associated factors. Design A cross-sectional study. Setting Study was conducted at an urban primary care clinic in Malaysia in 2012. Participants Patients aged >21 years were chosen using systematic random sampling. Methods Consenting patients answered a self-administered questionnaire, which included demographic data and their preferred and actual role before and after consultation. Doctors were asked to determine patients’ role preference. The Control Preference Scale was used to assess patients’ role preference. Primary outcome Prevalence of patients’ preferred role in decision-making. Secondary outcomes (1) Actual role played by the patient in decision-making. (2) Sociodemographic factors associated with patients’ preferred role in decision-making. (3) Doctors’ perception of patients’ involvement in decision-making. Results The response rate was 95.1% (470/494). Shared decision-making was preferred by 51.9% of patients, followed by passive (26.3%) and active (21.8%) roles in decision-making. Higher household income was significantly associated with autonomous role preference (p=0.018). Doctors’ perception did not concur with patients’ preferred role. Among patients whom doctors perceived to prefer a passive role, 73.5% preferred an autonomous role (p=0.900, κ=0.006). Conclusions The majority of patients attending the primary care clinic preferred and played an autonomous role in decision-making. Doctors underestimated patients’ preference to play an autonomous role. PMID:26729393

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.

Decision problems in management of construction projects

NASA Astrophysics Data System (ADS)

Szafranko, E.

2017-10-01

In a construction business, one must oftentimes make decisions during all stages of a building process, from planning a new construction project through its execution to the stage of using a ready structure. As a rule, the decision making process is made more complicated due to certain conditions specific for civil engineering. With such diverse decision situations, it is recommended to apply various decision making support methods. Both, literature and hands-on experience suggest several methods based on analytical and computational procedures, some less and some more complex. This article presents the methods which can be helpful in supporting decision making processes in the management of civil engineering projects. These are multi-criteria methods, such as MCE, AHP or indicator methods. Because the methods have different advantages and disadvantages, whereas decision situations have their own specific nature, a brief summary of the methods alongside some recommendations regarding their practical applications has been given at the end of the paper. The main aim of this article is to review the methods of decision support and their analysis for possible use in the construction industry.

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.

The use of Ethics Decision-Making Frameworks by Canadian Ethics Consultants: A Qualitative Study.

PubMed

Kaposy, Chris; Brunger, Fern; Maddalena, Victor; Singleton, Richard

2016-10-01

In this study, Canadian healthcare ethics consultants describe their use of ethics decision-making frameworks. Our research finds that ethics consultants in Canada use multi-purpose ethics decision-making frameworks, as well as targeted frameworks that focus on reaching an ethical resolution to a particular healthcare issue, such as adverse event reporting, or difficult triage scenarios. Several interviewees mention the influence that the accreditation process in Canadian healthcare organizations has on the adoption and use of such frameworks. Some of the ethics consultants we interviewed also report on their reluctance to use these tools. Limited empirical work has been done previously on the use of ethics decision-making frameworks. This study begins to fill this gap in our understanding of the work of healthcare ethics consultants. © 2016 John Wiley & Sons Ltd.

A sustainable manufacturing system design: A fuzzy multi-objective optimization model.

PubMed

Nujoom, Reda; Mohammed, Ahmed; Wang, Qian

2017-08-10

In the past decade, there has been a growing concern about the environmental protection in public society as governments almost all over the world have initiated certain rules and regulations to promote energy saving and minimize the production of carbon dioxide (CO 2 ) emissions in many manufacturing industries. The development of sustainable manufacturing systems is considered as one of the effective solutions to minimize the environmental impact. Lean approach is also considered as a proper method for achieving sustainability as it can reduce manufacturing wastes and increase the system efficiency and productivity. However, the lean approach does not include environmental waste of such as energy consumption and CO 2 emissions when designing a lean manufacturing system. This paper addresses these issues by evaluating a sustainable manufacturing system design considering a measurement of energy consumption and CO 2 emissions using different sources of energy (oil as direct energy source to generate thermal energy and oil or solar as indirect energy source to generate electricity). To this aim, a multi-objective mathematical model is developed incorporating the economic and ecological constraints aimed for minimization of the total cost, energy consumption, and CO 2 emissions for a manufacturing system design. For the real world scenario, the uncertainty in a number of input parameters was handled through the development of a fuzzy multi-objective model. The study also addresses decision-making in the number of machines, the number of air-conditioning units, and the number of bulbs involved in each process of a manufacturing system in conjunction with a quantity of material flow for processed products. A real case study was used for examining the validation and applicability of the developed sustainable manufacturing system model using the fuzzy multi-objective approach.

Decision Making in the Airplane

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Shafto, Michael G. (Technical Monitor)

1995-01-01

The Importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful In improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking In response to a problem, This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review

NASA Astrophysics Data System (ADS)

Uhde, Britta; Andreas Hahn, W.; Griess, Verena C.; Knoke, Thomas

2015-08-01

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.

Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review.

PubMed

Uhde, Britta; Hahn, W Andreas; Griess, Verena C; Knoke, Thomas

2015-08-01

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.

Decision technology.

PubMed

Edwards, W; Fasolo, B

2001-01-01

This review is about decision technology-the rules and tools that help us make wiser decisions. First, we review the three rules that are at the heart of most traditional decision technology-multi-attribute utility, Bayes' theorem, and subjective expected utility maximization. Since the inception of decision research, these rules have prescribed how we should infer values and probabilities and how we should combine them to make better decisions. We suggest how to make best use of all three rules in a comprehensive 19-step model. The remainder of the review explores recently developed tools of decision technology. It examines the characteristics and problems of decision-facilitating sites on the World Wide Web. Such sites now provide anyone who can use a personal computer with access to very sophisticated decision-aiding tools structured mainly to facilitate consumer decision making. It seems likely that the Web will be the mode by means of which decision tools will be distributed to lay users. But methods for doing such apparently simple things as winnowing 3000 options down to a more reasonable number, like 10, contain traps for unwary decision technologists. The review briefly examines Bayes nets and influence diagrams-judgment and decision-making tools that are available as computer programs. It very briefly summarizes the state of the art of eliciting probabilities from experts. It concludes that decision tools will be as important in the 21st century as spreadsheets were in the 20th.

An Ensemble-Based Forecasting Framework to Optimize Reservoir Releases

NASA Astrophysics Data System (ADS)

Ramaswamy, V.; Saleh, F.

2017-12-01

Increasing frequency of extreme precipitation events are stressing the need to manage water resources on shorter timescales. Short-term management of water resources becomes proactive when inflow forecasts are available and this information can be effectively used in the control strategy. This work investigates the utility of short term hydrological ensemble forecasts for operational decision making during extreme weather events. An advanced automated hydrologic prediction framework integrating a regional scale hydrologic model, GIS datasets and the meteorological ensemble predictions from the European Center for Medium Range Weather Forecasting (ECMWF) was coupled to an implicit multi-objective dynamic programming model to optimize releases from a water supply reservoir. The proposed methodology was evaluated by retrospectively forecasting the inflows to the Oradell reservoir in the Hackensack River basin in New Jersey during the extreme hydrologic event, Hurricane Irene. Additionally, the flexibility of the forecasting framework was investigated by forecasting the inflows from a moderate rainfall event to provide important perspectives on using the framework to assist reservoir operations during moderate events. The proposed forecasting framework seeks to provide a flexible, assistive tool to alleviate the complexity of operational decision-making.

Choosing an Advanced Therapy in Parkinson's Disease; is it an Evidence-Based Decision in Current Practice?

PubMed

Nijhuis, Frouke A P; van Heek, Jolien; Bloem, Bastiaan R; Post, Bart; Faber, Marjan J

2016-07-25

In advanced Parkinson's disease (PD), neurologists and patients face a complex decision for an advanced therapy. When choosing a treatment, the best available evidence should be combined with the professional's expertise and the patient's preferences. The objective of this study was to explore current decision-making in advanced PD. We conducted focus group discussions and individual interviews with patients (N = 20) who had received deep brain stimulation, Levodopa-Carbidopa intestinal gel, or subcutaneous apomorphine infusion, and with their caregivers (N = 16). Furthermore, we conducted semi-structured interviews with neurologists (N = 7) and PD nurse specialists (N = 3) to include the perspectives of all key players in this decision-making process. Data were analyzed by two researchers using a qualitative thematic analysis approach. Four themes representing current experiences with the decision-making process were identified: 1) information and information needs, 2) factors influencing treatment choice and individual decision strategies, 3) decision-making roles, and 4) barriers and facilitators to shared decision-making (SDM). Patient preferences were taken into account, however patients were not always provided with adequate information. The professional's expertise influenced the decision-making process in both positive and negative ways. Although professionals and patients considered SDM essential for the decision of an advanced treatment, they mentioned several barriers for the implementation in current practice. In this study we found several factors explaining why in current practice, evidence-based decision-making in advanced PD is not optimal. An important first step would be to develop objective information on all treatment options.

Ignorance- versus evidence-based decision making: a decision time analysis of the recognition heuristic.

PubMed

Hilbig, Benjamin E; Pohl, Rüdiger F

2009-09-01

According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments-and its duration-is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of evidence speaking for each of the objects and that decision times thus depend on the evidential difference between objects, or the degree of conflict between options. This article presents 3 experiments that tested predictions derived from the RH against those from alternative models. All experiments used naturally recognized objects without teaching participants any information and thus provided optimal conditions for application of the RH. However, results supported the alternative, evidence-based models and often conflicted with the RH. Recognition was not the key determinant of decision times, whereas differences between objects with respect to (both positive and negative) evidence predicted effects well. In sum, alternative models that allow for the integration of different pieces of information may well provide a better account of comparative judgments. (c) 2009 APA, all rights reserved.

Designing and evaluating an interprofessional shared decision-making and goal-setting decision aid for patients with diabetes in clinical care - systematic decision aid development and study protocol

PubMed Central

2014-01-01

Background Care of patients with diabetes often occurs in the context of other chronic illness. Competing disease priorities and competing patient-physician priorities present challenges in the provision of care for the complex patient. Guideline implementation interventions to date do not acknowledge these intricacies of clinical practice. As a result, patients and providers are left overwhelmed and paralyzed by the sheer volume of recommendations and tasks. An individualized approach to the patient with diabetes and multiple comorbid conditions using shared decision-making (SDM) and goal setting has been advocated as a patient-centred approach that may facilitate prioritization of treatment options. Furthermore, incorporating interprofessional integration into practice may overcome barriers to implementation. However, these strategies have not been taken up extensively in clinical practice. Objectives To systematically develop and test an interprofessional SDM and goal-setting toolkit for patients with diabetes and other chronic diseases, following the Knowledge to Action framework. Methods 1. Feasibility study: Individual interviews with primary care physicians, nurses, dietitians, pharmacists, and patients with diabetes will be conducted, exploring their experiences with shared decision-making and priority-setting, including facilitators and barriers, the relevance of a decision aid and toolkit for priority-setting, and how best to integrate it into practice. 2. Toolkit development: Based on this data, an evidence-based multi-component SDM toolkit will be developed. The toolkit will be reviewed by content experts (primary care, endocrinology, geriatricians, nurses, dietitians, pharmacists, patients) for accuracy and comprehensiveness. 3. Heuristic evaluation: A human factors engineer will review the toolkit and identify, list and categorize usability issues by severity. 4. Usability testing: This will be done using cognitive task analysis. 5. Iterative refinement: Throughout the development process, the toolkit will be refined through several iterative cycles of feedback and redesign. Discussion Interprofessional shared decision-making regarding priority-setting with the use of a decision aid toolkit may help prioritize care of individuals with multiple comorbid conditions. Adhering to principles of user-centered design, we will develop and refine a toolkit to assess the feasibility of this approach. PMID:24450385

Putting Families in the Center: Family Perspectives on Decision Making and ADHD and Implications for ADHD Care

ERIC Educational Resources Information Center

Davis, Catherine C.; Claudius, Milena; Palinkas, Lawrence A.; Wong, John B.; Leslie, Laurel K.

2012-01-01

Objective: To examine components of family-centered care in families' stories about treatment decision making for their child with ADHD. Method: Twenty-eight families participated in qualitative interviews that addressed families' perspectives on (a) the treatment decision-making process, (b) the cause and impact of their child's symptoms, and (c)…

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.

Application of the fuzzy topsis multi-attribute decision making method to determine scholarship recipients

NASA Astrophysics Data System (ADS)

Irvanizam, I.

2018-03-01

Some scholarships have been routinely offered by Ministry of Research, Technology and Higher Education of the Republic of Indonesia for students at Syiah Kuala University. In reality, the scholarship selection process is becoming subjective and highly complex problem. Multi-Attribute Decision Making (MADM) techniques can be a solution in order to solve scholarship selection problem. In this study, we demonstrated the application of a fuzzy TOPSIS as an MADM technique by using a numerical example in order to calculate a triangular fuzzy number for the fuzzy data onto a normalized weight. We then use this normalized value to construct the normalized fuzzy decision matrix. We finally use the fuzzy TOPSIS to rank alternatives in descending order based on the relative closeness to the ideal solution. The result in terms of final ranking shows slightly different from the previous work.

[Involving patients, the insured and the general public in healthcare decision making].

PubMed

Mühlbacher, Axel C; Juhnke, Christin

2016-01-01

No doubt, the public should be involved in healthcare decision making, especially when decision makers from politics and self-government agencies are faced with the difficult task of setting priorities. There is a general consensus on the need for a stronger patient centeredness, even in HTA processes, and internationally different ways of public participation are discussed and tested in decision making processes. This paper describes how the public can be involved in different decision situations, and it shows how preference measurement methods are currently being used in an international context to support decision making. It distinguishes between different levels of decision making on health technologies: approval, assessment, pricing, and finally utilization. The range of participation efforts extends from qualitative surveys of patients' needs (Citizen Councils of NICE in the UK) to science-based documentation of quantitative patient preferences, such as in the current pilot projects of the FDA in the US and the EMA at the European level. Possible approaches for the elicitation and documentation of preference structures and trade-offs in relation to alternate health technologies are decision aids, such as multi-criteria decision analysis (MCDA), that provide the necessary information for weighting and prioritizing decision criteria. Copyright © 2015. Published by Elsevier GmbH.

Designing and Evaluating Participatory Cyber-Infrastructure Systems for Multi-Scale Citizen Science

ERIC Educational Resources Information Center

Newman, Gregory J.

2010-01-01

Widespread and continuous spatial and temporal environmental data is essential for effective environmental monitoring, sustainable natural resource management, and ecologically responsible decisions. Our environmental monitoring, data management and reporting enterprise is not matched to current problems, concerns, and decision-making needs.…

Impact of Decision Criteria on Federal Aviation Administration Certification of Military Commercial Derivative Aircraft

DTIC Science & Technology

2012-03-01

Capt Low was a member of the Sigma Iota Epsilon professional management fraternity. He has performed as an on-equipment and off-equipment...FAA Certification, Military Commercial Derivative Aircraft, Multi-Attribute Decision Making 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

Ignorance- versus Evidence-Based Decision Making: A Decision Time Analysis of the Recognition Heuristic

ERIC Educational Resources Information Center

Hilbig, Benjamin E.; Pohl, Rudiger F.

2009-01-01

According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments--and its duration--is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of…

Decision Making in Action: Applying Research to Practice

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Hart, Sandra G. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment: Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

Shared decision-making in medical encounters regarding breast cancer treatment: the contribution of methodological triangulation.

PubMed

Durif-Bruckert, C; Roux, P; Morelle, M; Mignotte, H; Faure, C; Moumjid-Ferdjaoui, N

2015-07-01

The aim of this study on shared decision-making in the doctor-patient encounter about surgical treatment for early-stage breast cancer, conducted in a regional cancer centre in France, was to further the understanding of patient perceptions on shared decision-making. The study used methodological triangulation to collect data (both quantitative and qualitative) about patient preferences in the context of a clinical consultation in which surgeons followed a shared decision-making protocol. Data were analysed from a multi-disciplinary research perspective (social psychology and health economics). The triangulated data collection methods were questionnaires (n = 132), longitudinal interviews (n = 47) and observations of consultations (n = 26). Methodological triangulation revealed levels of divergence and complementarity between qualitative and quantitative results that suggest new perspectives on the three inter-related notions of decision-making, participation and information. Patients' responses revealed important differences between shared decision-making and participation per se. The authors note that subjecting patients to a normative behavioural model of shared decision-making in an era when paradigms of medical authority are shifting may undermine the patient's quest for what he or she believes is a more important right: a guarantee of the best care available. © 2014 John Wiley & Sons Ltd.

Decision Making on the Labor and Delivery Unit: An Investigation of Influencing Factors.

PubMed

Gregory, Megan E; Sonesh, Shirley C; Feitosa, Jennifer; Benishek, Lauren E; Hughes, Ashley M; Salas, Eduardo

2017-09-01

Objective The aim of this study was to describe the relationship between negative affect (NA), decision-making style, time stress, and decision quality in health care. Background Health care providers must often make swift, high-stakes decisions. Influencing factors of the decision-making process in this context have been understudied. Method Within a sample of labor and delivery nurses, physicians, and allied personnel, we used self-report measures to examine the impact of trait factors, including NA, decision-making style, and perceived time stress, on decision quality in a situational judgment test (Study 1). In Study 2, we observed the influence of state NA, state decision-making style, state time stress, and their relationship with decision quality on real clinical decisions. Results In Study 1, we found that trait NA significantly predicted avoidant decision-making style. Furthermore, those who were higher on trait time stress and trait avoidant decision-making style exhibited poorer decisions. In Study 2, we observed associations between state NA with state avoidant and analytical decision-making styles. We also observed that these decision-making styles, when considered in tandem with time stress, were influential in predicting clinical decision quality. Conclusion NA predicts some decision-making styles, and decision-making style can affect decision quality under time stress. This is particularly true for state factors. Application Individual differences, such as affect and decision-making style, should be considered during selection. Training to reduce time stress perceptions should be provided.

Applying a multi-replication framework to support dynamic situation assessment and predictive capabilities

NASA Astrophysics Data System (ADS)

Lammers, Craig; McGraw, Robert M.; Steinman, Jeffrey S.

2005-05-01

Technological advances and emerging threats reduce the time between target detection and action to an order of a few minutes. To effectively assist with the decision-making process, C4I decision support tools must quickly and dynamically predict and assess alternative Courses Of Action (COAs) to assist Commanders in anticipating potential outcomes. These capabilities can be provided through the faster-than-real-time predictive simulation of plans that are continuously re-calibrating with the real-time picture. This capability allows decision-makers to assess the effects of re-tasking opportunities, providing the decision-maker with tremendous freedom to make time-critical, mid-course decisions. This paper presents an overview and demonstrates the use of a software infrastructure that supports DSAP capabilities. These DSAP capabilities are demonstrated through the use of a Multi-Replication Framework that supports (1) predictivie simulations using JSAF (Joint Semi-Automated Forces); (2) real-time simulation, also using JSAF, as a state estimation mechanism; and, (3) real-time C4I data updates through TBMCS (Theater Battle Management Core Systems). This infrastructure allows multiple replications of a simulation to be executed simultaneously over a grid faster-than-real-time, calibrated with live data feeds. A cost evaluator mechanism analyzes potential outcomes and prunes simulations that diverge from the real-time picture. In particular, this paper primarily serves to walk a user through the process for using the Multi-Replication Framework providing an enhanced decision aid.

Competence and Quality in Real-Life Decision Making.

PubMed

Geisler, Martin; Allwood, Carl Martin

2015-01-01

What distinguishes a competent decision maker and how should the issue of decision quality be approached in a real-life context? These questions were explored in three studies. In Study 1, using a web-based questionnaire and targeting a community sample, we investigated the relationships between objective and subjective indicators of real-life decision-making success. In Study 2 and 3, targeting two different samples of professionals, we explored if the prevalent cognitively oriented definition of decision-making competence could be beneficially expanded by adding aspects of competence in terms of social skills and time-approach. The predictive power for each of these three aspects of decision-making competence was explored for different indicators of real-life decision-making success. Overall, our results suggest that research on decision-making competence would benefit by expanding the definition of competence, by including decision-related abilities in terms of social skills and time-approach. Finally, the results also indicate that individual differences in real-life decision-making success profitably can be approached and measured by different criteria.

Conceptual and Empirical Approaches to Financial Decision-making by Older Adults: Results from a Financial Decision-Making Rating Scale

PubMed Central

Lichtenberg, Peter A.; Ocepek-Welikson, Katja; Ficker, Lisa J.; Gross, Evan; Rahman-Filipiak, Analise; Teresi, Jeanne A.

2017-01-01

Objectives The objectives of this study were threefold: (1) to empirically test the conceptual model proposed by the Lichtenberg Financial Decision Rating Scale (LFDRS); (2) to examine the psychometric properties of the LFDRS contextual factors in financial decision-making by investigating both the reliability and convergent validity of the subscales and total scale, and (3) extending previous work on the scale through the collection of normative data on financial decision-making. Methods A convenience sample of 200 independent function and community dwelling older adults underwent cognitive and financial management testing and were interviewed using the LFDRS. Confirmatory factor analysis, internal consistency measures, and hierarchical regression were used in a sample of 200 community-dwelling older adults, all of whom were making or had recently made a significant financial decision. Results Results confirmed the scale’s reliability and supported the conceptual model. Convergent validity analyses indicate that as hypothesized, cognition is a significant predictor of risk scores. Financial management scores, however, were not predictive of decision-making risk scores. Conclusions The psychometric properties of the LFDRS support the scale’s use as it was proposed in Lichtenberg et al., 2015. Clinical Implications The LFDRS instructions and scale are provided for clinicians to use in financial capacity assessments. PMID:29077531

A multiobjective modeling approach to locate multi-compartment containers for urban-sorted waste

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

Tralhao, Lino, E-mail: lmlrt@inescc.p; Coutinho-Rodrigues, Joao, E-mail: coutinho@dec.uc.p; Alcada-Almeida, Luis, E-mail: alcada@inescc.p

2010-12-15

The location of multi-compartment sorted waste containers for recycling purposes in cities is an important problem in the context of urban waste management. The costs associated with those facilities and the impacts placed on populations are important concerns. This paper introduces a mixed-integer, multiobjective programming approach to identify the locations and capacities of such facilities. The approach incorporates an optimization model in a Geographical Information System (GIS)-based interactive decision support system that includes four objectives. The first objective minimizes the total investment cost; the second one minimizes the average distance from dwellings to the respective multi-compartment container; the last twomore » objectives address the 'pull' and 'push' characteristics of the decision problem, one by minimizing the number of individuals too close to any container, and the other by minimizing the number of dwellings too far from the respective multi-compartment container. The model determines the number of facilities to be opened, the respective container capacities, their locations, their respective shares of the total waste of each type to be collected, and the dwellings assigned to each facility. The approach proposed was tested with a case study for the historical center of Coimbra city, Portugal, where a large urban renovation project, addressing about 800 buildings, is being undertaken. This paper demonstrates that the models and techniques incorporated in the interactive decision support system (IDSS) can be used to assist a decision maker (DM) in analyzing this complex problem in a realistically sized urban application. Ten solutions consisting of different combinations of underground containers for the disposal of four types of sorted waste in 12 candidate sites, were generated. These solutions and tradeoffs among the objectives are presented to the DM via tables, graphs, color-coded maps and other graphics. The DM can then use this information to 'guide' the IDSS in identifying additional solutions of potential interest. Nevertheless, this research showed that a particular solution with a better objective balance can be identified. The actual sequence of additional solutions generated will depend upon the objectives and preferences of the DM in a specific application.« less

Building resilience to weather-related hazards through better preparedness

NASA Astrophysics Data System (ADS)

Keller, Julia; Golding, Brian; Johnston, David; Ruti, Paolo

2017-04-01

Recent developments in weather forecasting have transformed our ability to predict weather-related hazards, while mobile communication is radically changing the way that people receive information. At the same time, vulnerability to weather-related hazards is growing through urban expansion, population growth and climate change. This talk will address issues facing the science community in responding to the Sendai Framework objective to "substantially increase the availability of and access to multi-hazard early warning systems" in the context of weather-related hazards. It will also provide an overview of activities and approaches developed in the World Meteorological Organisation's High Impact Weather (HIWeather) project. HIWeather has identified and is promoting research in key multi-disciplinary gaps in our knowledge, including in basic meteorology, risk prediction, communication and decision making, that affect our ability to provide effective warnings. The results will be pulled together in demonstration projects that will both showcase leading edge capability and build developing country capacity.

Multi-criteria development and incorporation into decision tools for health technology adoption.

PubMed

Poulin, Paule; Austen, Lea; Scott, Catherine M; Waddell, Cameron D; Dixon, Elijah; Poulin, Michelle; Lafrenière, René

2013-01-01

When introducing new health technologies, decision makers must integrate research evidence with local operational management information to guide decisions about whether and under what conditions the technology will be used. Multi-criteria decision analysis can support the adoption or prioritization of health interventions by using criteria to explicitly articulate the health organization's needs, limitations, and values in addition to evaluating evidence for safety and effectiveness. This paper seeks to describe the development of a framework to create agreed-upon criteria and decision tools to enhance a pre-existing local health technology assessment (HTA) decision support program. The authors compiled a list of published criteria from the literature, consulted with experts to refine the criteria list, and used a modified Delphi process with a group of key stakeholders to review, modify, and validate each criterion. In a workshop setting, the criteria were used to create decision tools. A set of user-validated criteria for new health technology evaluation and adoption was developed and integrated into the local HTA decision support program. Technology evaluation and decision guideline tools were created using these criteria to ensure that the decision process is systematic, consistent, and transparent. This framework can be used by others to develop decision-making criteria and tools to enhance similar technology adoption programs. The development of clear, user-validated criteria for evaluating new technologies adds a critical element to improve decision-making on technology adoption, and the decision tools ensure consistency, transparency, and real-world relevance.

Quantifying Risk of Financial Incapacity and Financial Exploitation in Community-dwelling Older Adults: Utility of a Scoring System for the Lichtenberg Financial Decision-making Rating Scale.

PubMed

Lichtenberg, Peter A; Gross, Evan; Ficker, Lisa J

2018-06-08

This work examines the clinical utility of the scoring system for the Lichtenberg Financial Decision-making Rating Scale (LFDRS) and its usefulness for decision making capacity and financial exploitation. Objective 1 was to examine the clinical utility of a person centered, empirically supported, financial decision making scale. Objective 2 was to determine whether the risk-scoring system created for this rating scale is sufficiently accurate for the use of cutoff scores in cases of decisional capacity and cases of suspected financial exploitation. Objective 3 was to examine whether cognitive decline and decisional impairment predicted suspected financial exploitation. Two hundred independently living, non-demented community-dwelling older adults comprised the sample. Participants completed the rating scale and other cognitive measures. Receiver operating characteristic curves were in the good to excellent range for decisional capacity scoring, and in the fair to good range for financial exploitation. Analyses supported the conceptual link between decision making deficits and risk for exploitation, and supported the use of the risk-scoring system in a community-based population. This study adds to the empirical evidence supporting the use of the rating scale as a clinical tool assessing risk for financial decisional impairment and/or financial exploitation.

Multilevel Evaluation Systems Project. Final Report.

ERIC Educational Resources Information Center

Herman, Joan L.

Several studies were conducted in 1987 by the Multilevel Evaluation Systems Project, which focuses on developing a model for a multi-purpose, multi-user evaluation system to facilitate educational decision making and evaluation. The project model emphasizes on-going integrated assessment of individuals, classes, and programs using a variety of…

Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

NASA Astrophysics Data System (ADS)

Lee, G.; Jun, K. S.; Cung, E. S.

2014-09-01

This study proposes an improved group decision making (GDM) framework that combines VIKOR method with fuzzified data to quantify the spatial flood vulnerability including multi-criteria evaluation indicators. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. Triangular fuzzy numbers are used to consider the uncertainty of weights and the crisp data of proxy variables. This approach can effectively propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the south Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the results from general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods, such as those developed by Borda, Condorcet, and Copeland. The evaluated priorities were significantly dependent on the employed decision-making method. The proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

Gis-Based Site Selection for Underground Natural Resources Using Fuzzy Ahp-Owa

NASA Astrophysics Data System (ADS)

Sabzevari, A. R.; Delavar, M. R.

2017-09-01

Fuel consumption has significantly increased due to the growth of the population. A solution to address this problem is the underground storage of natural gas. The first step to reach this goal is to select suitable places for the storage. In this study, site selection for the underground natural gas reservoirs has been performed using a multi-criteria decision-making in a GIS environment. The "Ordered Weighted Average" (OWA) operator is one of the multi-criteria decision-making methods for ranking the criteria and consideration of uncertainty in the interaction among the criteria. In this paper, Fuzzy AHP_OWA (FAHP_OWA) is used to determine optimal sites for the underground natural gas reservoirs. Fuzzy AHP_OWA considers the decision maker's risk taking and risk aversion during the decision-making process. Gas consumption rate, temperature, distance from main transportation network, distance from gas production centers, population density and distance from gas distribution networks are the criteria used in this research. Results show that the northeast and west of Iran and the areas around Tehran (Tehran and Alborz Provinces) have a higher attraction for constructing a natural gas reservoir. The performance of the used method was also evaluated. This evaluation was performed using the location of the existing natural gas reservoirs in the country and the site selection maps for each of the quantifiers. It is verified that the method used in this study is capable of modeling different decision-making strategies used by the decision maker with about 88 percent of agreement between the modeling and test data.

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

On multi-site damage identification using single-site training data

NASA Astrophysics Data System (ADS)

Barthorpe, R. J.; Manson, G.; Worden, K.

2017-11-01

This paper proposes a methodology for developing multi-site damage location systems for engineering structures that can be trained using single-site damaged state data only. The methodology involves training a sequence of binary classifiers based upon single-site damage data and combining the developed classifiers into a robust multi-class damage locator. In this way, the multi-site damage identification problem may be decomposed into a sequence of binary decisions. In this paper Support Vector Classifiers are adopted as the means of making these binary decisions. The proposed methodology represents an advancement on the state of the art in the field of multi-site damage identification which require either: (1) full damaged state data from single- and multi-site damage cases or (2) the development of a physics-based model to make multi-site model predictions. The potential benefit of the proposed methodology is that a significantly reduced number of recorded damage states may be required in order to train a multi-site damage locator without recourse to physics-based model predictions. In this paper it is first demonstrated that Support Vector Classification represents an appropriate approach to the multi-site damage location problem, with methods for combining binary classifiers discussed. Next, the proposed methodology is demonstrated and evaluated through application to a real engineering structure - a Piper Tomahawk trainer aircraft wing - with its performance compared to classifiers trained using the full damaged-state dataset.

Bi-Level Decision Making for Supporting Energy and Water Nexus

NASA Astrophysics Data System (ADS)

Zhang, X.; Vesselinov, V. V.

2016-12-01

The inseparable relationship between energy production and water resources has led to the emerging energy-water nexus concept, which provides a means for integrated management and decision making of these two critical resources. However, the energy-water nexus frequently involves decision makers with different and competing management objectives. Furthermore, there is a challenge that decision makers and stakeholders might be making decisions sequentially from a higher level to a lower level, instead of at the same decision level, whereby the objective of a decision maker at a higher level should be satisfied first. In this study, a bi-level decision model is advanced to handle such decision-making situations for managing the energy-water nexus. The work represents a unique contribution to developing an integrated decision-support framework/tool to quantify and analyze the tradeoffs between the two-level energy-water nexus decision makers. Here, plans for electricity generation, fuel supply, water supply, capacity expansion of the power plants and environmental impacts are optimized to provide effective decision support. The developed decision-support framework is implemented in Julia (a high-level, high-performance dynamic programming language for technical computing) and is a part of the MADS (Model Analyses & Decision Support) framework (http://mads.lanl.gov). To demonstrate the capabilities of the developed methodology, a series of analyses are performed for synthetic problems consistent with actual real-world energy-water nexus management problems.

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.

Pricing and location decisions in multi-objective facility location problem with M/M/m/k queuing systems

NASA Astrophysics Data System (ADS)

Tavakkoli-Moghaddam, Reza; Vazifeh-Noshafagh, Samira; Taleizadeh, Ata Allah; Hajipour, Vahid; Mahmoudi, Amin

2017-01-01

This article presents a new multi-objective model for a facility location problem with congestion and pricing policies. This model considers situations in which immobile service facilities are congested by a stochastic demand following M/M/m/k queues. The presented model belongs to the class of mixed-integer nonlinear programming models and NP-hard problems. To solve such a hard model, a new multi-objective optimization algorithm based on a vibration theory, namely multi-objective vibration damping optimization (MOVDO), is developed. In order to tune the algorithms parameters, the Taguchi approach using a response metric is implemented. The computational results are compared with those of the non-dominated ranking genetic algorithm and non-dominated sorting genetic algorithm. The outputs demonstrate the robustness of the proposed MOVDO in large-sized problems.

Placement decisions and disparities among aboriginal groups: an application of the decision making ecology through multi-level analysis.

PubMed

Fluke, John D; Chabot, Martin; Fallon, Barbara; MacLaurin, Bruce; Blackstock, Cindy

2010-01-01

This paper examined the relative influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. It tested the hypothesis that extraneous factors, specifically, organizational characteristics, impact the decision to place a child in out-of-home care. A secondary aim was to identify possible decision making influences related to disparities in placement decisions tied to Aboriginal children. Research suggests that the Aboriginal status of the child and structural risk factors affecting the family, such as poverty and poor housing, substantially account for this overrepresentation. The decision to place a child in out-of-home care was examined using data from the Canadian Incidence Study of Reported Child Abuse and Neglect. This child welfare dataset collected information about the results of nearly 5,000 child maltreatment investigations as well as a description of the characteristics of the workers and organization responsible for conducting those investigations. Multi-level statistical models were developed using MPlus software, which can accommodate dichotomous outcome variables, which are more reflective of decision making in child welfare. MPlus allows the specific case of the logistic link function for binary outcome variables under maximum likelihood estimation. Final models revealed the importance of the number of Aboriginal reports to an organization as a key second level predictor of the placement decision. It is the only second level factor that remains in the final model. This finding was very stable when tested over several different levels of proportionate caseload representation ranging from greater than 50% to 20% of the caseload. Disparities among Aboriginal children in child welfare decision making were identified at the agency level. The study provides additional evidence supporting the possibility that one source of overrepresentation of Aboriginal children in the Canadian foster care system is a lack of appropriate resources at the agency or community level. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

MULTI-SCALED VULNERABILITY ANALYSES: IMPROVING DECISION-MAKING AT REGIONAL TO LOCAL LEVELS THROUGH PARTNERSHIP

EPA Science Inventory

Decision-makers at all scales are faced with setting priorities for both use of limited resources and for risk management. While there are all kinds of monitoring data and models to project conditions at different spatial and temporal scales, synthesized information to establish ...

Investigation and design of a Project Management Decision Support System for the 4950th Test Wing.

DTIC Science & Technology

1986-03-01

all decision makers is the need for memory aids (reports, hand written notes, mental memory joggers, etc.). 4. Even in similar decision making ... memories to synthesize a decision- making process based on their individual styles, skills, and knowledge (Sprague, 1982: 106). Control mechanisms...representations shown in Figures 4.9 and 4.10 provide a means to this objective. By enabling a manager to make and record reasonable changes to

Group decision making with the analytic hierarchy process in benefit-risk assessment: a tutorial.

PubMed

Hummel, J Marjan; Bridges, John F P; IJzerman, Maarten J

2014-01-01

The analytic hierarchy process (AHP) has been increasingly applied as a technique for multi-criteria decision analysis in healthcare. The AHP can aid decision makers in selecting the most valuable technology for patients, while taking into account multiple, and even conflicting, decision criteria. This tutorial illustrates the procedural steps of the AHP in supporting group decision making about new healthcare technology, including (1) identifying the decision goal, decision criteria, and alternative healthcare technologies to compare, (2) structuring the decision criteria, (3) judging the value of the alternative technologies on each decision criterion, (4) judging the importance of the decision criteria, (5) calculating group judgments, (6) analyzing the inconsistency in judgments, (7) calculating the overall value of the technologies, and (8) conducting sensitivity analyses. The AHP is illustrated via a hypothetical example, adapted from an empirical AHP analysis on the benefits and risks of tissue regeneration to repair small cartilage lesions in the knee.

'The biggest thing is trying to live for two people': Spousal experiences of supporting decision-making participation for partners with TBI.

PubMed

Knox, Lucy; Douglas, Jacinta M; Bigby, Christine

2015-01-01

To understand how the spouses of individuals with severe TBI experience the process of supporting their partners with decision-making. This study adopted a constructivist grounded theory approach, with data consisting of in-depth interviews conducted with spouses over a 12-month period. Data were analysed through an iterative process of open and focused coding, identification of emergent categories and exploration of relationships between categories. Participants were four spouses of individuals with severe TBI (with moderate-severe disability). Spouses had shared committed relationships (marriage or domestic partnerships) for at least 4 years at initial interview. Three spouses were in relationships that had commenced following injury. Two main themes emerged from the data. The first identified the saliency of the relational space in which decision-making took place. The second revealed the complex nature of decision-making within the spousal relationship. Spouses experience decision-making as a complex multi-stage process underpinned by a number of relational factors. Increased understanding of this process can guide health professionals in their provision of support for couples in exploring decision-making participation after injury.

Reconnaissance blind multi-chess: an experimentation platform for ISR sensor fusion and resource management

NASA Astrophysics Data System (ADS)

Newman, Andrew J.; Richardson, Casey L.; Kain, Sean M.; Stankiewicz, Paul G.; Guseman, Paul R.; Schreurs, Blake A.; Dunne, Jeffrey A.

2016-05-01

This paper introduces the game of reconnaissance blind multi-chess (RBMC) as a paradigm and test bed for understanding and experimenting with autonomous decision making under uncertainty and in particular managing a network of heterogeneous Intelligence, Surveillance and Reconnaissance (ISR) sensors to maintain situational awareness informing tactical and strategic decision making. The intent is for RBMC to serve as a common reference or challenge problem in fusion and resource management of heterogeneous sensor ensembles across diverse mission areas. We have defined a basic rule set and a framework for creating more complex versions, developed a web-based software realization to serve as an experimentation platform, and developed some initial machine intelligence approaches to playing it.

Cross-scale phenological data integration to benefit resource management and monitoring

USGS Publications Warehouse

Richardson, Andrew D.; Weltzin, Jake F.; Morisette, Jeffrey T.

2017-01-01

Climate change is presenting new challenges for natural resource managers charged with maintaining sustainable ecosystems and landscapes. Phenology, a branch of science dealing with seasonal natural phenomena (bird migration or plant flowering in response to weather changes, for example), bridges the gap between the biosphere and the climate system. Phenological processes operate across scales that span orders of magnitude—from leaf to globe and from days to seasons—making phenology ideally suited to multiscale, multiplatform data integration and delivery of information at spatial and temporal scales suitable to inform resource management decisions.A workshop report: Workshop held June 2016 to investigate opportunities and challenges facing multi-scale, multi-platform integration of phenological data to support natural resource management decision-making.

Microfinance participation and contraceptive decision-making: results from a national sample of women in Bangladesh.

PubMed

Murshid, N S; Ely, G E

2016-10-01

Our objective was to assess whether microfinance participation affords greater contraceptive decision-making power to women. Population based secondary data analysis. In this cross-sectional study using nationally representative data from the Bangladesh Demographic and Health Survey 2011 we conducted multinomial logistic regression to estimate the odds of contraceptive decision-making by respondents and their husbands based on microfinance participation. Microfinance participation was measured as a dichotomous variable and contraceptive decision-making was conceptualized based on who made decisions about contraceptive use: respondents only; their partners or husbands only; or both. The odds of decision-making by the respondent, with the reference case being joint decision-making, were higher for microfinance participants, but they were not significant. The odds of decision-making by the husband, with the reference case again being joint decision-making, were significantly lower among men who were partnered with women who participated in microfinance (RRR = 0.70, P < 0.01). Microfinance participation by women allowed men to share decision-making power with their wives that resulted in higher odds of joint decision-making. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Exploring Effective Decision Making through Human-Centered and Computational Intelligence Methods

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

Han, Kyungsik; Cook, Kristin A.; Shih, Patrick C.

Decision-making has long been studied to understand a psychological, cognitive, and social process of selecting an effective choice from alternative options. Its studies have been extended from a personal level to a group and collaborative level, and many computer-aided decision-making systems have been developed to help people make right decisions. There has been significant research growth in computational aspects of decision-making systems, yet comparatively little effort has existed in identifying and articulating user needs and requirements in assessing system outputs and the extent to which human judgments could be utilized for making accurate and reliable decisions. Our research focus ismore » decision-making through human-centered and computational intelligence methods in a collaborative environment, and the objectives of this position paper are to bring our research ideas to the workshop, and share and discuss ideas.« less

STARS Proceedings (3-4 December 1991)

DTIC Science & Technology

1991-12-04

PROJECT PROCESS OBJECTIVES & ASSOCIATED METRICS: Prioritize ECPs: complexity & error-history measures 0 Make vs Buy decisions: Effort & Quality (or...history measures, error- proneness and past histories of trouble with particular modules are very useful measures. Make vs Buy decisions: Does the...Effort offset the gain in Quality relative to buy ... Effort and Quality (or defect rate) histories give helpful indications of how to make this decision

Application of Construal Level and Value-Belief Norm Theories to Undergraduate Decision-Making on a Wildlife Socio-Scientific Issue

ERIC Educational Resources Information Center

Sutter, A. McKinzie; Dauer, Jenny M.; Forbes, Cory T.

2018-01-01

One aim of science education is to develop scientific literacy for decision-making in daily life. Socio-scientific issues (SSI) and structured decision-making frameworks can help students reach these objectives. This research uses value belief norm (VBN) theory and construal level theory (CLT) to explore students' use of personal values in their…

Improving accountability in vaccine decision-making.

PubMed

Timmis, James Kenneth; Black, Steven; Rappuoli, Rino

2017-11-01

Healthcare decisions, in particular those affecting entire populations, should be evidence-based and taken by decision-makers sharing broad alignment with affected stakeholders. However, criteria, priorities and procedures for decision-making are sometimes non-transparent, frequently vary considerably across equivalent decision-bodies, do not always consider the broader benefits of new health-measures, and therefore do not necessarily adequately represent the relevant stakeholder-spectrum. Areas covered: To address these issues in the context of the evaluation of new vaccines, we have proposed a first baseline set of core evaluation criteria, primarily selected by members of the vaccine research community, and suggested their implementation in vaccine evaluation procedures. In this communication, we review the consequences and utility of stakeholder-centered core considerations to increase transparency in and accountability of decision-making procedures, in general, and of the benefits gained by their inclusion in Multi-Criteria-Decision-Analysis tools, exemplified by SMART Vaccines, specifically. Expert commentary: To increase effectiveness and comparability of health decision outcomes, decision procedures should be properly standardized across equivalent (national) decision bodies. To this end, including stakeholder-centered criteria in decision procedures would significantly increase their transparency and accountability, support international capacity building to improve health, and reduce societal costs and inequity resulting from suboptimal health decision-making.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

PubMed Central

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Decision making in the Navy Budget Office.

DTIC Science & Technology

1986-06-01

The primary objective of this thesis is to familiarize the reader with the budget decision making pocesses and considerations which influence the ...formulation of the Department of the navy’s (DON) budget from perspective of the Office of Budget and Reports (OBR), the impact of resource allocation...budgetary) decisions upon the overall framwork within which DON budgetary decisions are made, the organizational

Agreement on Child Maltreatment Decisions: A Nonrandomized Study on the Effects of Structured Decision-Making

ERIC Educational Resources Information Center

Bartelink, C.; van Yperen, T. A.; ten Berge, I. J.; de Kwaadsteniet, L.; Witteman, C. L. M.

2014-01-01

Background: Practitioners investigating cases of suspected child maltreatment often disagree whether a child is subject to or at risk of abuse or neglect in the family and, if so, what to do about such abuse or neglect. Structured decision-making is considered to be a solution to the problem of subjective judgments and decisions. Objective: This…

Localized prostate cancer treatment decision-making information online: improving its effectiveness and dissemination for nonprofit and government-supported organizations.

PubMed

Silk, Kami J; Perrault, Evan K; Nazione, Samantha; Pace, Kristin; Hager, Polly; Springer, Steven

2013-12-01

The current study reports findings from evaluation research conducted to identify how online prostate cancer treatment decision-making information can be both improved and more effectively disseminated to those who need it most. A multi-method, multi-target approach was used and guided by McGuire's Communication Matrix Model. Focus groups (n = 31) with prostate cancer patients and their family members, and in-depth interviews with physicians (n = 8), helped inform a web survey (n = 89). Results indicated that physicians remain a key information source for medical advice and the Internet is a primary channel used to help make informed prostate cancer treatment decisions. Participants reported a need for more accessible information related to treatment options and treatment side effects. Additionally, physicians indicated that the best way for agencies to reach them with new information to deliver to patients is by contacting them directly and meeting with them one-on-one. Advice for organizations to improve their current prostate cancer web offerings and further ways to improve information dissemination are discussed.

Decision Making Under Uncertainty and Complexity: A Model-Based Scenario Approach to Supporting Integrated Water Resources Management

NASA Astrophysics Data System (ADS)

Liu, Y.; Gupta, H.; Wagener, T.; Stewart, S.; Mahmoud, M.; Hartmann, H.; Springer, E.

2007-12-01

Some of the most challenging issues facing contemporary water resources management are those typified by complex coupled human-environmental systems with poorly characterized uncertainties. In other words, major decisions regarding water resources have to be made in the face of substantial uncertainty and complexity. It has been suggested that integrated models can be used to coherently assemble information from a broad set of domains, and can therefore serve as an effective means for tackling the complexity of environmental systems. Further, well-conceived scenarios can effectively inform decision making, particularly when high complexity and poorly characterized uncertainties make the problem intractable via traditional uncertainty analysis methods. This presentation discusses the integrated modeling framework adopted by SAHRA, an NSF Science & Technology Center, to investigate stakeholder-driven water sustainability issues within the semi-arid southwestern US. The multi-disciplinary, multi-resolution modeling framework incorporates a formal scenario approach to analyze the impacts of plausible (albeit uncertain) alternative futures to support adaptive management of water resources systems. Some of the major challenges involved in, and lessons learned from, this effort will be discussed.

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.

D-Side: A Facility and Workforce Planning Group Multi-criteria Decision Support System for Johnson Space Center

NASA Technical Reports Server (NTRS)

Tavana, Madjid

2005-01-01

"To understand and protect our home planet, to explore the universe and search for life, and to inspire the next generation of explorers" is NASA's mission. The Systems Management Office at Johnson Space Center (JSC) is searching for methods to effectively manage the Center's resources to meet NASA's mission. D-Side is a group multi-criteria decision support system (GMDSS) developed to support facility decisions at JSC. D-Side uses a series of sequential and structured processes to plot facilities in a three-dimensional (3-D) graph on the basis of each facility alignment with NASA's mission and goals, the extent to which other facilities are dependent on the facility, and the dollar value of capital investments that have been postponed at the facility relative to the facility replacement value. A similarity factor rank orders facilities based on their Euclidean distance from Ideal and Nadir points. These similarity factors are then used to allocate capital improvement resources across facilities. We also present a parallel model that can be used to support decisions concerning allocation of human resources investments across workforce units. Finally, we present results from a pilot study where 12 experienced facility managers from NASA used D-Side and the organization's current approach to rank order and allocate funds for capital improvement across 20 facilities. Users evaluated D-Side favorably in terms of ease of use, the quality of the decision-making process, decision quality, and overall value-added. Their evaluations of D-Side were significantly more favorable than their evaluations of the current approach. Keywords: NASA, Multi-Criteria Decision Making, Decision Support System, AHP, Euclidean Distance, 3-D Modeling, Facility Planning, Workforce Planning.

Multi-criteria decision making approaches for quality control of genome-wide association studies.

PubMed

Malovini, Alberto; Rognoni, Carla; Puca, Annibale; Bellazzi, Riccardo

2009-03-01

Experimental errors in the genotyping phases of a Genome-Wide Association Study (GWAS) can lead to false positive findings and to spurious associations. An appropriate quality control phase could minimize the effects of this kind of errors. Several filtering criteria can be used to perform quality control. Currently, no formal methods have been proposed for taking into account at the same time these criteria and the experimenter's preferences. In this paper we propose two strategies for setting appropriate genotyping rate thresholds for GWAS quality control. These two approaches are based on the Multi-Criteria Decision Making theory. We have applied our method on a real dataset composed by 734 individuals affected by Arterial Hypertension (AH) and 486 nonagenarians without history of AH. The proposed strategies appear to deal with GWAS quality control in a sound way, as they lead to rationalize and make explicit the experimenter's choices thus providing more reproducible results.

Barriers to and facilitators of implementing shared decision making and decision support in a paediatric hospital: A descriptive study

PubMed Central

Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L

2016-01-01

OBJECTIVE: To explore multiple stakeholders’ perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. METHODS: An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators’, clinicians’, parents’ and youths’ perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. RESULTS: Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders’ knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital’s culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. CONCLUSIONS: Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors’ paediatric hospital. PMID:27398058

Examining Challenges Related to the Production of Actionable Climate Knowledge for Adaptation Decision-Making: A Focus on Climate Knowledge System Producers

NASA Astrophysics Data System (ADS)

Ernst, K.; Preston, B. L.; Tenggren, S.; Klein, R.; Gerger-Swartling, Å.

2017-12-01

Many challenges to adaptation decision-making and action have been identified across peer-reviewed and gray literature. These challenges have primarily focused on the use of climate knowledge for adaptation decision-making, the process of adaptation decision-making, and the needs of the decision-maker. Studies on climate change knowledge systems often discuss the imperative role of climate knowledge producers in adaptation decision-making processes and stress the need for producers to engage in knowledge co-production activities and to more effectively meet decision-maker needs. While the influence of climate knowledge producers on the co-production of science for adaptation decision-making is well-recognized, hardly any research has taken a direct approach to analyzing the challenges that climate knowledge producers face when undertaking science co-production. Those challenges can influence the process of knowledge production and may hinder the creation, utilization, and dissemination of actionable knowledge for adaptation decision-making. This study involves semi-structured interviews, focus groups, and participant observations to analyze, identify, and contextualize the challenges that climate knowledge producers in Sweden face as they endeavor to create effective climate knowledge systems for multiple contexts, scales, and levels across the European Union. Preliminary findings identify complex challenges related to education, training, and support; motivation, willingness, and culture; varying levels of prioritization; professional roles and responsibilities; the type and amount of resources available; and professional incentive structures. These challenges exist at varying scales and levels across individuals, organizations, networks, institutions, and disciplines. This study suggests that the creation of actionable knowledge for adaptation decision-making is not supported across scales and levels in the climate knowledge production landscape. Additionally, enabling the production of actionable knowledge for adaptation decision-making requires multi-level effort beyond the individual level.

Development of a Decision Support System for Monitoring, Reporting, Forecasting Ecological Conditions of the Appalachian Trail

Treesearch

Y. Wang; R. Nemani; F. Dieffenbach; K. Stolte; G. Holcomb

2010-01-01

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decision-making on management of the A.T. by providing a coherent framework for data integration,...

Thresholds for conservation and management: structured decision making as a conceptual framework

USGS Publications Warehouse

Nichols, James D.; Eaton, Mitchell J.; Martin, Julien; Edited by Guntenspergen, Glenn R.

2014-01-01

changes in system dynamics. They are frequently incorporated into ecological models used to project system responses to management actions. Utility thresholds are components of management objectives and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. Decision thresholds are derived from the other components of the decision process.We advocate a structured decision making (SDM) approach within which the following components are identified: objectives (possibly including utility thresholds), potential actions, models (possibly including ecological thresholds), monitoring program, and a solution algorithm (which produces decision thresholds). Adaptive resource management (ARM) is described as a special case of SDM developed for recurrent decision problems that are characterized by uncertainty. We believe that SDM, in general, and ARM, in particular, provide good approaches to conservation and management. Use of SDM and ARM also clarifies the distinct roles of ecological thresholds, utility thresholds, and decision thresholds in informed decision processes.

Understanding Resource Allocation in High Schools.

ERIC Educational Resources Information Center

Hartman, William T.

Despite commonly held views concerning educators' rational decision-making behavior, there are competing interpretations of school personnels' objective, actions, and decision-making processes. Alternative explanations emphasize bureaucratic routine, administrative convenience, educator self-interest, and political motivations, rather than…

Gendered Behavior Patterns in School Board Governance

ERIC Educational Resources Information Center

Mountford, Meredith; Brunner, C. Cryss

2010-01-01

Background/Context: Educational leadership literature lacks research focused on how gender influences decision making, in particular at the highest level of school governance, the school board table. Consequently, whether gender makes a difference during decision making at the school board table has yet to be determined. Purpose/Objective/Research…