Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

2017-08-01

Distributed radar network systems have been shown to have many unique features. Due to their advantage of signal and spatial diversities, radar networks are attractive for target detection. In practice, the netted radars in radar networks are supposed to maximize their transmit power to achieve better detection performance, which may be in contradiction with low probability of intercept (LPI). Therefore, this paper investigates the problem of adaptive power allocation for radar networks in a cooperative game-theoretic framework such that the LPI performance can be improved. Taking into consideration both the transmit power constraints and the minimum signal to interference plus noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game based on LPI is formulated, whose objective is to minimize the total transmit power by optimizing the power allocation in radar networks. First, a novel SINR-based network utility function is defined and utilized as a metric to evaluate power allocation. Then, with the well-designed network utility function, the existence and uniqueness of the Nash bargaining solution are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Numerical simulations and theoretic analysis are provided to evaluate the effectiveness of the proposed algorithm.

The Conference Proceedings of the 1997 Air Transport Research Group (ATRG) of the WCTR Society. Volume 3

NASA Technical Reports Server (NTRS)

Oum, T. H.; Bowen, B. D.

1997-01-01

This paper covers topics such as: Safety and Air Fares; International Airline Safety; Multi-fare Seat Allocation Problem; Dynamic Allocation of Airline Seat Inventory; Seat Allocation on Flights with Two Fares; Effects of Intercontinental Alliances; Domestic Airline Mergers; Simulating the Effects of Airline Deregulation on Frequency Choice; and Firm Size Inequality and Market Power.

Power-efficient distributed resource allocation under goodput QoS constraints for heterogeneous networks

NASA Astrophysics Data System (ADS)

Andreotti, Riccardo; Del Fiorentino, Paolo; Giannetti, Filippo; Lottici, Vincenzo

2016-12-01

This work proposes a distributed resource allocation (RA) algorithm for packet bit-interleaved coded OFDM transmissions in the uplink of heterogeneous networks (HetNets), characterized by small cells deployed over a macrocell area and sharing the same band. Every user allocates its transmission resources, i.e., bits per active subcarrier, coding rate, and power per subcarrier, to minimize the power consumption while both guaranteeing a target quality of service (QoS) and accounting for the interference inflicted by other users transmitting over the same band. The QoS consists of the number of information bits delivered in error-free packets per unit of time, or goodput (GP), estimated at the transmitter by resorting to an efficient effective SNR mapping technique. First, the RA problem is solved in the point-to-point case, thus deriving an approximate yet accurate closed-form expression for the power allocation (PA). Then, the interference-limited HetNet case is examined, where the RA problem is described as a non-cooperative game, providing a solution in terms of generalized Nash equilibrium. Thanks to the closed-form of the PA, the solution analysis is based on the best response concept. Hence, sufficient conditions for existence and uniqueness of the solution are analytically derived, along with a distributed algorithm capable of reaching the game equilibrium.

Reactive power planning under high penetration of wind energy using Benders decomposition

DOE PAGES

Xu, Yan; Wei, Yanli; Fang, Xin; ...

2015-11-05

This study addresses the optimal allocation of reactive power volt-ampere reactive (VAR) sources under the paradigm of high penetration of wind energy. Reactive power planning (RPP) in this particular condition involves a high level of uncertainty because of wind power characteristic. To properly model wind generation uncertainty, a multi-scenario framework optimal power flow that considers the voltage stability constraint under the worst wind scenario and transmission N 1 contingency is developed. The objective of RPP in this study is to minimise the total cost including the VAR investment cost and the expected generation cost. Therefore RPP under this condition ismore » modelled as a two-stage stochastic programming problem to optimise the VAR location and size in one stage, then to minimise the fuel cost in the other stage, and eventually, to find the global optimal RPP results iteratively. Benders decomposition is used to solve this model with an upper level problem (master problem) for VAR allocation optimisation and a lower problem (sub-problem) for generation cost minimisation. Impact of the potential reactive power support from doubly-fed induction generator (DFIG) is also analysed. Lastly, case studies on the IEEE 14-bus and 118-bus systems are provided to verify the proposed method.« less

Joint subchannel pairing and power control for cognitive radio networks with amplify-and-forward relaying.

PubMed

Shen, Yanyan; Wang, Shuqiang; Wei, Zhiming

2014-01-01

Dynamic spectrum sharing has drawn intensive attention in cognitive radio networks. The secondary users are allowed to use the available spectrum to transmit data if the interference to the primary users is maintained at a low level. Cooperative transmission for secondary users can reduce the transmission power and thus improve the performance further. We study the joint subchannel pairing and power allocation problem in relay-based cognitive radio networks. The objective is to maximize the sum rate of the secondary user that is helped by an amplify-and-forward relay. The individual power constraints at the source and the relay, the subchannel pairing constraints, and the interference power constraints are considered. The problem under consideration is formulated as a mixed integer programming problem. By the dual decomposition method, a joint optimal subchannel pairing and power allocation algorithm is proposed. To reduce the computational complexity, two suboptimal algorithms are developed. Simulations have been conducted to verify the performance of the proposed algorithms in terms of sum rate and average running time under different conditions.

Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

PubMed Central

Naeem, Muhammad; Illanko, Kandasamy; Karmokar, Ashok; Anpalagan, Alagan; Jaseemuddin, Muhammad

2013-01-01

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated. PMID:23966194

Power allocation strategies to minimize energy consumption in wireless body area networks.

PubMed

Kailas, Aravind

2011-01-01

The wide scale deployment of wireless body area networks (WBANs) hinges on designing energy efficient communication protocols to support the reliable communication as well as to prolong the network lifetime. Cooperative communications, a relatively new idea in wireless communications, offers the benefits of multi-antenna systems, thereby improving the link reliability and boosting energy efficiency. In this short paper, the advantages of resorting to cooperative communications for WBANs in terms of minimized energy consumption are investigated. Adopting an energy model that encompasses energy consumptions in the transmitter and receiver circuits, and transmitting energy per bit, it is seen that cooperative transmission can improve energy efficiency of the wireless network. In particular, the problem of optimal power allocation is studied with the constraint of targeted outage probability. Two strategies of power allocation are considered: power allocation with and without posture state information. Using analysis and simulation-based results, two key points are demonstrated: (i) allocating power to the on-body sensors making use of the posture information can reduce the total energy consumption of the WBAN; and (ii) when the channel condition is good, it is better to recruit less relays for cooperation to enhance energy efficiency.

Automated electric power management and control for Space Station Freedom

NASA Technical Reports Server (NTRS)

Dolce, James L.; Mellor, Pamela A.; Kish, James A.

1990-01-01

A comprehensive automation design is being developed for Space Station Freedom's electric power system. It strives to increase station productivity by applying expert systems and conventional algorithms to automate power system operation. An integrated approach to the power system command and control problem is defined and used to direct technology development in: diagnosis, security monitoring and analysis, battery management, and cooperative problem-solving for resource allocation. The prototype automated power system is developed using simulations and test-beds.

Satellite Power System (SPS) international agreements

NASA Technical Reports Server (NTRS)

Grove, S.

1978-01-01

The problems in obtaining international agreements on geostationary orbit availability, microwave frequency allocations and microwave frequency standards for satellites transmitting solar power are considered. The various U.S. policy options, strategies and time frames with respect to key issues are analyzed.

Wireless Power Transfer for Distributed Estimation in Sensor Networks

NASA Astrophysics Data System (ADS)

Mai, Vien V.; Shin, Won-Yong; Ishibashi, Koji

2017-04-01

This paper studies power allocation for distributed estimation of an unknown scalar random source in sensor networks with a multiple-antenna fusion center (FC), where wireless sensors are equipped with radio-frequency based energy harvesting technology. The sensors' observation is locally processed by using an uncoded amplify-and-forward scheme. The processed signals are then sent to the FC, and are coherently combined at the FC, at which the best linear unbiased estimator (BLUE) is adopted for reliable estimation. We aim to solve the following two power allocation problems: 1) minimizing distortion under various power constraints; and 2) minimizing total transmit power under distortion constraints, where the distortion is measured in terms of mean-squared error of the BLUE. Two iterative algorithms are developed to solve the non-convex problems, which converge at least to a local optimum. In particular, the above algorithms are designed to jointly optimize the amplification coefficients, energy beamforming, and receive filtering. For each problem, a suboptimal design, a single-antenna FC scenario, and a common harvester deployment for colocated sensors, are also studied. Using the powerful semidefinite relaxation framework, our result is shown to be valid for any number of sensors, each with different noise power, and for an arbitrarily number of antennas at the FC.

Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

PubMed Central

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-01-01

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

PubMed

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-10-27

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

Location-allocation models and new solution methodologies in telecommunication networks

NASA Astrophysics Data System (ADS)

Dinu, S.; Ciucur, V.

2016-08-01

When designing a telecommunications network topology, three types of interdependent decisions are combined: location, allocation and routing, which are expressed by the following design considerations: how many interconnection devices - consolidation points/concentrators should be used and where should they be located; how to allocate terminal nodes to concentrators; how should the voice, video or data traffic be routed and what transmission links (capacitated or not) should be built into the network. Including these three components of the decision into a single model generates a problem whose complexity makes it difficult to solve. A first method to address the overall problem is the sequential one, whereby the first step deals with the location-allocation problem and based on this solution the subsequent sub-problem (routing the network traffic) shall be solved. The issue of location and allocation in a telecommunications network, called "The capacitated concentrator location- allocation - CCLA problem" is based on one of the general location models on a network in which clients/demand nodes are the terminals and facilities are the concentrators. Like in a location model, each client node has a demand traffic, which must be served, and the facilities can serve these demands within their capacity limit. In this study, the CCLA problem is modeled as a single-source capacitated location-allocation model whose optimization objective is to determine the minimum network cost consisting of fixed costs for establishing the locations of concentrators, costs for operating concentrators and costs for allocating terminals to concentrators. The problem is known as a difficult combinatorial optimization problem for which powerful algorithms are required. Our approach proposes a Fuzzy Genetic Algorithm combined with a local search procedure to calculate the optimal values of the location and allocation variables. To confirm the efficiency of the proposed algorithm with respect to the quality of solutions, significant size test problems were considered: up to 100 terminal nodes and 50 concentrators on a 100 × 100 square grid. The performance of this hybrid intelligent algorithm was evaluated by measuring the quality of its solutions with respect to the following statistics: the standard deviation and the ratio of the best solution obtained.

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach.

PubMed

Ke, Mingxing; Li, Ding; Tian, Shiwei; Zhang, Yuli; Tong, Kaixiang; Xu, Yuhua

2018-05-08

The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ -equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.

Allocation and management issues in multiple-transaction open access transmission networks

NASA Astrophysics Data System (ADS)

Tao, Shu

This thesis focuses on some key issues related to allocation and management by the independent grid operator (IGO) of unbundled services in multiple-transaction open access transmission networks. The three unbundled services addressed in the thesis are transmission real power losses, reactive power support requirements from generation sources, and transmission congestion management. We develop the general framework that explicitly represents multiple transactions undertaken simultaneously in the transmission grid. This framework serves as the basis for formulating various problems treated in the thesis. We use this comprehensive framework to develop a physical-flow-based mechanism to allocate the total transmission losses to each transaction using the system. An important property of the allocation scheme is its capability to effectively deal with counter flows that result in the presence of specific transactions. Using the loss allocation results as the basis, we construct the equivalent loss compensation concept and apply it to develop flexible and effective procedures for compensating losses in multiple-transaction networks. We present a new physical-flow-based mechanism for allocating the reactive power support requirements provided by generators in multiple-transaction networks. The allocatable reactive support requirements are formulated as the sum of two specific components---the voltage magnitude variation component and the voltage angle variation component. The formulation utilizes the multiple-transaction framework and makes use of certain simplifying approximations. The formulation leads to a natural allocation as a function of the amount of each transaction. The physical interpretation of each allocation as a sensitivity of the reactive output of a generator is discussed. We propose a congestion management allocation scheme for multiple-transaction networks. The proposed scheme determines the allocation of congestion among the transactions on a physical-flow basis. It also proposes a congestion relief scheme that removes the congestion attributed to each transaction on the network in a least-cost manner to the IGO and determines the appropriate transmission charges to each transaction for its transmission usage. The thesis provides a compendium of problems that are natural extensions of the research results reported here and appear to be good candidates for future work.

Artificial Intelligence Based Control Power Optimization on Tailless Aircraft. [ARMD Seedling Fund Phase I

NASA Technical Reports Server (NTRS)

Gern, Frank; Vicroy, Dan D.; Mulani, Sameer B.; Chhabra, Rupanshi; Kapania, Rakesh K.; Schetz, Joseph A.; Brown, Derrell; Princen, Norman H.

2014-01-01

Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

Re-insurance in the Swiss health insurance market: Fit, power, and balance.

PubMed

Schmid, Christian P R; Beck, Konstantin

2016-07-01

Risk equalization mechanisms mitigate insurers' incentives to practice risk selection. On the other hand, incentives to limit healthcare spending can be distorted by risk equalization, particularly when risk equalization payments depend on realized costs instead of expected costs. In addition, cost based risk equalization mechanisms may incentivize health insurers to distort the allocation of resources among different services. The incentives to practice risk selection, to limit healthcare spending, and to distort the allocation of resources can be measured by fit, power, and balance, respectively. We apply these three measures to evaluate the risk adjustment mechanism in Switzerland. Our results suggest that it performs very well in terms of power but rather poorly in terms of fit. The latter indicates that risk selection might be a severe problem. We show that re-insurance can reduce this problem while power remains on a high level. In addition, we provide evidence that the Swiss risk equalization mechanism does not lead to imbalances across different services. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Optimal Resource Allocation for NOMA-TDMA Scheme with α-Fairness in Industrial Internet of Things.

PubMed

Sun, Yanjing; Guo, Yiyu; Li, Song; Wu, Dapeng; Wang, Bin

2018-05-15

In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, and power control are jointly optimized in order to maximize the system α -fair utility under transmit power constraint and minimum rate constraint. The optimization problem is nonconvex because of the fractional objective function and the nonconvex constraints. To deal with the original problem, we firstly convert the objective function in the optimization problem into a difference of two convex functions (D.C.) form, and then propose a NOMA-TDMA-DC algorithm to exploit the global optimum. Numerical results show that the NOMA-TDMA scheme significantly outperforms the traditional orthogonal multiple access scheme in terms of both spectral efficiency and user fairness.

Improved minimum cost and maximum power two stage genome-wide association study designs.

PubMed

Stanhope, Stephen A; Skol, Andrew D

2012-01-01

In a two stage genome-wide association study (2S-GWAS), a sample of cases and controls is allocated into two groups, and genetic markers are analyzed sequentially with respect to these groups. For such studies, experimental design considerations have primarily focused on minimizing study cost as a function of the allocation of cases and controls to stages, subject to a constraint on the power to detect an associated marker. However, most treatments of this problem implicitly restrict the set of feasible designs to only those that allocate the same proportions of cases and controls to each stage. In this paper, we demonstrate that removing this restriction can improve the cost advantages demonstrated by previous 2S-GWAS designs by up to 40%. Additionally, we consider designs that maximize study power with respect to a cost constraint, and show that recalculated power maximizing designs can recover a substantial amount of the planned study power that might otherwise be lost if study funding is reduced. We provide open source software for calculating cost minimizing or power maximizing 2S-GWAS designs.

Spectrum Sharing Based on a Bertrand Game in Cognitive Radio Sensor Networks

PubMed Central

Zeng, Biqing; Zhang, Chi; Hu, Pianpian; Wang, Shengyu

2017-01-01

In the study of power control and allocation based on pricing, the utility of secondary users is usually studied from the perspective of the signal to noise ratio. The study of secondary user utility from the perspective of communication demand can not only promote the secondary users to meet the maximum communication needs, but also to maximize the utilization of spectrum resources, however, research in this area is lacking, so from the viewpoint of meeting the demand of network communication, this paper designs a two stage model to solve spectrum leasing and allocation problem in cognitive radio sensor networks (CRSNs). In the first stage, the secondary base station collects the secondary network communication requirements, and rents spectrum resources from several primary base stations using the Bertrand game to model the transaction behavior of the primary base station and secondary base station. The second stage, the subcarriers and power allocation problem of secondary base stations is defined as a nonlinear programming problem to be solved based on Nash bargaining. The simulation results show that the proposed model can satisfy the communication requirements of each user in a fair and efficient way compared to other spectrum sharing schemes. PMID:28067850

Optimal Sensor Allocation for Fault Detection and Isolation

NASA Technical Reports Server (NTRS)

Azam, Mohammad; Pattipati, Krishna; Patterson-Hine, Ann

2004-01-01

Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

Decision-theoretic methodology for reliability and risk allocation in nuclear power plants

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

Cho, N.Z.; Papazoglou, I.A.; Bari, R.A.

1985-01-01

This paper describes a methodology for allocating reliability and risk to various reactor systems, subsystems, components, operations, and structures in a consistent manner, based on a set of global safety criteria which are not rigid. The problem is formulated as a multiattribute decision analysis paradigm; the multiobjective optimization, which is performed on a PRA model and reliability cost functions, serves as the guiding principle for reliability and risk allocation. The concept of noninferiority is used in the multiobjective optimization problem. Finding the noninferior solution set is the main theme of the current approach. The assessment of the decision maker's preferencesmore » could then be performed more easily on the noninferior solution set. Some results of the methodology applications to a nontrivial risk model are provided and several outstanding issues such as generic allocation and preference assessment are discussed.« less

Load allocation of power plant using multi echelon economic dispatch

NASA Astrophysics Data System (ADS)

Wahyuda, Santosa, Budi; Rusdiansyah, Ahmad

2017-11-01

In this paper, the allocation of power plant load which is usually done with a single echelon as in the load flow calculation, is expanded into a multi echelon. A plant load allocation model based on the integration of economic dispatch and multi-echelon problem is proposed. The resulting model is called as Single Objective Multi Echelon Economic Dispatch (SOME ED). This model allows the distribution of electrical power in more detail in the transmission and distribution substations along the existing network. Considering the interconnection system where the distance between the plant and the load center is usually far away, therefore the loss in this model is seen as a function of distance. The advantages of this model is its capability of allocating electrical loads properly, as well as economic dispatch information with the flexibility of electric power system as a result of using multi-echelon. In this model, the flexibility can be viewed from two sides, namely the supply and demand sides, so that the security of the power system is maintained. The model was tested on a small artificial data. The results demonstrated a good performance. It is still very open to further develop the model considering the integration with renewable energy, multi-objective with environmental issues and applied to the case with a larger scale.

Statistical mechanics of competitive resource allocation using agent-based models

NASA Astrophysics Data System (ADS)

Chakraborti, Anirban; Challet, Damien; Chatterjee, Arnab; Marsili, Matteo; Zhang, Yi-Cheng; Chakrabarti, Bikas K.

2015-01-01

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.

Power Allocation Based on Data Classification in Wireless Sensor Networks

PubMed Central

Wang, Houlian; Zhou, Gongbo

2017-01-01

Limited node energy in wireless sensor networks is a crucial factor which affects the monitoring of equipment operation and working conditions in coal mines. In addition, due to heterogeneous nodes and different data acquisition rates, the number of arriving packets in a queue network can differ, which may lead to some queue lengths reaching the maximum value earlier compared with others. In order to tackle these two problems, an optimal power allocation strategy based on classified data is proposed in this paper. Arriving data is classified into dissimilar classes depending on the number of arriving packets. The problem is formulated as a Lyapunov drift optimization with the objective of minimizing the weight sum of average power consumption and average data class. As a result, a suboptimal distributed algorithm without any knowledge of system statistics is presented. The simulations, conducted in the perfect channel state information (CSI) case and the imperfect CSI case, reveal that the utility can be pushed arbitrarily close to optimal by increasing the parameter V, but with a corresponding growth in the average delay, and that other tunable parameters W and the classification method in the interior of utility function can trade power optimality for increased average data class. The above results show that data in a high class has priorities to be processed than data in a low class, and energy consumption can be minimized in this resource allocation strategy. PMID:28498346

A power allocation method for 2 × 2 VLC-MIMO indoor communication

NASA Astrophysics Data System (ADS)

Dai, Mingjun; Yuan, Jing; Feng, Renhai; Wang, Hui; Chen, Bin; Lin, Xiaohui

2016-08-01

Visible light communication (VLC) has been a promising field of optical communications which focuses on visible light spectrum that humans can see. Unlike existing studies which mainly discuss point-to-point communication, in this paper, we consider a VLC network, in particular a 2 × 2 system. Our focus is on dealing with interference in this network. The objective is to maximize the signal to interference plus noise ratio (SINR) of one receiver for a given SINR of another receiver. We formulate a power allocation optimization problem to deal with such interference, and introduce dichotomy to solve this optimization problem. Simulation results have twofold meaning: First, SINR_1 increases with the growth of SINR_2, which are the SINR of the two receivers, respectively. Second, our proposed scheme outperforms the classical time-division multiple access technique in terms of transmit powers of both light sources when the data rate for these two schemes are set to be identical for each user, respectively.

DAISY-DAMP: A distributed AI system for the dynamic allocation and management of power

NASA Technical Reports Server (NTRS)

Hall, Steven B.; Ohler, Peter C.

1988-01-01

One of the critical parameters that must be addressed when designing a loosely coupled Distributed AI SYstem (DAISY) has to do with the degree to which authority is centralized or decentralized. The decision to implement the Dynamic Allocation and Management of Power (DAMP) system as a network of cooperating agents mandated this study. The DAISY-DAMP problem is described; the component agents of the system are characterized; and the communication protocols system elucidated. The motivations and advantages in designing the system with authority decentralized is discussed. Progress in the area of Speech Act theory is proposed as playing a role in constructing decentralized systems.

Fuel, environmental, and transmission pricing considerations in a deregulated environment

NASA Astrophysics Data System (ADS)

Obessis, Emmanouil Vlassios

The 1992 National Energy Policy Act drastically changed the traditional structure of the vertically integrated utility. To facilitate increased competition in the power utility sector, all markets related to power generation have been opened to free competition and trading. To survive in the new competitive environment, power producers need to reduce costs and increase efficiency. Fuel marketing strategies are thus, getting more aggressive and fuel markets are becoming more competitive, offering more options regarding fuel supplies and contracts. At the same time, the 1990 Clean Air Act Amendments are taking effect. Although tightening the emission standards, this legislation offers utilities a wider flexibility in choosing compliance strategies. It also set maximum annual allowable levels replacing the traditional uniform maximum emission rates. The bill also introduced the concept of marketable emission allowances and provided for the establishment of nationwide markets where allowances may be traded, sold, or purchased. Several fuel- and emission-constrained algorithms have been historically presented, but those two classes of constraints, in general, were handled independently. The multiobjective optimization model developed in this research work, concurrently satisfies sets of detailed fuel and emission limits, modeling in a more accurate way the fuel supply and environmental limitations and their complexities in the new deregulated operational environment. Development of the implementation software is an integral part of this research project. This software may be useful for both daily scheduling activities and short-term operational planning. A Lagrangian multipliers-based variant is used to solve the problem. Single line searches are used to update the multipliers, thus offering attractive execution times. This work also investigates the applicability of cooperative games to the problem of transmission cost allocation. Interest in game theory as a powerful tool to solve common property allocation problems has been renewed. A simple allocation framework is developed using capacity based costing rules. Different solution concepts are applied to solve small scale transmission pricing problems. Game models may render themselves useful in investigating "what if" scenarios.

Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) - a review

NASA Astrophysics Data System (ADS)

Fanuel, Ibrahim Mwita; Mushi, Allen; Kajunguri, Damian

2018-03-01

This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution (MODE) to solve the multi-objective problem in agricultural water management. The paper focused on different application aspects which include water allocation, irrigation planning, crop pattern and allocation of available land. The performance and results of these techniques are discussed. The review finds that there is a potential to use MODE to analyzed the multi-objective problem, the application is more significance due to its advantage of being simple and powerful technique than any Evolutionary Algorithm. The paper concludes with the hopeful new trend of research that demand effective use of MODE; inclusion of benefits derived from farm byproducts and production costs into the model.

Optimum sample size allocation to minimize cost or maximize power for the two-sample trimmed mean test.

PubMed

Guo, Jiin-Huarng; Luh, Wei-Ming

2009-05-01

When planning a study, sample size determination is one of the most important tasks facing the researcher. The size will depend on the purpose of the study, the cost limitations, and the nature of the data. By specifying the standard deviation ratio and/or the sample size ratio, the present study considers the problem of heterogeneous variances and non-normality for Yuen's two-group test and develops sample size formulas to minimize the total cost or maximize the power of the test. For a given power, the sample size allocation ratio can be manipulated so that the proposed formulas can minimize the total cost, the total sample size, or the sum of total sample size and total cost. On the other hand, for a given total cost, the optimum sample size allocation ratio can maximize the statistical power of the test. After the sample size is determined, the present simulation applies Yuen's test to the sample generated, and then the procedure is validated in terms of Type I errors and power. Simulation results show that the proposed formulas can control Type I errors and achieve the desired power under the various conditions specified. Finally, the implications for determining sample sizes in experimental studies and future research are discussed.

Patch Network for Power Allocation and Distribution in Smart Materials

NASA Technical Reports Server (NTRS)

Golembiewski, Walter T.

2000-01-01

The power allocation and distribution (PAD) circuitry is capable of allocating and distributing a single or multiple sources of power over multi-elements of a power user grid system. The purpose of this invention is to allocate and distribute power that is collected by individual patch rectennas to a region of specific power-user devices, such as actuators. The patch rectenna converts microwave power into DC power. Then this DC power is used to drive actuator devices. However, the power from patch rectennas is not sufficient to drive actuators unless all the collected power is effectively used to drive another group by allocation and distribution. The power allocation and distribution (PAD) circuitry solves the shortfall of power for devices in a large array. The PAD concept is based on the networked power control in which power collected over the whole array of rectennas is allocated to a sub domain where a group of devices is required to be activated for operation. Then the allocated power is distributed to individual element of power-devices in the sub domain according to a selected run-mode.

76 FR 45551 - Post-2014 Resource Pool; Loveland Area Projects, Proposed Power Allocation

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-29

... Proposed Power Allocation. SUMMARY: Western Area Power Administration (Western), a Federal power marketing... Pool Proposed Power Allocation developed under the requirements of the Power Marketing Initiative of Western's Energy Planning and Management Program (Program). Western notified the public of allocation...

Performance improvement of optical CDMA networks with stochastic artificial bee colony optimization technique

NASA Astrophysics Data System (ADS)

Panda, Satyasen

2018-05-01

This paper proposes a modified artificial bee colony optimization (ABC) algorithm based on levy flight swarm intelligence referred as artificial bee colony levy flight stochastic walk (ABC-LFSW) optimization for optical code division multiple access (OCDMA) network. The ABC-LFSW algorithm is used to solve asset assignment problem based on signal to noise ratio (SNR) optimization in OCDM networks with quality of service constraints. The proposed optimization using ABC-LFSW algorithm provides methods for minimizing various noises and interferences, regulating the transmitted power and optimizing the network design for improving the power efficiency of the optical code path (OCP) from source node to destination node. In this regard, an optical system model is proposed for improving the network performance with optimized input parameters. The detailed discussion and simulation results based on transmitted power allocation and power efficiency of OCPs are included. The experimental results prove the superiority of the proposed network in terms of power efficiency and spectral efficiency in comparison to networks without any power allocation approach.

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept

PubMed Central

Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-01-01

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme. PMID:29186850

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept.

PubMed

Shi, Chenguang; Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-11-25

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme.

A cooperative game theory approach to transmission planning in power systems

NASA Astrophysics Data System (ADS)

Contreras, Javier

The rapid restructuring of the electric power industry from a vertically integrated entity into a decentralized industry has given rise to complex problems. In particular, the transmission component of the electric power system requires new methodologies to fully capture this emerging competitive industry. Game theory models are used to model strategic interactions in a competitive environment. This thesis presents a new decentralized framework to study the transmission network expansion problem using cooperative game theory. First, the players and the rules of the game are defined. Second, a coalition formation scheme is developed. Finally, the optimized cost of expansion is allocated based on the history of the coalition formation.

Evaluation of Contribution for Voltage Control Ancillary Services Based on Social Surplus

NASA Astrophysics Data System (ADS)

Ueki, Yuji; Hara, Ryoichi; Kita, Hiroyuki; Hasegawa, Jun

Reactive power supply plays an important role in active power supply with adequate system voltages. Various pricing mechanism for reactive power supply have been developed and some of them are adopted in some power systems, however they are in a trial stage. The authors also focus on development of a pricing method for reactive power ancillary services. This problem involves two technical issues: rational estimation of the cost associated with reactive power supply and fair and transparent allocation of the estimated cost among the market participants. This paper proposes methods for evaluating the contribution of generators and demands.

Investigation of Optimal Control Allocation for Gust Load Alleviation in Flight Control

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Taylor, Brian R.; Bodson, Marc

2012-01-01

Advances in sensors and avionics computation power suggest real-time structural load measurements could be used in flight control systems for improved safety and performance. A conventional transport flight control system determines the moments necessary to meet the pilot's command, while rejecting disturbances and maintaining stability of the aircraft. Control allocation is the problem of converting these desired moments into control effector commands. In this paper, a framework is proposed to incorporate real-time structural load feedback and structural load constraints in the control allocator. Constrained optimal control allocation can be used to achieve desired moments without exceeding specified limits on monitored load points. Minimization of structural loads by the control allocator is used to alleviate gust loads. The framework to incorporate structural loads in the flight control system and an optimal control allocation algorithm will be described and then demonstrated on a nonlinear simulation of a generic transport aircraft with flight dynamics and static structural loads.

How large customer direct power transaction mode give consideration to power generation cleaning and power saving

NASA Astrophysics Data System (ADS)

Liu, Yu; Zeng, Ming; Liu, Wei; Li, Ran

2017-05-01

The so-called Large Customers' Direct Power Transaction, refers to the mode that the users on high voltage level, or being seized of hold the large power or independent power distribution, have the qualification of purchasing electricity directly from the generation companies and pay reasonable electricity transmission and distribution fee to the power network enterprises because the transaction is through its transmission channel. The Direct Purchase promotes the marketization level of electricity trading, but there are some problems in its developing process, especially whether promotes the green optimal allocation of power resources, this paper aims to explore the solution.

76 FR 64085 - Post-2014 Resource Pool-Loveland Area Projects, Final Power Allocation

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-17

... power allocation. SUMMARY: The Western Area Power Administration (Western), a Federal power marketing..., Final Power Allocation developed under the requirements of subpart C-Power Marketing Initiative of the Energy Planning and Management Program (Program) Final Rule, 10 CFR part 905. These final power...

Evaluation of Dynamic Channel and Power Assignment for Cognitive Networks

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

Syed A. Ahmad; Umesh Shukla; Ryan E. Irwin

2011-03-01

In this paper, we develop a unifying optimization formulation to describe the Dynamic Channel and Power Assignment (DCPA) problem and evaluation method for comparing DCPA algorithms. DCPA refers to the allocation of transmit power and frequency channels to links in a cognitive network so as to maximize the total number of feasible links while minimizing the aggregate transmit power. We apply our evaluation method to five algorithms representative of DCPA used in literature. This comparison illustrates the tradeoffs between control modes (centralized versus distributed) and channel/power assignment techniques. We estimate the complexity of each algorithm. Through simulations, we evaluate themore » effectiveness of the algorithms in achieving feasible link allocations in the network, as well as their power efficiency. Our results indicate that, when few channels are available, the effectiveness of all algorithms is comparable and thus the one with smallest complexity should be selected. The Least Interfering Channel and Iterative Power Assignment (LICIPA) algorithm does not require cross-link gain information, has the overall lowest run time, and highest feasibility ratio of all the distributed algorithms; however, this comes at a cost of higher average power per link.« less

Joint terminals and relay optimization for two-way power line information exchange systems with QoS constraints

NASA Astrophysics Data System (ADS)

Wu, Xiaolin; Rong, Yue

2015-12-01

The quality-of-service (QoS) criteria (measured in terms of the minimum capacity requirement in this paper) are very important to practical indoor power line communication (PLC) applications as they greatly affect the user experience. With a two-way multicarrier relay configuration, in this paper we investigate the joint terminals and relay power optimization for the indoor broadband PLC environment, where the relay node works in the amplify-and-forward (AF) mode. As the QoS-constrained power allocation problem is highly non-convex, the globally optimal solution is computationally intractable to obtain. To overcome this challenge, we propose an alternating optimization (AO) method to decompose this problem into three convex/quasi-convex sub-problems. Simulation results demonstrate the fast convergence of the proposed algorithm under practical PLC channel conditions. Compared with the conventional bidirectional direct transmission (BDT) system, the relay-assisted two-way information exchange (R2WX) scheme can meet the same QoS requirement with less total power consumption.

Joint Transmit Power Allocation and Splitting for SWIPT Aided OFDM-IDMA in Wireless Sensor Networks

PubMed Central

Li, Shanshan; Zhou, Xiaotian; Wang, Cheng-Xiang; Yuan, Dongfeng; Zhang, Wensheng

2017-01-01

In this paper, we propose to combine Orthogonal Frequency Division Multiplexing-Interleave Division Multiple Access (OFDM-IDMA) with Simultaneous Wireless Information and Power Transfer (SWIPT), resulting in SWIPT aided OFDM-IDMA scheme for power-limited sensor networks. In the proposed system, the Receive Node (RN) applies Power Splitting (PS) to coordinate the Energy Harvesting (EH) and Information Decoding (ID) process, where the harvested energy is utilized to guarantee the iterative Multi-User Detection (MUD) of IDMA to work under sufficient number of iterations. Our objective is to minimize the total transmit power of Source Node (SN), while satisfying the requirements of both minimum harvested energy and Bit Error Rate (BER) performance from individual receive nodes. We formulate such a problem as a joint power allocation and splitting one, where the iteration number of MUD is also taken into consideration as the key parameter to affect both EH and ID constraints. To solve it, a sub-optimal algorithm is proposed to determine the power profile, PS ratio and iteration number of MUD in an iterative manner. Simulation results verify that the proposed algorithm can provide significant performance improvement. PMID:28677636

Joint Transmit Power Allocation and Splitting for SWIPT Aided OFDM-IDMA in Wireless Sensor Networks.

PubMed

Li, Shanshan; Zhou, Xiaotian; Wang, Cheng-Xiang; Yuan, Dongfeng; Zhang, Wensheng

2017-07-04

In this paper, we propose to combine Orthogonal Frequency Division Multiplexing-Interleave Division Multiple Access (OFDM-IDMA) with Simultaneous Wireless Information and Power Transfer (SWIPT), resulting in SWIPT aided OFDM-IDMA scheme for power-limited sensor networks. In the proposed system, the Receive Node (RN) applies Power Splitting (PS) to coordinate the Energy Harvesting (EH) and Information Decoding (ID) process, where the harvested energy is utilized to guarantee the iterative Multi-User Detection (MUD) of IDMA to work under sufficient number of iterations. Our objective is to minimize the total transmit power of Source Node (SN), while satisfying the requirements of both minimum harvested energy and Bit Error Rate (BER) performance from individual receive nodes. We formulate such a problem as a joint power allocation and splitting one, where the iteration number of MUD is also taken into consideration as the key parameter to affect both EH and ID constraints. To solve it, a sub-optimal algorithm is proposed to determine the power profile, PS ratio and iteration number of MUD in an iterative manner. Simulation results verify that the proposed algorithm can provide significant performance improvement.

Opportunistic Capacity-Based Resource Allocation for Chunk-Based Multi-Carrier Cognitive Radio Sensor Networks

PubMed Central

Huang, Jie; Zeng, Xiaoping; Jian, Xin; Tan, Xiaoheng; Zhang, Qi

2017-01-01

The spectrum allocation for cognitive radio sensor networks (CRSNs) has received considerable research attention under the assumption that the spectrum environment is static. However, in practice, the spectrum environment varies over time due to primary user/secondary user (PU/SU) activity and mobility, resulting in time-varied spectrum resources. This paper studies resource allocation for chunk-based multi-carrier CRSNs with time-varied spectrum resources. We present a novel opportunistic capacity model through a continuous time semi-Markov chain (CTSMC) to describe the time-varied spectrum resources of chunks and, based on this, a joint power and chunk allocation model by considering the opportunistically available capacity of chunks is proposed. To reduce the computational complexity, we split this model into two sub-problems and solve them via the Lagrangian dual method. Simulation results illustrate that the proposed opportunistic capacity-based resource allocation algorithm can achieve better performance compared with traditional algorithms when the spectrum environment is time-varied. PMID:28106803

Rate and power efficient image compressed sensing and transmission

NASA Astrophysics Data System (ADS)

Olanigan, Saheed; Cao, Lei; Viswanathan, Ramanarayanan

2016-01-01

This paper presents a suboptimal quantization and transmission scheme for multiscale block-based compressed sensing images over wireless channels. The proposed method includes two stages: dealing with quantization distortion and transmission errors. First, given the total transmission bit rate, the optimal number of quantization bits is assigned to the sensed measurements in different wavelet sub-bands so that the total quantization distortion is minimized. Second, given the total transmission power, the energy is allocated to different quantization bit layers based on their different error sensitivities. The method of Lagrange multipliers with Karush-Kuhn-Tucker conditions is used to solve both optimization problems, for which the first problem can be solved with relaxation and the second problem can be solved completely. The effectiveness of the scheme is illustrated through simulation results, which have shown up to 10 dB improvement over the method without the rate and power optimization in medium and low signal-to-noise ratio cases.

Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks

NASA Astrophysics Data System (ADS)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2011-01-01

In this paper, we propose a scheme for the optimal allocation of power, source coding rate, and channel coding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower source coding rate, so they will be able to allocate a greater portion of the total available bit rate to channel coding. Stronger channel coding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channel coding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, source coding rate and channel coding rate for the nodes of the visual sensor network.

Computationally Efficient Power Allocation Algorithm in Multicarrier-Based Cognitive Radio Networks: OFDM and FBMC Systems

NASA Astrophysics Data System (ADS)

Shaat, Musbah; Bader, Faouzi

2010-12-01

Cognitive Radio (CR) systems have been proposed to increase the spectrum utilization by opportunistically access the unused spectrum. Multicarrier communication systems are promising candidates for CR systems. Due to its high spectral efficiency, filter bank multicarrier (FBMC) can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM) for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier-based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs) constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The proposed algorithm utilizes the spectrum holes in PUs bands as well as active PU bands. The performance of the proposed algorithm is investigated for OFDM and FBMC based CR systems. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and proves the efficiency of using FBMC in CR context.

Preliminary Effectiveness Study of Coping Power Program for Aggressive Children in Pakistan.

PubMed

Mushtaq, Asia; Lochman, John E; Tariq, Pervaiz N; Sabih, Fazaila

2017-10-01

Aggression is a characteristic feature of many psychiatric disorders. To address the scarceness for evidence-based interventions for behavioral problems in Pakistan, we evaluated the effectiveness of culturally adapted version of Coping Power Program. The purpose of the study was to determine the extent to which Coping Power Program is capable of reducing aggressive behavior and improving competent behavior, when delivered in a different culture, i.e., Pakistan. With randomized control trial (RCT) of pre- and post-testing, 112 fourth grade boys were allocated to Coping Power intervention condition and waitlist control condition. The intervention group showed significant reduction in aggression at post assessment, in comparison to control group. Boys who received Coping Power intervention also showed improvements in behavior, social skills, and social cognitive processes, with better anger control and problem solving strategies, in comparison to the control group. The results of the study provide preliminary evidence, supporting the effectiveness of Coping Power Program for Pakistani children. Despite its limitations, the results of this study are promising and suggest that Coping Power is an effective intervention to reduce behavioral problems and promote healthy and positive behaviors in children, even when implemented in different contexts with greater potential for violence exposure.

Simultaneous Wireless Power Transfer and Secure Multicasting in Cooperative Decode-and-Forward Relay Networks.

PubMed

Lee, Jong-Ho; Sohn, Illsoo; Kim, Yong-Hwa

2017-05-16

In this paper, we investigate simultaneous wireless power transfer and secure multicasting via cooperative decode-and-forward (DF) relays in the presence of multiple energy receivers and eavesdroppers. Two scenarios are considered under a total power budget: maximizing the minimum harvested energy among the energy receivers under a multicast secrecy rate constraint; and maximizing the multicast secrecy rate under a minimum harvested energy constraint. For both scenarios, we solve the transmit power allocation and relay beamformer design problems by using semidefinite relaxation and bisection technique. We present numerical results to analyze the energy harvesting and secure multicasting performances in cooperative DF relay networks.

Simultaneous Wireless Power Transfer and Secure Multicasting in Cooperative Decode-and-Forward Relay Networks

PubMed Central

Lee, Jong-Ho; Sohn, Illsoo; Kim, Yong-Hwa

2017-01-01

In this paper, we investigate simultaneous wireless power transfer and secure multicasting via cooperative decode-and-forward (DF) relays in the presence of multiple energy receivers and eavesdroppers. Two scenarios are considered under a total power budget: maximizing the minimum harvested energy among the energy receivers under a multicast secrecy rate constraint; and maximizing the multicast secrecy rate under a minimum harvested energy constraint. For both scenarios, we solve the transmit power allocation and relay beamformer design problems by using semidefinite relaxation and bisection technique. We present numerical results to analyze the energy harvesting and secure multicasting performances in cooperative DF relay networks. PMID:28509841

Optimizing Experimental Designs Relative to Costs and Effect Sizes.

ERIC Educational Resources Information Center

Headrick, Todd C.; Zumbo, Bruno D.

A general model is derived for the purpose of efficiently allocating integral numbers of units in multi-level designs given prespecified power levels. The derivation of the model is based on a constrained optimization problem that maximizes a general form of a ratio of expected mean squares subject to a budget constraint. This model provides more…

Optimality versus stability in water resource allocation.

PubMed

Read, Laura; Madani, Kaveh; Inanloo, Bahareh

2014-01-15

Water allocation is a growing concern in a developing world where limited resources like fresh water are in greater demand by more parties. Negotiations over allocations often involve multiple groups with disparate social, economic, and political status and needs, who are seeking a management solution for a wide range of demands. Optimization techniques for identifying the Pareto-optimal (social planner solution) to multi-criteria multi-participant problems are commonly implemented, although often reaching agreement for this solution is difficult. In negotiations with multiple-decision makers, parties who base decisions on individual rationality may find the social planner solution to be unfair, thus creating a need to evaluate the willingness to cooperate and practicality of a cooperative allocation solution, i.e., the solution's stability. This paper suggests seeking solutions for multi-participant resource allocation problems through an economics-based power index allocation method. This method can inform on allocation schemes that quantify a party's willingness to participate in a negotiation rather than opt for no agreement. Through comparison of the suggested method with a range of distance-based multi-criteria decision making rules, namely, least squares, MAXIMIN, MINIMAX, and compromise programming, this paper shows that optimality and stability can produce different allocation solutions. The mismatch between the socially-optimal alternative and the most stable alternative can potentially result in parties leaving the negotiation as they may be too dissatisfied with their resource share. This finding has important policy implications as it justifies why stakeholders may not accept the socially optimal solution in practice, and underlies the necessity of considering stability where it may be more appropriate to give up an unstable Pareto-optimal solution for an inferior stable one. Authors suggest assessing the stability of an allocation solution as an additional component to an analysis that seeks to distribute water in a negotiated process. Copyright © 2013 Elsevier Ltd. All rights reserved.

Power Allocation and Outage Probability Analysis for SDN-based Radio Access Networks

NASA Astrophysics Data System (ADS)

Zhao, Yongxu; Chen, Yueyun; Mai, Zhiyuan

2018-01-01

In this paper, performance of Access network Architecture based SDN (Software Defined Network) is analyzed with respect to the power allocation issue. A power allocation scheme PSO-PA (Particle Swarm Optimization-power allocation) algorithm is proposed, the proposed scheme is subjected to constant total power with the objective of minimizing system outage probability. The entire access network resource configuration is controlled by the SDN controller, then it sends the optimized power distribution factor to the base station source node (SN) and the relay node (RN). Simulation results show that the proposed scheme reduces the system outage probability at a low complexity.

Calculation and application of energy transaction allocation factors in electric power transmission systems

NASA Astrophysics Data System (ADS)

Fradi, Aniss

The ability to allocate the active power (MW) loading on transmission lines and transformers, is the basis of the "flow based" transmission allocation system developed by the North American Electric Reliability Council. In such a system, the active power flows must be allocated to each line or transformer in proportion to the active power being transmitted by each transaction imposed on the system. Currently, this is accomplished through the use of the linear Power Transfer Distribution Factors (PTDFs). Unfortunately, no linear allocation models exist for other energy transmission quantities, such as MW and MVAR losses, MVAR and MVA flows, etc. Early allocation schemes were developed to allocate MW losses due to transactions to branches in a transmission system, however they exhibited diminished accuracy, since most of them are based on linear power flow modeling of the transmission system. This thesis presents a new methodology to calculate Energy Transaction Allocation factors (ETA factors, or eta factors), using the well-known process of integration of a first derivative function, as well as consistent and well-established mathematical and AC power flow models. The factors give a highly accurate allocation of any non-linear system quantity to transactions placed on the transmission system. The thesis also extends the new ETA factors calculation procedure to restructure a new economic dispatch scheme where multiple sets of generators are economically dispatched to meet their corresponding load and their share of the losses.

Market-Based Coordination of Thermostatically Controlled Loads—Part II: Unknown Parameters and Case Studies

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

Li, Sen; Zhang, Wei; Lian, Jianming

This two-part paper considers the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. The companion paper (Part I) formulates the problem and proposes a load coordination framework using the mechanism design approach. To address the unknown parameters, Part II of this paper presents a joint state and parameter estimation framework based on the expectation maximization algorithm. The overall framework is then validated using real-world weather data andmore » price data, and is compared with other approaches in terms of aggregated power response. Simulation results indicate that our coordination framework can effectively improve the efficiency of the power grid operations and reduce power congestion at key times.« less

A hybrid Jaya algorithm for reliability-redundancy allocation problems

NASA Astrophysics Data System (ADS)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

10 CFR Appendix D to Subpart D of... - Classes of Actions that Normally Require EISs

Code of Federal Regulations, 2012 CFR

2012-01-01

...] D7Contracts, policies, and marketing and allocation plans for electric power D8Import or export of natural gas... and Allocation Plans for Electric Power Establishment and implementation of contracts, policies, and marketing and allocation plans related to electric power acquisition that involve (1) The interconnection of...

10 CFR Appendix D to Subpart D of... - Classes of Actions that Normally Require EISs

Code of Federal Regulations, 2013 CFR

2013-01-01

...] D7Contracts, policies, and marketing and allocation plans for electric power D8Import or export of natural gas... and Allocation Plans for Electric Power Establishment and implementation of contracts, policies, and marketing and allocation plans related to electric power acquisition that involve (1) The interconnection of...

Research on allocation efficiency of the daisy chain allocation algorithm

NASA Astrophysics Data System (ADS)

Shi, Jingping; Zhang, Weiguo

2013-03-01

With the improvement of the aircraft performance in reliability, maneuverability and survivability, the number of the control effectors increases a lot. How to distribute the three-axis moments into the control surfaces reasonably becomes an important problem. Daisy chain method is simple and easy to be carried out in the design of the allocation system. But it can not solve the allocation problem for entire attainable moment subset. For the lateral-directional allocation problem, the allocation efficiency of the daisy chain can be directly measured by the area of its subset of attainable moments. Because of the non-linear allocation characteristic, the subset of attainable moments of daisy-chain method is a complex non-convex polygon, and it is difficult to solve directly. By analyzing the two-dimensional allocation problems with a "micro-element" idea, a numerical calculation algorithm is proposed to compute the area of the non-convex polygon. In order to improve the allocation efficiency of the algorithm, a genetic algorithm with the allocation efficiency chosen as the fitness function is proposed to find the best pseudo-inverse matrix.

Market power in auction and efficiency in emission permits allocation.

PubMed

Jiang, Min Xing; Yang, Dong Xiao; Chen, Zi Yue; Nie, Pu Yan

2016-12-01

This paper analyzes how to achieve the cost-effectiveness by initial allocation of CO 2 emission permits when a single dominant firm in production market has market power in auction, and compare two prevalent allocation patterns, mixed allocation and single auction. We show how the firm with market power may manipulate the auction price, thereby this leads to fail to achieve cost-effective solution by auction unless the total permits for allocation equal to the effective emissions cap. Provided that the market power firm receives strictly positive free permits, the effective emissions cap of mixed allocation is larger than that of single auction. The production market share of dominant firm is increasing with the free permits it holds. Finally, we examine the compliance costs and welfare of mixed allocation and single auction, the result show that the former is preferred to the later when policy makers consider economic welfare without welfare cost due to CO 2 emissions. Copyright © 2016 Elsevier Ltd. All rights reserved.

A trust-based sensor allocation algorithm in cooperative space search problems

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik

2011-06-01

Sensor allocation is an important and challenging problem within the field of multi-agent systems. The sensor allocation problem involves deciding how to assign a number of targets or cells to a set of agents according to some allocation protocol. Generally, in order to make efficient allocations, we need to design mechanisms that consider both the task performers' costs for the service and the associated probability of success (POS). In our problem, the costs are the used sensor resource, and the POS is the target tracking performance. Usually, POS may be perceived differently by different agents because they typically have different standards or means of evaluating the performance of their counterparts (other sensors in the search and tracking problem). Given this, we turn to the notion of trust to capture such subjective perceptions. In our approach, we develop a trust model to construct a novel mechanism that motivates sensor agents to limit their greediness or selfishness. Then we model the sensor allocation optimization problem with trust-in-loop negotiation game and solve it using a sub-game perfect equilibrium. Numerical simulations are performed to demonstrate the trust-based sensor allocation algorithm in cooperative space situation awareness (SSA) search problems.

Sex allocation conflict in insect societies: who wins?

PubMed Central

Helanterä, Heikki; Ratnieks, Francis L. W.

2009-01-01

Sex allocation in colonies of eusocial Hymenoptera is one of the best studied social conflicts. We outline a framework for analysing conflict outcome through power and the costs of manipulation and suggest that the conflict will often be unresolved because both major parties of interest, the queen and the workers, should manipulate allocation even at considerable costs to the colony. We suggest future work for analysing power in the conflict between queen and workers over sex allocation and discuss the extent of male power. PMID:19656859

Kalai-Smorodinsky bargaining solution for optimal resource allocation over wireless DS-CDMA visual sensor networks

NASA Astrophysics Data System (ADS)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2012-01-01

Surveillance applications usually require high levels of video quality, resulting in high power consumption. The existence of a well-behaved scheme to balance video quality and power consumption is crucial for the system's performance. In the present work, we adopt the game-theoretic approach of Kalai-Smorodinsky Bargaining Solution (KSBS) to deal with the problem of optimal resource allocation in a multi-node wireless visual sensor network (VSN). In our setting, the Direct Sequence Code Division Multiple Access (DS-CDMA) method is used for channel access, while a cross-layer optimization design, which employs a central processing server, accounts for the overall system efficacy through all network layers. The task assigned to the central server is the communication with the nodes and the joint determination of their transmission parameters. The KSBS is applied to non-convex utility spaces, efficiently distributing the source coding rate, channel coding rate and transmission powers among the nodes. In the underlying model, the transmission powers assume continuous values, whereas the source and channel coding rates can take only discrete values. Experimental results are reported and discussed to demonstrate the merits of KSBS over competing policies.

Power allocation and range performance considerations for a dual-frequency EBPSK/MPPSK system

NASA Astrophysics Data System (ADS)

Yao, Yu; Wu, Lenan; Zhao, Junhui

2017-12-01

Extended binary phase shift keying/M-ary position phase shift keying (EBPSK/MPPSK)-MODEM provides radar and communication functions on a single hardware platform with a single waveform. However, its range estimation accuracy is worse than continuous-wave (CW) radar because of the imbalance of power in two carrier frequencies. In this article, the power allocation method for dual-frequency EBPSK/MPPSK modulated systems is presented. The power of two signal transmitters is adequately allocated to ensure that the power in two carrier frequencies is equal. The power allocation ratios for two types of modulation systems are obtained. Moreover, considerations regarding the range of operation of the dual-frequency system are analysed. In addition to theoretical considerations, computer simulations are provided to illustrate the performance.

A group-based tasks allocation algorithm for the optimization of long leave opportunities in academic departments

NASA Astrophysics Data System (ADS)

Eyono Obono, S. D.; Basak, Sujit Kumar

2011-12-01

The general formulation of the assignment problem consists in the optimal allocation of a given set of tasks to a workforce. This problem is covered by existing literature for different domains such as distributed databases, distributed systems, transportation, packets radio networks, IT outsourcing, and teaching allocation. This paper presents a new version of the assignment problem for the allocation of academic tasks to staff members in departments with long leave opportunities. It presents the description of a workload allocation scheme and its algorithm, for the allocation of an equitable number of tasks in academic departments where long leaves are necessary.

Allocation of Transaction Cost to Market Participants Using an Analytical Method in Deregulated Market

NASA Astrophysics Data System (ADS)

Jeyasankari, S.; Jeslin Drusila Nesamalar, J.; Charles Raja, S.; Venkatesh, P.

2014-04-01

Transmission cost allocation is one of the major challenges in transmission open access faced by the electric power sector. The purpose of this work is to provide an analytical method for allocating transmission transaction cost in deregulated market. This research work provides a usage based transaction cost allocation method based on line-flow impact factor (LIF) which relates the power flow in each line with respect to transacted power for the given transaction. This method provides the impact of line flows without running iterative power flow solution and is well suited for real time applications. The proposed method is compared with the Newton-Raphson (NR) method of cost allocation on sample six bus and practical Indian utility 69 bus systems by considering multilateral transaction.

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

PubMed

Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

2015-09-01

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

Statistical Power and Optimum Sample Allocation Ratio for Treatment and Control Having Unequal Costs Per Unit of Randomization

ERIC Educational Resources Information Center

Liu, Xiaofeng

2003-01-01

This article considers optimal sample allocation between the treatment and control condition in multilevel designs when the costs per sampling unit vary due to treatment assignment. Optimal unequal allocation may reduce the cost from that of a balanced design without sacrificing any power. The optimum sample allocation ratio depends only on the…

PRACTICAL: Planning and Resource Allocation in C2-Domains With Time Critical Algorithms (PRACTICAL: Planning en Allocatie in C2-Domeinen Met Tijdkritische Algoritmen)

DTIC Science & Technology

1993-02-01

the (re)planning framework, incorporating the demonstrators CALIGULA and ALLOCATOR for resource allocation and scheduling respectively. In the Command...demonstrator CALIGULA for the problem of allocating frequencies to a radio link network. The problems in the domain of scheduling are dealt with. which has...demonstrating the (re)planning framework, incorporating the demonstrators CALIGULA and ALLOCATOR for resource allocation and scheduling respectively

Vehicle routing problem and capacitated vehicle routing problem frameworks in fund allocation problem

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

2016-11-01

Two new methods adopted from methods commonly used in the field of transportation and logistics are proposed to solve a specific issue of investment allocation problem. Vehicle routing problem and capacitated vehicle routing methods are applied to optimize the fund allocation of a portfolio of investment assets. This is done by determining the sequence of the assets. As a result, total investment risk is minimized by this sequence.

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

PubMed Central

Yu, Hongyan; Zhang, Yongqiang; Yang, Yuanyuan; Ji, Luyue

2017-01-01

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. PMID:28820496

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.

PubMed

Yu, Hongyan; Zhang, Yongqiang; Guo, Songtao; Yang, Yuanyuan; Ji, Luyue

2017-08-18

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.

Coordinated control of micro-grid based on distributed moving horizon control.

PubMed

Ma, Miaomiao; Shao, Liyang; Liu, Xiangjie

2018-05-01

This paper proposed the distributed moving horizon coordinated control scheme for the power balance and economic dispatch problems of micro-grid based on distributed generation. We design the power coordinated controller for each subsystem via moving horizon control by minimizing a suitable objective function. The objective function of distributed moving horizon coordinated controller is chosen based on the principle that wind power subsystem has the priority to generate electricity while photovoltaic power generation coordinates with wind power subsystem and the battery is only activated to meet the load demand when necessary. The simulation results illustrate that the proposed distributed moving horizon coordinated controller can allocate the output power of two generation subsystems reasonably under varying environment conditions, which not only can satisfy the load demand but also limit excessive fluctuations of output power to protect the power generation equipment. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Intelligent Optimization of Modulation Indexes in Unified Tracking and Communication System

NASA Astrophysics Data System (ADS)

Yang, Wei-wei; Cong, Bo; Huang, Qiong; Zhu, Li-wei

2016-02-01

In the unified tracking and communication system, the ranging signal and the telemetry, communication signals are used in the same channel. In the link budget, it is necessary to allocate the power reasonably, so as to ensure the performance of system and reduce the cost. In this paper, the nonlinear optimization problem is studied using intelligent optimization method. Simulation analysis results show that the proposed method is effective.

The Normalized-Rate Iterative Algorithm: A Practical Dynamic Spectrum Management Method for DSL

NASA Astrophysics Data System (ADS)

Statovci, Driton; Nordström, Tomas; Nilsson, Rickard

2006-12-01

We present a practical solution for dynamic spectrum management (DSM) in digital subscriber line systems: the normalized-rate iterative algorithm (NRIA). Supported by a novel optimization problem formulation, the NRIA is the only DSM algorithm that jointly addresses spectrum balancing for frequency division duplexing systems and power allocation for the users sharing a common cable bundle. With a focus on being implementable rather than obtaining the highest possible theoretical performance, the NRIA is designed to efficiently solve the DSM optimization problem with the operators' business models in mind. This is achieved with the help of two types of parameters: the desired network asymmetry and the desired user priorities. The NRIA is a centralized DSM algorithm based on the iterative water-filling algorithm (IWFA) for finding efficient power allocations, but extends the IWFA by finding the achievable bitrates and by optimizing the bandplan. It is compared with three other DSM proposals: the IWFA, the optimal spectrum balancing algorithm (OSBA), and the bidirectional IWFA (bi-IWFA). We show that the NRIA achieves better bitrate performance than the IWFA and the bi-IWFA. It can even achieve performance almost as good as the OSBA, but with dramatically lower requirements on complexity. Additionally, the NRIA can achieve bitrate combinations that cannot be supported by any other DSM algorithm.

Efficient and equitable spatial allocation of renewable power plants at the country scale

NASA Astrophysics Data System (ADS)

Drechsler, Martin; Egerer, Jonas; Lange, Martin; Masurowski, Frank; Meyerhoff, Jürgen; Oehlmann, Malte

2017-09-01

Globally, the production of renewable energy is undergoing rapid growth. One of the most pressing issues is the appropriate allocation of renewable power plants, as the question of where to produce renewable electricity is highly controversial. Here we explore this issue through analysis of the efficient and equitable spatial allocation of wind turbines and photovoltaic power plants in Germany. We combine multiple methods, including legal analysis, economic and energy modelling, monetary valuation and numerical optimization. We find that minimum distances between renewable power plants and human settlements should be as small as is legally possible. Even small reductions in efficiency lead to large increases in equity. By considering electricity grid expansion costs, we find a more even allocation of power plants across the country than is the case when grid expansion costs are neglected.

Research on air and missile defense task allocation based on extended contract net protocol

NASA Astrophysics Data System (ADS)

Zhang, Yunzhi; Wang, Gang

2017-10-01

Based on the background of air and missile defense distributed element corporative engagement, the interception task allocation problem of multiple weapon units with multiple targets under network condition is analyzed. Firstly, a mathematical model of task allocation is established by combat task decomposition. Secondly, the initialization assignment based on auction contract and the adjustment allocation scheme based on swap contract were introduced to the task allocation. Finally, through the simulation calculation of typical situation, the model can be used to solve the task allocation problem in complex combat environment.

Minimizing the Total Service Time of Discrete Dynamic Berth Allocation Problem by an Iterated Greedy Heuristic

PubMed Central

2014-01-01

Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocation problem (discrete DBAP), which aims to minimize total service time, and proposes an iterated greedy (IG) algorithm to solve it. The proposed IG algorithm is tested on three benchmark problem sets. Experimental results show that the proposed IG algorithm can obtain optimal solutions for all test instances of the first and second problem sets and outperforms the best-known solutions for 35 out of 90 test instances of the third problem set. PMID:25295295

18 CFR 366.5 - Allocation of costs for non-power goods and services.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Allocation of costs for non-power goods and services. 366.5 Section 366.5 Conservation of Power and Water Resources FEDERAL... ACT OF 2005, FEDERAL POWER ACT AND NATURAL GAS ACT BOOKS AND RECORDS Definitions and Provisions Under...

18 CFR 366.5 - Allocation of costs for non-power goods and services.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Allocation of costs for non-power goods and services. 366.5 Section 366.5 Conservation of Power and Water Resources FEDERAL... ACT OF 2005, FEDERAL POWER ACT AND NATURAL GAS ACT BOOKS AND RECORDS Definitions and Provisions Under...

Speaking truth to power: the effect of candid feedback on how individuals with power allocate resources.

PubMed

Oc, Burak; Bashshur, Michael R; Moore, Celia

2015-03-01

Subordinates are often seen as impotent, able to react to but not affect how powerholders treat them. Instead, we conceptualize subordinate feedback as an important trigger of powerholders' behavioral self-regulation and explore subordinates' reciprocal influence on how powerholders allocate resources to them over time. In 2 experiments using a multiparty, multiround dictator game paradigm, we found that when subordinates provided candid feedback about whether they found prior allocations to be fair or unfair, powerholders regulated how self-interested their allocations were over time. However, when subordinates provided compliant feedback about powerholders' prior allocation decisions (offered consistently positive feedback, regardless of the powerholders' prior allocation), those powerholders made increasingly self-interested allocations over time. In addition, we showed that guilt partially mediates this relationship: powerholders feel more guilty after receiving negative feedback about an allocation, subsequently leading to a less self-interested allocation, whereas they feel less guilty after receiving positive feedback about an allocation, subsequently taking more for themselves. Our findings integrate the literature on upward feedback with theory about moral self-regulation to support the idea that subordinates are an important source of influence over those who hold power over them. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Dynamic resource allocation in a hierarchical multiprocessor system: A preliminary study

NASA Technical Reports Server (NTRS)

Ngai, Tin-Fook

1986-01-01

An integrated system approach to dynamic resource allocation is proposed. Some of the problems in dynamic resource allocation and the relationship of these problems to system structures are examined. A general dynamic resource allocation scheme is presented. A hierarchial system architecture which dynamically maps between processor structure and programs at multiple levels of instantiations is described. Simulation experiments were conducted to study dynamic resource allocation on the proposed system. Preliminary evaluation based on simple dynamic resource allocation algorithms indicates that with the proposed system approach, the complexity of dynamic resource management could be significantly reduced while achieving reasonable effective dynamic resource allocation.

Models of resource allocation optimization when solving the control problems in organizational systems

NASA Astrophysics Data System (ADS)

Menshikh, V.; Samorokovskiy, A.; Avsentev, O.

2018-03-01

The mathematical model of optimizing the allocation of resources to reduce the time for management decisions and algorithms to solve the general problem of resource allocation. The optimization problem of choice of resources in organizational systems in order to reduce the total execution time of a job is solved. This problem is a complex three-level combinatorial problem, for the solving of which it is necessary to implement the solution to several specific problems: to estimate the duration of performing each action, depending on the number of performers within the group that performs this action; to estimate the total execution time of all actions depending on the quantitative composition of groups of performers; to find such a distribution of the existing resource of performers in groups to minimize the total execution time of all actions. In addition, algorithms to solve the general problem of resource allocation are proposed.

TCSC based filtering and improvement of power quality

NASA Astrophysics Data System (ADS)

Arulvendhan, K.; Dilli srinivasan, J.; Vinil, M.

2018-04-01

Thyristor Controlled Series Capacitor (TCSC) as a dynamic system, also its competence in growing power allocation in transmission lines, can be used to improve different power system problems. TCSC’s dissimilar advantages can be categorised as steady-state and transient ones. During a fault, TCSC can increase power quality by reducing the current and benefit to keep the voltage as high as conceivable. In this paper, the application of TCSC to enrich one of the vital power quality issues, i.e., voltage sag is investigated. Different operating modes of TCSC have dissimilar influences on the voltage of the bus that the line armed with TCSC is connected to. Relocating to bypass mode upon manifestation of a fault is a significant feature of TCSC to advance voltage sag. The simulations on a trial network disclose these facts.

A transaction assessment method for allocation of transmission services

NASA Astrophysics Data System (ADS)

Banunarayanan, Venkatasubramaniam

The purpose of this research is to develop transaction assessment methods for allocating transmission services that are provided by an area/utility to power transactions. Transmission services are the services needed to deliver, or provide the capacity to deliver, real and reactive power from one or more supply points to one or more delivery points. As the number of transactions increase rapidly in the emerging deregulated environment, accurate quantification of the transmission services an area/utility provides to accommodate a transaction is becoming important, because then appropriate pricing schemes can be developed to compensate for the parties that provide these services. The Allocation methods developed are based on the "Fair Resource Allocation Principle" and they determine for each transaction the following: the flowpath of the transaction (both real and reactive power components), generator reactive power support from each area/utility, real power loss support from each area/utility. Further, allocation methods for distributing the cost of relieving congestion on transmission lines caused by transactions are also developed. The main feature of the proposed methods is representation of actual usage of the transmission services by the transactions. The proposed method is tested extensively on a variety of systems. The allocation methods developed in this thesis for allocation of transmission services to transactions is not only useful in studying the impact of transactions on a transmission system in a multi-transaction case, but they are indeed necessary to meet the criteria set forth by FERC with regard to pricing based on actual usage. The "consistency" of the proposed allocation methods has also been investigated and tested.

An overview of the artificial intelligence and expert systems component of RICIS

NASA Technical Reports Server (NTRS)

Feagin, Terry

1987-01-01

Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.

Reactive Power Pricing Model Considering the Randomness of Wind Power Output

NASA Astrophysics Data System (ADS)

Dai, Zhong; Wu, Zhou

2018-01-01

With the increase of wind power capacity integrated into grid, the influence of the randomness of wind power output on the reactive power distribution of grid is gradually highlighted. Meanwhile, the power market reform puts forward higher requirements for reasonable pricing of reactive power service. Based on it, the article combined the optimal power flow model considering wind power randomness with integrated cost allocation method to price reactive power. Meanwhile, considering the advantages and disadvantages of the present cost allocation method and marginal cost pricing, an integrated cost allocation method based on optimal power flow tracing is proposed. The model realized the optimal power flow distribution of reactive power with the minimal integrated cost and wind power integration, under the premise of guaranteeing the balance of reactive power pricing. Finally, through the analysis of multi-scenario calculation examples and the stochastic simulation of wind power outputs, the article compared the results of the model pricing and the marginal cost pricing, which proved that the model is accurate and effective.

Sort-Mid tasks scheduling algorithm in grid computing.

PubMed

Reda, Naglaa M; Tawfik, A; Marzok, Mohamed A; Khamis, Soheir M

2015-11-01

Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, and they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new heuristic algorithm called Sort-Mid is proposed. It aims to maximizing the utilization and minimizing the makespan. The new strategy of Sort-Mid algorithm is to find appropriate resources. The base step is to get the average value via sorting list of completion time of each task. Then, the maximum average is obtained. Finally, the task has the maximum average is allocated to the machine that has the minimum completion time. The allocated task is deleted and then, these steps are repeated until all tasks are allocated. Experimental tests show that the proposed algorithm outperforms almost other algorithms in terms of resources utilization and makespan.

Sort-Mid tasks scheduling algorithm in grid computing

PubMed Central

Reda, Naglaa M.; Tawfik, A.; Marzok, Mohamed A.; Khamis, Soheir M.

2014-01-01

Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, and they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new heuristic algorithm called Sort-Mid is proposed. It aims to maximizing the utilization and minimizing the makespan. The new strategy of Sort-Mid algorithm is to find appropriate resources. The base step is to get the average value via sorting list of completion time of each task. Then, the maximum average is obtained. Finally, the task has the maximum average is allocated to the machine that has the minimum completion time. The allocated task is deleted and then, these steps are repeated until all tasks are allocated. Experimental tests show that the proposed algorithm outperforms almost other algorithms in terms of resources utilization and makespan. PMID:26644937

A Suboptimal Power-Saving Transmission Scheme in Multiple Component Carrier Networks

NASA Astrophysics Data System (ADS)

Chung, Yao-Liang; Tsai, Zsehong

Power consumption due to transmissions in base stations (BSs) has been a major contributor to communication-related CO2 emissions. A power optimization model is developed in this study with respect to radio resource allocation and activation in a multiple Component Carrier (CC) environment. We formulate and solve the power-minimization problem of the BS transceivers for multiple-CC networks with carrier aggregation, while maintaining the overall system and respective users' utilities above minimum levels. The optimized power consumption based on this model can be viewed as a lower bound of that of other algorithms employed in practice. A suboptimal scheme with low computation complexity is proposed. Numerical results show that the power consumption of our scheme is much better than that of the conventional one in which all CCs are always active, if both schemes maintain the same required utilities.

Unequal power allocation for JPEG transmission over MIMO systems.

PubMed

Sabir, Muhammad Farooq; Bovik, Alan Conrad; Heath, Robert W

2010-02-01

With the introduction of multiple transmit and receive antennas in next generation wireless systems, real-time image and video communication are expected to become quite common, since very high data rates will become available along with improved data reliability. New joint transmission and coding schemes that explore advantages of multiple antenna systems matched with source statistics are expected to be developed. Based on this idea, we present an unequal power allocation scheme for transmission of JPEG compressed images over multiple-input multiple-output systems employing spatial multiplexing. The JPEG-compressed image is divided into different quality layers, and different layers are transmitted simultaneously from different transmit antennas using unequal transmit power, with a constraint on the total transmit power during any symbol period. Results show that our unequal power allocation scheme provides significant image quality improvement as compared to different equal power allocations schemes, with the peak-signal-to-noise-ratio gain as high as 14 dB at low signal-to-noise-ratios.

A game-theoretical pricing mechanism for multiuser rate allocation for video over WiMAX

NASA Astrophysics Data System (ADS)

Chen, Chao-An; Lo, Chi-Wen; Lin, Chia-Wen; Chen, Yung-Chang

2010-07-01

In multiuser rate allocation in a wireless network, strategic users can bias the rate allocation by misrepresenting their bandwidth demands to a base station, leading to an unfair allocation. Game-theoretical approaches have been proposed to address the unfair allocation problems caused by the strategic users. However, existing approaches rely on a timeconsuming iterative negotiation process. Besides, they cannot completely prevent unfair allocations caused by inconsistent strategic behaviors. To address these problems, we propose a Search Based Pricing Mechanism to reduce the communication time and to capture a user's strategic behavior. Our simulation results show that the proposed method significantly reduce the communication time as well as converges stably to an optimal allocation.

Stochastic Optimization For Water Resources Allocation

NASA Astrophysics Data System (ADS)

Yamout, G.; Hatfield, K.

2003-12-01

For more than 40 years, water resources allocation problems have been addressed using deterministic mathematical optimization. When data uncertainties exist, these methods could lead to solutions that are sub-optimal or even infeasible. While optimization models have been proposed for water resources decision-making under uncertainty, no attempts have been made to address the uncertainties in water allocation problems in an integrated approach. This paper presents an Integrated Dynamic, Multi-stage, Feedback-controlled, Linear, Stochastic, and Distributed parameter optimization approach to solve a problem of water resources allocation. It attempts to capture (1) the conflict caused by competing objectives, (2) environmental degradation produced by resource consumption, and finally (3) the uncertainty and risk generated by the inherently random nature of state and decision parameters involved in such a problem. A theoretical system is defined throughout its different elements. These elements consisting mainly of water resource components and end-users are described in terms of quantity, quality, and present and future associated risks and uncertainties. Models are identified, modified, and interfaced together to constitute an integrated water allocation optimization framework. This effort is a novel approach to confront the water allocation optimization problem while accounting for uncertainties associated with all its elements; thus resulting in a solution that correctly reflects the physical problem in hand.

Allocation of Load-Loss Cost Caused by Voltage Sag

NASA Astrophysics Data System (ADS)

Gao, X.

2017-10-01

This paper focuses on the allocation of load-loss cost caused by voltage sag in the environment of electricity market. To compensate the loss of loads due to voltage sags, the load-loss cost is allocated to both sources and power consumers. On the basis of Load Drop Cost (LDC), a quantitative evaluation index of load-loss cost caused by voltage sag is identified. The load-loss cost to be allocated to power consumers themselves is calculated according to load classification. Based on the theory of power component the quantitative relation between sources and loads is established, thereby a quantitative calculation method for load-loss cost allocated to each source is deduced and the quantitative compensation from individual source to load is proposed. A simple five-bus system illustrates the main features of the proposed method.

Study on optimal configuration of the grid-connected wind-solar-battery hybrid power system

NASA Astrophysics Data System (ADS)

Ma, Gang; Xu, Guchao; Ju, Rong; Wu, Tiantian

2017-08-01

The capacity allocation of each energy unit in the grid-connected wind-solar-battery hybrid power system is a significant segment in system design. In this paper, taking power grid dispatching into account, the research priorities are as follows: (1) We establish the mathematic models of each energy unit in the hybrid power system. (2) Based on dispatching of the power grid, energy surplus rate, system energy volatility and total cost, we establish the evaluation system for the wind-solar-battery power system and use a number of different devices as the constraint condition. (3) Based on an improved Genetic algorithm, we put forward a multi-objective optimisation algorithm to solve the optimal configuration problem in the hybrid power system, so we can achieve the high efficiency and economy of the grid-connected hybrid power system. The simulation result shows that the grid-connected wind-solar-battery hybrid power system has a higher comprehensive performance; the method of optimal configuration in this paper is useful and reasonable.

An improved risk-explicit interval linear programming model for pollution load allocation for watershed management.

PubMed

Xia, Bisheng; Qian, Xin; Yao, Hong

2017-11-01

Although the risk-explicit interval linear programming (REILP) model has solved the problem of having interval solutions, it has an equity problem, which can lead to unbalanced allocation between different decision variables. Therefore, an improved REILP model is proposed. This model adds an equity objective function and three constraint conditions to overcome this equity problem. In this case, pollution reduction is in proportion to pollutant load, which supports balanced development between different regional economies. The model is used to solve the problem of pollution load allocation in a small transboundary watershed. Compared with the REILP original model result, our model achieves equity between the upstream and downstream pollutant loads; it also overcomes the problem of greatest pollution reduction, where sources are nearest to the control section. The model provides a better solution to the problem of pollution load allocation than previous versions.

Constraint-based scheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte

1991-01-01

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Constraint-based scheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte

1991-01-01

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocations for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its applications to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Constraint-based scheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte

1993-01-01

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Fair sharing of resources in a supply network with constraints.

PubMed

Carvalho, Rui; Buzna, Lubos; Just, Wolfram; Helbing, Dirk; Arrowsmith, David K

2012-04-01

This paper investigates the effect of network topology on the fair allocation of network resources among a set of agents, an all-important issue for the efficiency of transportation networks all around us. We analyze a generic mechanism that distributes network capacity fairly among existing flow demands. The problem can be solved by semianalytical methods on a nearest-neighbor graph with one source and sink pair, when transport occurs over shortest paths. For this setup, we uncover a broad range of patterns of intersecting shortest paths as a function of the distance between the source and the sink. When the number of intersections is the maximum and the distance between the source and the sink is large, we find that a fair allocation implies a decrease of at least 50% from the maximum throughput. We also find that the histogram of the flow allocations assigned to the agents decays as a power law with exponent -1. Our semianalytical framework suggests possible explanations for the well-known reduction of the throughput in fair allocations. It also suggests that the combination of network topology and routing rules can lead to highly uneven (but fair) distributions of resources, a remark of caution to network designers.

Fair sharing of resources in a supply network with constraints

NASA Astrophysics Data System (ADS)

Carvalho, Rui; Buzna, Lubos; Just, Wolfram; Helbing, Dirk; Arrowsmith, David K.

2012-04-01

This paper investigates the effect of network topology on the fair allocation of network resources among a set of agents, an all-important issue for the efficiency of transportation networks all around us. We analyze a generic mechanism that distributes network capacity fairly among existing flow demands. The problem can be solved by semianalytical methods on a nearest-neighbor graph with one source and sink pair, when transport occurs over shortest paths. For this setup, we uncover a broad range of patterns of intersecting shortest paths as a function of the distance between the source and the sink. When the number of intersections is the maximum and the distance between the source and the sink is large, we find that a fair allocation implies a decrease of at least 50% from the maximum throughput. We also find that the histogram of the flow allocations assigned to the agents decays as a power law with exponent -1. Our semianalytical framework suggests possible explanations for the well-known reduction of the throughput in fair allocations. It also suggests that the combination of network topology and routing rules can lead to highly uneven (but fair) distributions of resources, a remark of caution to network designers.

Political model of social evolution

PubMed Central

Acemoglu, Daron; Egorov, Georgy; Sonin, Konstantin

2011-01-01

Almost all democratic societies evolved socially and politically out of authoritarian and nondemocratic regimes. These changes not only altered the allocation of economic resources in society but also the structure of political power. In this paper, we develop a framework for studying the dynamics of political and social change. The society consists of agents that care about current and future social arrangements and economic allocations; allocation of political power determines who has the capacity to implement changes in economic allocations and future allocations of power. The set of available social rules and allocations at any point in time is stochastic. We show that political and social change may happen without any stochastic shocks or as a result of a shock destabilizing an otherwise stable social arrangement. Crucially, the process of social change is contingent (and history-dependent): the timing and sequence of stochastic events determine the long-run equilibrium social arrangements. For example, the extent of democratization may depend on how early uncertainty about the set of feasible reforms in the future is resolved. PMID:22198760

Political model of social evolution.

PubMed

Acemoglu, Daron; Egorov, Georgy; Sonin, Konstantin

2011-12-27

Almost all democratic societies evolved socially and politically out of authoritarian and nondemocratic regimes. These changes not only altered the allocation of economic resources in society but also the structure of political power. In this paper, we develop a framework for studying the dynamics of political and social change. The society consists of agents that care about current and future social arrangements and economic allocations; allocation of political power determines who has the capacity to implement changes in economic allocations and future allocations of power. The set of available social rules and allocations at any point in time is stochastic. We show that political and social change may happen without any stochastic shocks or as a result of a shock destabilizing an otherwise stable social arrangement. Crucially, the process of social change is contingent (and history-dependent): the timing and sequence of stochastic events determine the long-run equilibrium social arrangements. For example, the extent of democratization may depend on how early uncertainty about the set of feasible reforms in the future is resolved.

A legal primer for the obesity prevention movement.

PubMed

Mermin, Seth E; Graff, Samantha K

2009-10-01

Public health advocates and scientists working on obesity prevention policy face challenges in balancing legal rights, individual freedom, and societal health goals. In particular, the US Constitution and the 50 state constitutions place limits on the ability of government to act, even in the best interests of the public. To help policymakers avoid crossing constitutional boundaries, we distilled the legal concepts most relevant to formulating policies aimed at preventing obesity: police power; allocation of power among federal, state, and local governments; freedom of speech; property rights; privacy; equal protection; and contract rights. The goal is to allow policymakers to avoid potential constitutional problems in the formation of obesity prevention policy.

Analyzing the Effect of Multi-fuel and Practical Constraints on Realistic Economic Load Dispatch using Novel Two-stage PSO

NASA Astrophysics Data System (ADS)

Chintalapudi, V. S.; Sirigiri, Sivanagaraju

2017-04-01

In power system restructuring, pricing the electrical power plays a vital role in cost allocation between suppliers and consumers. In optimal power dispatch problem, not only the cost of active power generation but also the costs of reactive power generated by the generators should be considered to increase the effectiveness of the problem. As the characteristics of reactive power cost curve are similar to that of active power cost curve, a nonconvex reactive power cost function is formulated. In this paper, a more realistic multi-fuel total cost objective is formulated by considering active and reactive power costs of generators. The formulated cost function is optimized by satisfying equality, in-equality and practical constraints using the proposed uniform distributed two-stage particle swarm optimization. The proposed algorithm is a combination of uniform distribution of control variables (to start the iterative process with good initial value) and two-stage initialization processes (to obtain best final value in less number of iterations) can enhance the effectiveness of convergence characteristics. Obtained results for the considered standard test functions and electrical systems indicate the effectiveness of the proposed algorithm and can obtain efficient solution when compared to existing methods. Hence, the proposed method is a promising method and can be easily applied to optimize the power system objectives.

A robust optimisation approach to the problem of supplier selection and allocation in outsourcing

NASA Astrophysics Data System (ADS)

Fu, Yelin; Keung Lai, Kin; Liang, Liang

2016-03-01

We formulate the supplier selection and allocation problem in outsourcing under an uncertain environment as a stochastic programming problem. Both the decision-maker's attitude towards risk and the penalty parameters for demand deviation are considered in the objective function. A service level agreement, upper bound for each selected supplier's allocation and the number of selected suppliers are considered as constraints. A novel robust optimisation approach is employed to solve this problem under different economic situations. Illustrative examples are presented with managerial implications highlighted to support decision-making.

Analog Processor To Solve Optimization Problems

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Eberhardt, Silvio P.; Thakoor, Anil P.

1993-01-01

Proposed analog processor solves "traveling-salesman" problem, considered paradigm of global-optimization problems involving routing or allocation of resources. Includes electronic neural network and auxiliary circuitry based partly on concepts described in "Neural-Network Processor Would Allocate Resources" (NPO-17781) and "Neural Network Solves 'Traveling-Salesman' Problem" (NPO-17807). Processor based on highly parallel computing solves problem in significantly less time.

Solar power satellites - Technical, social and political implications

NASA Astrophysics Data System (ADS)

Knelman, F. H.

Solar power satellite systems (SPS) are examined, together with their environmental and social impacts and the energy policies necessary for their construction. The energy source, the sun, is acceptable to advocates of decentralized technologies, while the conversion system is fitted to large institutions. However, large-scale power plants are subject to persistent malfunctions, and the approximately 50 sq km SPS solar array is projected to suffer from at least recurring cell contact failures. The power could also be generated by heat engines for transmission by either laser or microwaves. Numerous feasibility and cost-benefit studies are still required, including defining the transmission beam's effects on the atmosphere, ionosphere, and human health. Furthermore, the resource allocations, capital costs, insurance, and institutional problems still need clarification, as do the design, logistics, and development of an entire new, much larger launch system based on Shuttle technology. Finally, the military defensibility of the SPS power station is questioned.

Adaptive power allocation schemes based on IAFS algorithm for OFDM-based cognitive radio systems

NASA Astrophysics Data System (ADS)

Zhang, Shuying; Zhao, Xiaohui; Liang, Cong; Ding, Xu

2017-01-01

In cognitive radio (CR) systems, reasonable power allocation can increase transmission rate of CR users or secondary users (SUs) as much as possible and at the same time insure normal communication among primary users (PUs). This study proposes an optimal power allocation scheme for the OFDM-based CR system with one SU influenced by multiple PU interference constraints. This scheme is based on an improved artificial fish swarm (IAFS) algorithm in combination with the advantage of conventional artificial fish swarm (ASF) algorithm and particle swarm optimisation (PSO) algorithm. In performance comparison of IAFS algorithm with other intelligent algorithms by simulations, the superiority of the IAFS algorithm is illustrated; this superiority results in better performance of our proposed scheme than that of the power allocation algorithms proposed by the previous studies in the same scenario. Furthermore, our proposed scheme can obtain higher transmission data rate under the multiple PU interference constraints and the total power constraint of SU than that of the other mentioned works.

75 FR 1616 - Post-2010 Resource Pool, Pick-Sloan Missouri Basin Program-Eastern Division

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-12

... Allocation for the new customer was calculated using the Procedures. As defined in the Post-1985 Marketing..., a Federal power marketing agency of the Department of Energy (DOE), hereby announces the Post-2010... need to withdraw power from existing customers. The Final Power Allocation is published to show Western...

Development a heuristic method to locate and allocate the medical centers to minimize the earthquake relief operation time.

PubMed

Aghamohammadi, Hossein; Saadi Mesgari, Mohammad; Molaei, Damoon; Aghamohammadi, Hasan

2013-01-01

Location-allocation is a combinatorial optimization problem, and is defined as Non deterministic Polynomial Hard (NP) hard optimization. Therefore, solution of such a problem should be shifted from exact to heuristic or Meta heuristic due to the complexity of the problem. Locating medical centers and allocating injuries of an earthquake to them has high importance in earthquake disaster management so that developing a proper method will reduce the time of relief operation and will consequently decrease the number of fatalities. This paper presents the development of a heuristic method based on two nested genetic algorithms to optimize this location allocation problem by using the abilities of Geographic Information System (GIS). In the proposed method, outer genetic algorithm is applied to the location part of the problem and inner genetic algorithm is used to optimize the resource allocation. The final outcome of implemented method includes the spatial location of new required medical centers. The method also calculates that how many of the injuries at each demanding point should be taken to any of the existing and new medical centers as well. The results of proposed method showed high performance of designed structure to solve a capacitated location-allocation problem that may arise in a disaster situation when injured people has to be taken to medical centers in a reasonable time.

Large Scale Multi-area Static/Dynamic Economic Dispatch using Nature Inspired Optimization

NASA Astrophysics Data System (ADS)

Pandit, Manjaree; Jain, Kalpana; Dubey, Hari Mohan; Singh, Rameshwar

2017-04-01

Economic dispatch (ED) ensures that the generation allocation to the power units is carried out such that the total fuel cost is minimized and all the operating equality/inequality constraints are satisfied. Classical ED does not take transmission constraints into consideration, but in the present restructured power systems the tie-line limits play a very important role in deciding operational policies. ED is a dynamic problem which is performed on-line in the central load dispatch centre with changing load scenarios. The dynamic multi-area ED (MAED) problem is more complex due to the additional tie-line, ramp-rate and area-wise power balance constraints. Nature inspired (NI) heuristic optimization methods are gaining popularity over the traditional methods for complex problems. This work presents the modified particle swarm optimization (PSO) based techniques where parameter automation is effectively used for improving the search efficiency by avoiding stagnation to a sub-optimal result. This work validates the performance of the PSO variants with traditional solver GAMS for single as well as multi-area economic dispatch (MAED) on three test cases of a large 140-unit standard test system having complex constraints.

Artificial Intelligence Techniques for the Berth Allocation and Container Stacking Problems in Container Terminals

NASA Astrophysics Data System (ADS)

Salido, Miguel A.; Rodriguez-Molins, Mario; Barber, Federico

The Container Stacking Problem and the Berth Allocation Problem are two important problems in maritime container terminal's management which are clearly related. Terminal operators normally demand all containers to be loaded into an incoming vessel should be ready and easily accessible in the terminal before vessel's arrival. Similarly, customers (i.e., vessel owners) expect prompt berthing of their vessels upon arrival. In this paper, we present an artificial intelligence based-integrated system to relate these problems. Firstly, we develop a metaheuristic algorithm for berth allocation which generates an optimized order of vessel to be served according to existing berth constraints. Secondly, we develop a domain-oriented heuristic planner for calculating the number of reshuffles needed to allocate containers in the appropriate place for a given berth ordering of vessels. By combining these optimized solutions, terminal operators can be assisted to decide the most appropriated solution in each particular case.

Large-Scale Multiantenna Multisine Wireless Power Transfer

NASA Astrophysics Data System (ADS)

Huang, Yang; Clerckx, Bruno

2017-11-01

Wireless Power Transfer (WPT) is expected to be a technology reshaping the landscape of low-power applications such as the Internet of Things, Radio Frequency identification (RFID) networks, etc. Although there has been some progress towards multi-antenna multi-sine WPT design, the large-scale design of WPT, reminiscent of massive MIMO in communications, remains an open challenge. In this paper, we derive efficient multiuser algorithms based on a generalizable optimization framework, in order to design transmit sinewaves that maximize the weighted-sum/minimum rectenna output DC voltage. The study highlights the significant effect of the nonlinearity introduced by the rectification process on the design of waveforms in multiuser systems. Interestingly, in the single-user case, the optimal spatial domain beamforming, obtained prior to the frequency domain power allocation optimization, turns out to be Maximum Ratio Transmission (MRT). In contrast, in the general weighted sum criterion maximization problem, the spatial domain beamforming optimization and the frequency domain power allocation optimization are coupled. Assuming channel hardening, low-complexity algorithms are proposed based on asymptotic analysis, to maximize the two criteria. The structure of the asymptotically optimal spatial domain precoder can be found prior to the optimization. The performance of the proposed algorithms is evaluated. Numerical results confirm the inefficiency of the linear model-based design for the single and multi-user scenarios. It is also shown that as nonlinear model-based designs, the proposed algorithms can benefit from an increasing number of sinewaves.

Multiple Interacting Risk Factors: On Methods for Allocating Risk Factor Interactions.

PubMed

Price, Bertram; MacNicoll, Michael

2015-05-01

A persistent problem in health risk analysis where it is known that a disease may occur as a consequence of multiple risk factors with interactions is allocating the total risk of the disease among the individual risk factors. This problem, referred to here as risk apportionment, arises in various venues, including: (i) public health management, (ii) government programs for compensating injured individuals, and (iii) litigation. Two methods have been described in the risk analysis and epidemiology literature for allocating total risk among individual risk factors. One method uses weights to allocate interactions among the individual risk factors. The other method is based on risk accounting axioms and finding an optimal and unique allocation that satisfies the axioms using a procedure borrowed from game theory. Where relative risk or attributable risk is the risk measure, we find that the game-theory-determined allocation is the same as the allocation where risk factor interactions are apportioned to individual risk factors using equal weights. Therefore, the apportionment problem becomes one of selecting a meaningful set of weights for allocating interactions among the individual risk factors. Equal weights and weights proportional to the risks of the individual risk factors are discussed. © 2015 Society for Risk Analysis.

75 FR 76975 - 2015 Resource Pool-Sierra Nevada Region

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-10

...The Western Area Power Administration (Western), a Federal power marketing administration of DOE, announces the Final 2015 Resource Pool allocations pursuant to its 2004 Power Marketing Plan (Marketing Plan) for the Sierra Nevada Customer Service Region (SNR). This notice includes a summary of the comments received on Western's proposed 2015 Resource Pool allocations and Western's responses.

Fund allocation using capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita; Darus, Maslina

2014-09-01

In investment fund allocation, it is unwise for an investor to distribute his fund into several assets simultaneously due to economic reasons. One solution is to allocate the fund into a particular asset at a time in a sequence that will either maximize returns or minimize risks depending on the investor's objective. The vehicle routing problem (VRP) provides an avenue to this issue. VRP answers the question on how to efficiently use the available fleet of vehicles to meet a given service demand, subjected to a set of operational requirements. This paper proposes an idea of using capacitated vehicle routing problem (CVRP) to optimize investment fund allocation by employing data of selected stocks in the FTSE Bursa Malaysia. Results suggest that CRVP can be applied to solve the issue of investment fund allocation and increase the investor's profit.

Consideration of environmental noise effects in transportation planning by governmental entities

NASA Technical Reports Server (NTRS)

Mayo, L. H.

1975-01-01

Environmental concerns are reviewed with respect to major transportation systems: the interstate highway system and commercial air transportation. The type of planning that was done for interstate highway systems is described, and the shift in social value emphasis that has become apparent since the interstate system was authorized is considered. Other topics discussed include the constitutional framework for the allocation of governmental power with respect to transportation systems planning, governmental assessment of the aircraft noise problem, and evaluating the social benefit of noise abatement.

Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and Solutions

PubMed Central

2017-01-01

Multi-robot task allocation is one of the main problems to address in order to design a multi-robot system, very especially when robots form coalitions that must carry out tasks before a deadline. A lot of factors affect the performance of these systems and among them, this paper is focused on the physical interference effect, produced when two or more robots want to access the same point simultaneously. To our best knowledge, this paper presents the first formal description of multi-robot task allocation that includes a model of interference. Thanks to this description, the complexity of the allocation problem is analyzed. Moreover, the main contribution of this paper is to provide the conditions under which the optimal solution of the aforementioned allocation problem can be obtained solving an integer linear problem. The optimal results are compared to previous allocation algorithms already proposed by the first two authors of this paper and with a new method proposed in this paper. The results obtained show how the new task allocation algorithms reach up more than an 80% of the median of the optimal solution, outperforming previous auction algorithms with a huge reduction of the execution time. PMID:28118384

Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and Solutions.

PubMed

Guerrero, Jose; Oliver, Gabriel; Valero, Oscar

2017-01-01

Multi-robot task allocation is one of the main problems to address in order to design a multi-robot system, very especially when robots form coalitions that must carry out tasks before a deadline. A lot of factors affect the performance of these systems and among them, this paper is focused on the physical interference effect, produced when two or more robots want to access the same point simultaneously. To our best knowledge, this paper presents the first formal description of multi-robot task allocation that includes a model of interference. Thanks to this description, the complexity of the allocation problem is analyzed. Moreover, the main contribution of this paper is to provide the conditions under which the optimal solution of the aforementioned allocation problem can be obtained solving an integer linear problem. The optimal results are compared to previous allocation algorithms already proposed by the first two authors of this paper and with a new method proposed in this paper. The results obtained show how the new task allocation algorithms reach up more than an 80% of the median of the optimal solution, outperforming previous auction algorithms with a huge reduction of the execution time.

Nurses' perceptions of individual and organizational political reasons for horizontal peer bullying.

PubMed

Katrinli, Alev; Atabay, Gulem; Gunay, Gonca; Cangarli, Burcu Guneri

2010-09-01

Nurses are exposed to bullying for various reasons. It has been argued that the reason for bullying can be political, meaning that the behavior occurs to serve the self-interests of the perpetrators. This study aims to identify how nurses perceive the relevance of individual and political reasons for bullying behaviors. In February 2009 a survey was conducted with nurses working in a research and training hospital located in Turkey. The results showed that the aim of influencing promotion, task assignments, performance appraisal, recruitment, dismissal, allocation of equipment and operational means, together with allocation of personal benefits and organizational structure decisions, were perceived as potential political reasons for bullying by nurses. Moreover, the reasons for the various bullying behaviors were perceived as relevant to individual characteristics, namely, the perpetrators' need for power, and their psychological and private life problems.

A Legal Primer for the Obesity Prevention Movement

PubMed Central

Mermin, Seth E.

2009-01-01

Public health advocates and scientists working on obesity prevention policy face challenges in balancing legal rights, individual freedom, and societal health goals. In particular, the US Constitution and the 50 state constitutions place limits on the ability of government to act, even in the best interests of the public. To help policymakers avoid crossing constitutional boundaries, we distilled the legal concepts most relevant to formulating policies aimed at preventing obesity: police power; allocation of power among federal, state, and local governments; freedom of speech; property rights; privacy; equal protection; and contract rights. The goal is to allow policymakers to avoid potential constitutional problems in the formation of obesity prevention policy. PMID:19696384

Application of Hybrid Optimization-Expert System for Optimal Power Management on Board Space Power Station

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Basheer, Omar Ali AL

1996-01-01

The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.

18 CFR 367.28 - Methods of allocation.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Methods of allocation... Instructions § 367.28 Methods of allocation. Indirect costs and compensation for use of capital must be allocated to projects in accordance with the service company's applicable and currently effective methods of...

18 CFR 367.28 - Methods of allocation.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Methods of allocation... Instructions § 367.28 Methods of allocation. Indirect costs and compensation for use of capital must be allocated to projects in accordance with the service company's applicable and currently effective methods of...

On Market-Based Coordination of Thermostatically Controlled Loads With User Preference

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

Li, Sen; Zhang, Wei; Lian, Jianming

2014-12-15

This paper presents a market-based control framework to coordinate a group of autonomous Thermostatically Controlled Loads (TCL) to achieve the system-level objectives with pricing incentives. The problem is formulated as maximizing the social welfare subject to feeder power constraint. It allows the coordinator to affect the aggregated power of a group of dynamical systems, and creates an interactive market where the users and the coordinator cooperatively determine the optimal energy allocation and energy price. The optimal pricing strategy is derived, which maximizes social welfare while respecting the feeder power constraint. The bidding strategy is also designed to compute the optimalmore » price in real time (e.g., every 5 minutes) based on local device information. The coordination framework is validated with realistic simulations in GridLab-D. Extensive simulation results demonstrate that the proposed approach effectively maximizes the social welfare and decreases power congestion at key times.« less

Essays on electricity transmission investment and financial transmission rights

NASA Astrophysics Data System (ADS)

Shang, Wenzhuo

The U.S. electric power industry has been going through fundamental restructuring and realignment since the 1990's. Many issues and problems have emerged during the transition, and both economists and engineers have been looking for the solutions fervently. In this dissertation, which consists primarily of three essays, we apply economics theory and techniques to the power industry and address two related issues, transmission investment and financial transmission rights (FTRs). The first essay takes the decentralized perspective and investigates the efficiency attribute of market-based transmission investment under perfect competition. We clarify, for the first time, the nature of the externality created by loop flows that causes transmission investment to be inefficient. Our findings have important implications for better understanding of transmission market design and creating incentives for efficient transmission investment. In the second essay, we define several rules for allocating transmission investment cost within the framework of cooperative game theory. These rules provide fair, stable or efficient cost allocations in theory and are good benchmarks against which the allocation mechanism in practice can be compared and improved upon. In the last essay, we make exploratory efforts in analyzing and assessing empirically the performance of the Midwest independent system operator (MISO) FTR auction market. We reveal some stylized facts about this young market and find that it is not efficient under the risk-neutrality assumption. We also point out and correct the drawbacks in previous related work and suggest about more complete empirical work in future. In all, this dissertation makes both theoretic and empirical analysis of the two hot issues related to the power industry and comes up with findings that have important implications for the development of this industry.

Two-way DF relaying assisted D2D communication: ergodic rate and power allocation

NASA Astrophysics Data System (ADS)

Ni, Yiyang; Wang, Yuxi; Jin, Shi; Wong, Kai-Kit; Zhu, Hongbo

2017-12-01

In this paper, we investigate the ergodic rate for a device-to-device (D2D) communication system aided by a two-way decode-and-forward (DF) relay node. We first derive closed-form expressions for the ergodic rate of the D2D link under asymmetric and symmetric cases, respectively. We subsequently discuss two special scenarios including weak interference case and high signal-to-noise ratio case. Then we derive the tight approximations for each of the considered scenarios. Assuming that each transmitter only has access to its own statistical channel state information (CSI), we further derive closed-form power allocation strategy to improve the system performance according to the analytical results of the ergodic rate. Furthermore, some insights are provided for the power allocation strategy based on the analytical results. The strategies are easy to compute and require to know only the channel statistics. Numerical results show the accuracy of the analysis results under various conditions and test the availability of the power allocation strategy.

Energy Efficiency Optimization in Relay-Assisted MIMO Systems With Perfect and Statistical CSI

NASA Astrophysics Data System (ADS)

Zappone, Alessio; Cao, Pan; Jorswieck, Eduard A.

2014-01-01

A framework for energy-efficient resource allocation in a single-user, amplify-and-forward relay-assisted MIMO system is devised in this paper. Previous results in this area have focused on rate maximization or sum power minimization problems, whereas fewer results are available when bits/Joule energy efficiency (EE) optimization is the goal. The performance metric to optimize is the ratio between the system's achievable rate and the total consumed power. The optimization is carried out with respect to the source and relay precoding matrices, subject to QoS and power constraints. Such a challenging non-convex problem is tackled by means of fractional programming and and alternating maximization algorithms, for various CSI assumptions at the source and relay. In particular the scenarios of perfect CSI and those of statistical CSI for either the source-relay or the relay-destination channel are addressed. Moreover, sufficient conditions for beamforming optimality are derived, which is useful in simplifying the system design. Numerical results are provided to corroborate the validity of the theoretical findings.

Proposing integrated Shannon's entropy-inverse data envelopment analysis methods for resource allocation problem under a fuzzy environment

NASA Astrophysics Data System (ADS)

Çakır, Süleyman

2017-10-01

In this study, a two-phase methodology for resource allocation problems under a fuzzy environment is proposed. In the first phase, the imprecise Shannon's entropy method and the acceptability index are suggested, for the first time in the literature, to select input and output variables to be used in the data envelopment analysis (DEA) application. In the second step, an interval inverse DEA model is executed for resource allocation in a short run. In an effort to exemplify the practicality of the proposed fuzzy model, a real case application has been conducted involving 16 cement firms listed in Borsa Istanbul. The results of the case application indicated that the proposed hybrid model is a viable procedure to handle input-output selection and resource allocation problems under fuzzy conditions. The presented methodology can also lend itself to different applications such as multi-criteria decision-making problems.

77 FR 32183 - Transmission Planning and Cost Allocation by Transmission Owning and Operating Public Utilities

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-31

... it would not wait for systemic problems to undermine transmission planning before action is taken... that the development of transmission facilities can involve long lead times and complex problems... rather than allowing the problems in transmission planning and cost allocation to continue or to increase...

Augmented Lagrange Hopfield network for solving economic dispatch problem in competitive environment

NASA Astrophysics Data System (ADS)

Vo, Dieu Ngoc; Ongsakul, Weerakorn; Nguyen, Khai Phuc

2012-11-01

This paper proposes an augmented Lagrange Hopfield network (ALHN) for solving economic dispatch (ED) problem in the competitive environment. The proposed ALHN is a continuous Hopfield network with its energy function based on augmented Lagrange function for efficiently dealing with constrained optimization problems. The ALHN method can overcome the drawbacks of the conventional Hopfield network such as local optimum, long computational time, and linear constraints. The proposed method is used for solving the ED problem with two revenue models of revenue based on payment for power delivered and payment for reserve allocated. The proposed ALHN has been tested on two systems of 3 units and 10 units for the two considered revenue models. The obtained results from the proposed methods are compared to those from differential evolution (DE) and particle swarm optimization (PSO) methods. The result comparison has indicated that the proposed method is very efficient for solving the problem. Therefore, the proposed ALHN could be a favorable tool for ED problem in the competitive environment.

Effect of distributed generation installation on power loss using genetic algorithm method

NASA Astrophysics Data System (ADS)

Hasibuan, A.; Masri, S.; Othman, W. A. F. W. B.

2018-02-01

Injection of the generator distributed in the distribution network can affect the power system significantly. The effect that occurs depends on the allocation of DG on each part of the distribution network. Implementation of this approach has been made to the IEEE 30 bus standard and shows the optimum location and size of the DG which shows a decrease in power losses in the system. This paper aims to show the impact of distributed generation on the distribution system losses. The main purpose of installing DG on a distribution system is to reduce power losses on the power system.Some problems in power systems that can be solved with the installation of DG, one of which will be explored in the use of DG in this study is to reduce the power loss in the transmission line. Simulation results from case studies on the IEEE 30 bus standard system show that the system power loss decreased from 5.7781 MW to 1,5757 MW or just 27,27%. The simulated DG is injected to the bus with the lowest voltage drop on the bus number 8.

A Simplified GCS-DCSK Modulation and Its Performance Optimization

NASA Astrophysics Data System (ADS)

Xu, Weikai; Wang, Lin; Chi, Chong-Yung

2016-12-01

In this paper, a simplified Generalized Code-Shifted Differential Chaos Shift Keying (GCS-DCSK) whose transmitter never needs any delay circuits, is proposed. However, its performance is deteriorated because the orthogonality between substreams cannot be guaranteed. In order to optimize its performance, the system model of the proposed GCS-DCSK with power allocations on substreams is presented. An approximate bit error rate (BER) expression of the proposed model, which is a function of substreams’ power, is derived using Gaussian Approximation. Based on the BER expression, an optimal power allocation strategy between information substreams and reference substream is obtained. Simulation results show that the BER performance of the proposed GCS-DCSK with the optimal power allocation can be significantly improved when the number of substreams M is large.

Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

2017-04-01

Capacitated Vehicle Routing Problem-Investment Fund Allocation Problem (CVRP-IFAP) provides investors with a sequence of assets to allocate their funds into. To minimize total risks of investment in CVRP-IFAP covariance values measure the risks between two assets. Another measure of risks are correlation values between returns. The correlation values can be used to diversify the risk of investment loss in order to optimize expected return against a certain level of risk. This study compares the total risk obtained from CVRP-IFAP when using covariance values and correlation values. Results show that CVRP-IFAP with covariance values provides lesser total risks and a significantly better measure of risk.

Economic aspects of spectrum management

NASA Technical Reports Server (NTRS)

Stibolt, R. D.

1979-01-01

Problems associated with the allocation of the radio frequency spectrum are addressed. It is observed that the current method very likely does not allocate the resource to those most valuing its use. Ecomonic criteria by which the effectiveness of resource allocation schemes can be judged are set forth and some thoughts on traditional objections to implementation of market characteristics into frequency allocation are offered. The problem of dividing orbit and spectrum between two satellite services sharing the same band but having significantly different system characteristics is discussed. The problem is compounded by the likelihood that one service will commence operation much sooner than the other. Some alternative schemes are offered that, within proper international constraints, could achieve a desired flexibility in the division of orbit and frequency between the two services domestically over the next several years.

Game Theory for Wireless Sensor Networks: A Survey

PubMed Central

Shi, Hai-Yan; Wang, Wan-Liang; Kwok, Ngai-Ming; Chen, Sheng-Yong

2012-01-01

Game theory (GT) is a mathematical method that describes the phenomenon of conflict and cooperation between intelligent rational decision-makers. In particular, the theory has been proven very useful in the design of wireless sensor networks (WSNs). This article surveys the recent developments and findings of GT, its applications in WSNs, and provides the community a general view of this vibrant research area. We first introduce the typical formulation of GT in the WSN application domain. The roles of GT are described that include routing protocol design, topology control, power control and energy saving, packet forwarding, data collection, spectrum allocation, bandwidth allocation, quality of service control, coverage optimization, WSN security, and other sensor management tasks. Then, three variations of game theory are described, namely, the cooperative, non-cooperative, and repeated schemes. Finally, existing problems and future trends are identified for researchers and engineers in the field. PMID:23012533

Learning automata-based solutions to the nonlinear fractional knapsack problem with applications to optimal resource allocation.

PubMed

Granmo, Ole-Christoffer; Oommen, B John; Myrer, Svein Arild; Olsen, Morten Goodwin

2007-02-01

This paper considers the nonlinear fractional knapsack problem and demonstrates how its solution can be effectively applied to two resource allocation problems dealing with the World Wide Web. The novel solution involves a "team" of deterministic learning automata (LA). The first real-life problem relates to resource allocation in web monitoring so as to "optimize" information discovery when the polling capacity is constrained. The disadvantages of the currently reported solutions are explained in this paper. The second problem concerns allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. This is the scenario encountered when the user has to evaluate multiple web sites by accessing a limited number of web pages, and the proportions of interest are the fraction of each web site that is successfully validated by an HTML validator. Using the general LA paradigm to tackle both of the real-life problems, the proposed scheme improves a current solution in an online manner through a series of informed guesses that move toward the optimal solution. At the heart of the scheme, a team of deterministic LA performs a controlled random walk on a discretized solution space. Comprehensive experimental results demonstrate that the discretization resolution determines the precision of the scheme, and that for a given precision, the current solution (to both problems) is consistently improved until a nearly optimal solution is found--even for switching environments. Thus, the scheme, while being novel to the entire field of LA, also efficiently handles a class of resource allocation problems previously not addressed in the literature.

Game theoretic power allocation and waveform selection for satellite communications

NASA Astrophysics Data System (ADS)

Shu, Zhihui; Wang, Gang; Tian, Xin; Shen, Dan; Pham, Khanh; Blasch, Erik; Chen, Genshe

2015-05-01

Game theory is a useful method to model interactions between agents with conflicting interests. In this paper, we set up a Game Theoretic Model for Satellite Communications (SATCOM) to solve the interaction between the transmission pair (blue side) and the jammer (red side) to reach a Nash Equilibrium (NE). First, the IFT Game Application Model (iGAM) for SATCOM is formulated to improve the utility of the transmission pair while considering the interference from a jammer. Specifically, in our framework, the frame error rate performance of different modulation and coding schemes is used in the game theoretic solution. Next, the game theoretic analysis shows that the transmission pair can choose the optimal waveform and power given the received power from the jammer. We also describe how the jammer chooses the optimal power given the waveform and power allocation from the transmission pair. Finally, simulations are implemented for the iGAM and the simulation results show the effectiveness of the SATCOM power allocation, waveform selection scheme, and jamming mitigation.

Why are the many poor?

PubMed

Townsend, P

1986-01-01

In this article the author restates the same arguments put forward in the first Fabian Tract of 1884 entitled Why Are the Many Poor? Today, mass poverty is still the central problem facing the British nation and all nations. The only long-term remedy is to restrict the power and wealth of the rich, to dismantle the present structures of social privilege, and to build social institutions based on fair allocation of wealth and on social equality. The public debate of one hundred years ago on the connections between poverty and wealth is revived in this article.

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

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

Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subjectmore » that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.« less

10 CFR Appendix D to Subpart D of... - Classes of Actions that Normally Require EISs

Code of Federal Regulations, 2014 CFR

2014-01-01

... [Reserved] D7 Contracts, policies, and marketing and allocation plans for electric power D8 Import or export... operational change D10 Treatment, storage, and disposal facilities for high-level waste and spent nuclear fuel... Contracts, Policies, and Marketing and Allocation Plans for Electric Power Establishment and implementation...

75 FR 78988 - Post-2014 Resource Pool-Loveland Area Projects, Allocation Procedures and Call for Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-17

... Administration (Western), a Federal power marketing agency of the Department of Energy (DOE), is publishing this... allocation of Federal electric power. Subpart C of the Energy Planning and Management Program (Program... for applications, in conjunction with the Loveland Area Projects (LAP) Final Post-1989 Marketing Plan...

Resource allocation in shared spectrum access communications for operators with diverse service requirements

NASA Astrophysics Data System (ADS)

Kibria, Mirza Golam; Villardi, Gabriel Porto; Ishizu, Kentaro; Kojima, Fumihide; Yano, Hiroyuki

2016-12-01

In this paper, we study inter-operator spectrum sharing and intra-operator resource allocation in shared spectrum access communication systems and propose efficient dynamic solutions to address both inter-operator and intra-operator resource allocation optimization problems. For inter-operator spectrum sharing, we present two competent approaches, namely the subcarrier gain-based sharing and fragmentation-based sharing, which carry out fair and flexible allocation of the available shareable spectrum among the operators subject to certain well-defined sharing rules, traffic demands, and channel propagation characteristics. The subcarrier gain-based spectrum sharing scheme has been found to be more efficient in terms of achieved throughput. However, the fragmentation-based sharing is more attractive in terms of computational complexity. For intra-operator resource allocation, we consider resource allocation problem with users' dissimilar service requirements, where the operator supports users with delay constraint and non-delay constraint service requirements, simultaneously. This optimization problem is a mixed-integer non-linear programming problem and non-convex, which is computationally very expensive, and the complexity grows exponentially with the number of integer variables. We propose less-complex and efficient suboptimal solution based on formulating exact linearization, linear approximation, and convexification techniques for the non-linear and/or non-convex objective functions and constraints. Extensive simulation performance analysis has been carried out that validates the efficiency of the proposed solution.

A Framework for Optimal Control Allocation with Structural Load Constraints

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Taylor, Brian R.; Jutte, Christine V.; Burken, John J.; Trinh, Khanh V.; Bodson, Marc

2010-01-01

Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.

Smart LED allocation scheme for efficient multiuser visible light communication networks.

PubMed

Sewaiwar, Atul; Tiwari, Samrat Vikramaditya; Chung, Yeon Ho

2015-05-18

In a multiuser bidirectional visible light communication (VLC), a large number of LEDs or an LED array needs to be allocated in an efficient manner to ensure sustainable data rate and link quality. Moreover, in order to support an increasing or decreasing number of users in the network, the LED allocation is required to be performed dynamically. In this paper, a novel smart LED allocation scheme for efficient multiuser VLC networks is presented. The proposed scheme allocates RGB LEDs to multiple users in a dynamic and efficient fashion, while satisfying illumination requirements in an indoor environment. The smart LED array comprised of RGB LEDs is divided into sectors according to the location of the users. The allocated sectors then provide optical power concentration toward the users for efficient and reliable data transmission. An algorithm for the dynamic allocation of the LEDs is also presented. To verify its effective resource allocation feature of the proposed scheme, simulations were performed. It is found that the proposed smart LED allocation scheme provides the effect of optical beamforming toward individual users, thereby increasing the collective power concentration of the optical signals on the desirable users and resulting in significantly increased data rate, while ensuring sufficient illumination in a multiuser VLC environment.

A novel profit-allocation strategy for SDN enterprises

NASA Astrophysics Data System (ADS)

Hu, Wei; Hou, Ye; Tian, Longwei; Li, Yuan

2017-01-01

Aiming to solve the problem of profit allocation for supply and demand network (SDN) enterprises that ignores risk factors and generates low satisfaction, a novel profit-allocation model based on cooperative game theory and TOPSIS is proposed. This new model avoids the defect of the single-profit allocation model by introducing risk factors, compromise coefficients and high negotiation points. By measuring the Euclidean distance between the ideal solution vector and the negative ideal solution vector, every node's satisfaction problem for the SDN was resolved, and the mess phenomenon was avoided. Finally, the rationality and effectiveness of the proposed model was verified using a numerical example.

Optimal allocation model of construction land based on two-level system optimization theory

NASA Astrophysics Data System (ADS)

Liu, Min; Liu, Yanfang; Xia, Yuping; Lei, Qihong

2007-06-01

The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.

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

Hameed, Abdul; Khoshkbarforoushha, Alireza; Ranjan, Rajiv

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subjectmore » that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.« less

Research on power source structure optimization for East China Power Grid

NASA Astrophysics Data System (ADS)

Xu, Lingjun; Sang, Da; Zhang, Jianping; Tang, Chunyi; Xu, Da

2017-05-01

The structure of east china power grid is not reasonable for the coal power takes a much higher proportion than hydropower, at present the coal power takes charge of most peak load regulation, and the pressure of peak load regulation cannot be ignored. The nuclear power, wind power, photovoltaic, other clean energy and hydropower, coal power and wind power from outside will be actively developed in future, which increases the pressure of peak load regulation. According to development of economic and social, Load status and load prediction, status quo and planning of power source and the characteristics of power source, the peak load regulation balance is carried out and put forward a reasonable plan of power source allocation. The ultimate aim is to optimize the power source structure and to provide reference for power source allocation in east china.

Trading a Problem-solving Task

NASA Astrophysics Data System (ADS)

Matsubara, Shigeo

This paper focuses on a task allocation problem, especially cases where the task is to find a solution in a search problem or a constraint satisfaction problem. If the search problem is hard to solve, a contractor may fail to find a solution. Here, the more computational resources such as the CPU time the contractor invests in solving the search problem, the more a solution is likely to be found. This brings about a new problem that a contractee has to find an appropriate level of the quality in a task achievement as well as to find an efficient allocation of a task among contractors. For example, if the contractee asks the contractor to find a solution with certainty, the payment from the contractee to the contractor may exceed the contractee's benefit from obtaining a solution, which discourages the contractee from trading a task. However, solving this problem is difficult because the contractee cannot ascertain the contractor's problem-solving ability such as the amount of available resources and knowledge (e.g. algorithms, heuristics) or monitor what amount of resources are actually invested in solving the allocated task. To solve this problem, we propose a task allocation mechanism that is able to choose an appropriate level of the quality in a task achievement and prove that this mechanism guarantees that each contractor reveals its true information. Moreover, we show that our mechanism can increase the contractee's utility compared with a simple auction mechanism by using computer simulation.

Bayesian adaptive phase II screening design for combination trials.

PubMed

Cai, Chunyan; Yuan, Ying; Johnson, Valen E

2013-01-01

Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Simulation studies show that the proposed design substantially outperforms the conventional multiarm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while allocating substantially more patients to efficacious treatments. The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while providing higher power to identify the best treatment at the end of the trial.

Resource allocation for wildland fire suppression planning using a stochastic program

Treesearch

Alex Taylor Masarie

2011-01-01

Resource allocation for wildland fire suppression problems, referred to here as Fire-S problems, have been studied for over a century. Not only have the many variants of the base Fire-S problem made it such a durable one to study, but advances in suppression technology and our ever-expanding knowledge of and experience with wildland fire behavior have required almost...

Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch

NASA Astrophysics Data System (ADS)

Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.

2014-10-01

The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.

Comprehensive reliability allocation method for CNC lathes based on cubic transformed functions of failure mode and effects analysis

NASA Astrophysics Data System (ADS)

Yang, Zhou; Zhu, Yunpeng; Ren, Hongrui; Zhang, Yimin

2015-03-01

Reliability allocation of computerized numerical controlled(CNC) lathes is very important in industry. Traditional allocation methods only focus on high-failure rate components rather than moderate failure rate components, which is not applicable in some conditions. Aiming at solving the problem of CNC lathes reliability allocating, a comprehensive reliability allocation method based on cubic transformed functions of failure modes and effects analysis(FMEA) is presented. Firstly, conventional reliability allocation methods are introduced. Then the limitations of direct combination of comprehensive allocation method with the exponential transformed FMEA method are investigated. Subsequently, a cubic transformed function is established in order to overcome these limitations. Properties of the new transformed functions are discussed by considering the failure severity and the failure occurrence. Designers can choose appropriate transform amplitudes according to their requirements. Finally, a CNC lathe and a spindle system are used as an example to verify the new allocation method. Seven criteria are considered to compare the results of the new method with traditional methods. The allocation results indicate that the new method is more flexible than traditional methods. By employing the new cubic transformed function, the method covers a wider range of problems in CNC reliability allocation without losing the advantages of traditional methods.

Scheduling language and algorithm development study. Volume 1, phase 2: Design considerations for a scheduling and resource allocation system

NASA Technical Reports Server (NTRS)

Morrell, R. A.; Odoherty, R. J.; Ramsey, H. R.; Reynolds, C. C.; Willoughby, J. K.; Working, R. D.

1975-01-01

Data and analyses related to a variety of algorithms for solving typical large-scale scheduling and resource allocation problems are presented. The capabilities and deficiencies of various alternative problem solving strategies are discussed from the viewpoint of computer system design.

18 CFR 367.17 - Comprehensive inter-period income tax allocation.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Comprehensive inter... NATURAL GAS ACT General Instructions § 367.17 Comprehensive inter-period income tax allocation. (a) Where... tax method. In general, comprehensive inter-period tax allocation should be followed whenever...

A heuristic approach to handle capacitated facility location problem evaluated using clustering internal evaluation

NASA Astrophysics Data System (ADS)

Sutanto, G. R.; Kim, S.; Kim, D.; Sutanto, H.

2018-03-01

One of the problems in dealing with capacitated facility location problem (CFLP) is occurred because of the difference between the capacity numbers of facilities and the number of customers that needs to be served. A facility with small capacity may result in uncovered customers. These customers need to be re-allocated to another facility that still has available capacity. Therefore, an approach is proposed to handle CFLP by using k-means clustering algorithm to handle customers’ allocation. And then, if customers’ re-allocation is needed, is decided by the overall average distance between customers and the facilities. This new approach is benchmarked to the existing approach by Liao and Guo which also use k-means clustering algorithm as a base idea to decide the facilities location and customers’ allocation. Both of these approaches are benchmarked by using three clustering evaluation methods with connectedness, compactness, and separations factors.

Flexible power and bandwidth allocation in mobile satellites

NASA Astrophysics Data System (ADS)

Keyes, L. A.

The introduction of L-band mobile communication services by spot beam satellites creates a payload design challenge due to uncertainty in the location and size of the new market to be served. A combination of payload technologies that allow a flexible allocation of power and bandwidth to any portion of the coverage area is described. Power flexibility is achieved by a novel combination of a low-level beam-forming network and a matrix power module which ensures equal sharing of power among individual amplifiers. This eliminates the loss of efficiency and increased mass when an amplifier associated with a beam must be over-designed to meet uncertainties in power distribution between beams. Flexibility in allocation of bandwidth to beams is achieved by intermediate frequency subdivision of the L-band service categories defined by ITU. These spectral subdivisions are assigned to beams by an IF interconnect matrix having beam ports and filter ports as inputs and outputs, respectively. Two such filter switch matrices are required, one for the inbound L-band to feeder link transponder, and one for the outbound feeder link to L-band transponder.

Multi-Agent Coordination Techniques for Naval Tactical Combat Resources Management

DTIC Science & Technology

2008-07-01

resource coordination and cooperation problems. The combat resource allocation planning problem is treated in the companion report [2]. 2.3 Resource...report focuses on the resource coordination problem, while allocation algorithms are discussed in the companion report [2]. First, coordination in...classification of each should be indicated as with the title.) Canada’s Leader in Defence and National Security Science and Technology Chef de file au Canada en

Performance analysis of optimal power allocation in wireless cooperative communication systems

NASA Astrophysics Data System (ADS)

Babikir Adam, Edriss E.; Samb, Doudou; Yu, Li

2013-03-01

Cooperative communication has been recently proposed in wireless communication systems for exploring the inherent spatial diversity in relay channels.The Amplify-and-Forward (AF) cooperation protocols with multiple relays have not been sufficiently investigated even if it has a low complexity in term of implementation. We consider in this work a cooperative diversity system in which a source transmits some information to a destination with the help of multiple relay nodes with AF protocols and investigate the optimality of allocating powers both at the source and the relays system by optimizing the symbol error rate (SER) performance in an efficient way. Firstly we derive a closedform SER formulation for MPSK signal using the concept of moment generating function and some statistical approximations in high signal to noise ratio (SNR) for the system under studied. We then find a tight corresponding lower bound which converges to the same limit as the theoretical upper bound and develop an optimal power allocation (OPA) technique with mean channel gains to minimize the SER. Simulation results show that our scheme outperforms the equal power allocation (EPA) scheme and is tight to the theoretical approximation based on the SER upper bound in high SNR for different number of relays.

Resource Allocation in Healthcare: Implications of Models of Medicine as a Profession

PubMed Central

Kluge, Eike-Henner W.

2007-01-01

For decades, the problem of how to allocate healthcare resources in a just and equitable fashion has been the subject of concerted discussion and analysis, yet the issue has stubbornly resisted resolution. This article suggests that a major reason for this is that the discussion has focused exclusively on the nature and status of the material resources, and that the nature and role of the medical profession have been entirely ignored. Because physicians are gatekeepers to healthcare resources, their role in allocation is central from a process perspective. This article identifies 3 distinct interpretations of the nature of medicine, shows how each mandates a different method of allocation, and argues that unless an appropriate model of medicine is developed that acknowledges the valid points contained in each of the 3 approaches, the allocation problem will remain unsolvable. PMID:17435657

A mathematical modeling approach to resource allocation for railroad-highway crossing safety upgrades.

PubMed

Konur, Dinçer; Golias, Mihalis M; Darks, Brandon

2013-03-01

State Departments of Transportation (S-DOT's) periodically allocate budget for safety upgrades at railroad-highway crossings. Efficient resource allocation is crucial for reducing accidents at railroad-highway crossings and increasing railroad as well as highway transportation safety. While a specific method is not restricted to S-DOT's, sorting type of procedures are recommended by the Federal Railroad Administration (FRA), United States Department of Transportation for the resource allocation problem. In this study, a generic mathematical model is proposed for the resource allocation problem for railroad-highway crossing safety upgrades. The proposed approach is compared to sorting based methods for safety upgrades of public at-grade railroad-highway crossings in Tennessee. The comparison shows that the proposed mathematical modeling approach is more efficient than sorting methods in reducing accidents and severity. Copyright © 2012 Elsevier Ltd. All rights reserved.

Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System.

PubMed

Chinnadurai, Sunil; Selvaprabhu, Poongundran; Jeong, Yongchae; Jiang, Xueqin; Lee, Moon Ho

2017-09-18

In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE) maximization problem in a 5G massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) downlink system with imperfect channel state information (CSI) at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA) algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM). A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP) that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach's algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.

Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System

PubMed Central

Jeong, Yongchae; Jiang, Xueqin; Lee, Moon Ho

2017-01-01

In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE) maximization problem in a 5G massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) downlink system with imperfect channel state information (CSI) at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA) algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM). A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP) that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach’s algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme. PMID:28927019

An Approach for Transmission Loss and Cost Allocation by Loss Allocation Index and Co-operative Game Theory

NASA Astrophysics Data System (ADS)

Khan, Baseem; Agnihotri, Ganga; Mishra, Anuprita S.

2016-03-01

In the present work authors proposed a novel method for transmission loss and cost allocation to users (generators and loads). In the developed methodology transmission losses are allocated to users based on their usage of the transmission line. After usage allocation, particular loss allocation indices (PLAI) are evaluated for loads and generators. Also Cooperative game theory approach is applied for comparison of results. The proposed method is simple and easy to implement on the practical power system. Sample 6 bus and IEEE 14 bus system is used for showing the effectiveness of proposed method.

A GA based penalty function technique for solving constrained redundancy allocation problem of series system with interval valued reliability of components

NASA Astrophysics Data System (ADS)

Gupta, R. K.; Bhunia, A. K.; Roy, D.

2009-10-01

In this paper, we have considered the problem of constrained redundancy allocation of series system with interval valued reliability of components. For maximizing the overall system reliability under limited resource constraints, the problem is formulated as an unconstrained integer programming problem with interval coefficients by penalty function technique and solved by an advanced GA for integer variables with interval fitness function, tournament selection, uniform crossover, uniform mutation and elitism. As a special case, considering the lower and upper bounds of the interval valued reliabilities of the components to be the same, the corresponding problem has been solved. The model has been illustrated with some numerical examples and the results of the series redundancy allocation problem with fixed value of reliability of the components have been compared with the existing results available in the literature. Finally, sensitivity analyses have been shown graphically to study the stability of our developed GA with respect to the different GA parameters.

Multi-robot task allocation based on two dimensional artificial fish swarm algorithm

NASA Astrophysics Data System (ADS)

Zheng, Taixiong; Li, Xueqin; Yang, Liangyi

2007-12-01

The problem of task allocation for multiple robots is to allocate more relative-tasks to less relative-robots so as to minimize the processing time of these tasks. In order to get optimal multi-robot task allocation scheme, a twodimensional artificial swarm algorithm based approach is proposed in this paper. In this approach, the normal artificial fish is extended to be two dimension artificial fish. In the two dimension artificial fish, each vector of primary artificial fish is extended to be an m-dimensional vector. Thus, each vector can express a group of tasks. By redefining the distance between artificial fish and the center of artificial fish, the behavior of two dimension fish is designed and the task allocation algorithm based on two dimension artificial swarm algorithm is put forward. At last, the proposed algorithm is applied to the problem of multi-robot task allocation and comparer with GA and SA based algorithm is done. Simulation and compare result shows the proposed algorithm is effective.

Resource allocation using ANN in LTE

NASA Astrophysics Data System (ADS)

Yigit, Tuncay; Ersoy, Mevlut

2017-07-01

LTE is the 4th generation wireless network technology, which provides flexible bandwidth, higher data speeds and lower delay. Difficulties may be experienced upon an increase in the number of users in LTE. The objective of this study is to ensure a faster solution to any such resource allocation problems which might arise upon an increase in the number of users. A fast and effective solution has been obtained by making use of Artificial Neural Network. As a result, fast working artificial intelligence methods may be used in resource allocation problems during operation.

Low-Complexity User Selection for Rate Maximization in MIMO Broadcast Channels with Downlink Beamforming

PubMed Central

Silva, Adão; Gameiro, Atílio

2014-01-01

We present in this work a low-complexity algorithm to solve the sum rate maximization problem in multiuser MIMO broadcast channels with downlink beamforming. Our approach decouples the user selection problem from the resource allocation problem and its main goal is to create a set of quasiorthogonal users. The proposed algorithm exploits physical metrics of the wireless channels that can be easily computed in such a way that a null space projection power can be approximated efficiently. Based on the derived metrics we present a mathematical model that describes the dynamics of the user selection process which renders the user selection problem into an integer linear program. Numerical results show that our approach is highly efficient to form groups of quasiorthogonal users when compared to previously proposed algorithms in the literature. Our user selection algorithm achieves a large portion of the optimum user selection sum rate (90%) for a moderate number of active users. PMID:24574928

Magnetic MIMO Signal Processing and Optimization for Wireless Power Transfer

NASA Astrophysics Data System (ADS)

Yang, Gang; Moghadam, Mohammad R. Vedady; Zhang, Rui

2017-06-01

In magnetic resonant coupling (MRC) enabled multiple-input multiple-output (MIMO) wireless power transfer (WPT) systems, multiple transmitters (TXs) each with one single coil are used to enhance the efficiency of simultaneous power transfer to multiple single-coil receivers (RXs) by constructively combining their induced magnetic fields at the RXs, a technique termed "magnetic beamforming". In this paper, we study the optimal magnetic beamforming design in a multi-user MIMO MRC-WPT system. We introduce the multi-user power region that constitutes all the achievable power tuples for all RXs, subject to the given total power constraint over all TXs as well as their individual peak voltage and current constraints. We characterize each boundary point of the power region by maximizing the sum-power deliverable to all RXs subject to their minimum harvested power constraints. For the special case without the TX peak voltage and current constraints, we derive the optimal TX current allocation for the single-RX setup in closed-form as well as that for the multi-RX setup. In general, the problem is a non-convex quadratically constrained quadratic programming (QCQP), which is difficult to solve. For the case of one single RX, we show that the semidefinite relaxation (SDR) of the problem is tight. For the general case with multiple RXs, based on SDR we obtain two approximate solutions by applying time-sharing and randomization, respectively. Moreover, for practical implementation of magnetic beamforming, we propose a novel signal processing method to estimate the magnetic MIMO channel due to the mutual inductances between TXs and RXs. Numerical results show that our proposed magnetic channel estimation and adaptive beamforming schemes are practically effective, and can significantly improve the power transfer efficiency and multi-user performance trade-off in MIMO MRC-WPT systems.

Adaptive Sensing of Time Series with Application to Remote Exploration

NASA Technical Reports Server (NTRS)

Thompson, David R.; Cabrol, Nathalie A.; Furlong, Michael; Hardgrove, Craig; Low, Bryan K. H.; Moersch, Jeffrey; Wettergreen, David

2013-01-01

We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.

8-PSK Signaling over non-linear satellite channels

NASA Technical Reports Server (NTRS)

Horan, Sheila B.; Caballero, Ruben B. Eng.

1996-01-01

Space agencies are under pressure to utilize better bandwidth-efficient communication methods due to the actual allocated frequency bands becoming more congested. Also budget reductions is another problem that the space agencies must deal with. This budget constraint results in simpler spacecraft carrying less communication capabilities and also the reduction in staff to capture data in the earth stations. It is then imperative that the most bandwidth efficient communication methods be utilized. This thesis presents a study of 8-ary Phase Shift Keying (8PSK) modulation with respect to bandwidth, power efficiency, spurious emissions and interference susceptibility over a non-linear satellite channel.

Smart Computer-Assisted Markets

NASA Astrophysics Data System (ADS)

McCabe, Kevin A.; Rassenti, Stephen J.; Smith, Vernon L.

1991-10-01

The deregulation movement has motivated the experimental study of auction markets designed for interdependent network industries such as natural gas pipelines or electric power systems. Decentralized agents submit bids to buy commodity and offers to sell transportation and commodity to a computerized dispatch center. Computer algorithms determine prices and allocations that maximize the gains from exchange in the system relative to the submitted bids and offers. The problem is important, because traditionally the scale and coordination economies in such industries were thought to require regulation. Laboratory experiments are used to study feasibility, limitations, incentives, and performance of proposed market designs for deregulation, providing motivation for new theory.

Theater-Level Gaming and Analysis Workshop for Force Planning. Volume II. Summary, Discussion of Issues and Requirements for Research. September 27- 29, 1977, Held at Xerox International Center for Training and Management Development, Leesburg, Virginia

DTIC Science & Technology

1981-05-01

be allocated to targets on the battlefield and in the rear area. The speaker describes the VECTOR I/NUCLEAR model, a combination of the UNICORN target...outlined. UNICORN is compatible with VECTOR 1 in level of detail. It is an expected value damage model and uses linear programming to optimize the...and a growing appreciation for the power of simulation in addressing large, complex problems, it was only a few short years before these games had

ETR, TRA642. BASEMENT SPACE ALLOCATION FOR EXPERIMENTERS CA. 1966, SOUTHEAST ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

ETR, TRA-642. BASEMENT SPACE ALLOCATION FOR EXPERIMENTERS CA. 1966, SOUTHEAST QUADRANT OF FLOOR. WESTINGHOUSE ATOMIC POWER DIVISION (WAPD) AND BETTIS ATOMIC POWER LABORATORY (BAPL) CONSUME MOST OF THE QUADRANT. PHILLIPS PETROLEUM COMPANY ETR-E-2256, 12/1966. INL INDEX NO. 532-0642-00-706-021256, REV. F. - Idaho National Engineering Laboratory, Test Reactor Area, Materials & Engineering Test Reactors, Scoville, Butte County, ID

Hybrid digital-analog video transmission in wireless multicast and multiple-input multiple-output system

NASA Astrophysics Data System (ADS)

Liu, Yu; Lin, Xiaocheng; Fan, Nianfei; Zhang, Lin

2016-01-01

Wireless video multicast has become one of the key technologies in wireless applications. But the main challenge of conventional wireless video multicast, i.e., the cliff effect, remains unsolved. To overcome the cliff effect, a hybrid digital-analog (HDA) video transmission framework based on SoftCast, which transmits the digital bitstream with the quantization residuals, is proposed. With an effective power allocation algorithm and appropriate parameter settings, the residual gains can be maximized; meanwhile, the digital bitstream can assure transmission of a basic video to the multicast receiver group. In the multiple-input multiple-output (MIMO) system, since nonuniform noise interference on different antennas can be regarded as the cliff effect problem, ParCast, which is a variation of SoftCast, is also applied to video transmission to solve it. The HDA scheme with corresponding power allocation algorithms is also applied to improve video performance. Simulations show that the proposed HDA scheme can overcome the cliff effect completely with the transmission of residuals. What is more, it outperforms the compared WSVC scheme by more than 2 dB when transmitting under the same bandwidth, and it can further improve performance by nearly 8 dB in MIMO when compared with the ParCast scheme.

A systematic approach to designing statistically powerful heteroscedastic 2 × 2 factorial studies while minimizing financial costs.

PubMed

Jan, Show-Li; Shieh, Gwowen

2016-08-31

The 2 × 2 factorial design is widely used for assessing the existence of interaction and the extent of generalizability of two factors where each factor had only two levels. Accordingly, research problems associated with the main effects and interaction effects can be analyzed with the selected linear contrasts. To correct for the potential heterogeneity of variance structure, the Welch-Satterthwaite test is commonly used as an alternative to the t test for detecting the substantive significance of a linear combination of mean effects. This study concerns the optimal allocation of group sizes for the Welch-Satterthwaite test in order to minimize the total cost while maintaining adequate power. The existing method suggests that the optimal ratio of sample sizes is proportional to the ratio of the population standard deviations divided by the square root of the ratio of the unit sampling costs. Instead, a systematic approach using optimization technique and screening search is presented to find the optimal solution. Numerical assessments revealed that the current allocation scheme generally does not give the optimal solution. Alternatively, the suggested approaches to power and sample size calculations give accurate and superior results under various treatment and cost configurations. The proposed approach improves upon the current method in both its methodological soundness and overall performance. Supplementary algorithms are also developed to aid the usefulness and implementation of the recommended technique in planning 2 × 2 factorial designs.

Dynamic Interaction between Cap & Trade and Electricity Markets

NASA Astrophysics Data System (ADS)

Jeev, Kumar

Greenhouse Gases (GHG), such as Carbon-Dioxide (CO2), which is released in the atmosphere due to anthropogenic activities like power production, are now accepted as the main culprits for global warming. The Regional Greenhouse Gas Initiative (RGGI), an initiative of the North East and Mid-Atlantic States of the United States (US) for limiting the emission of GHG, has developed a regional cap-and-trade program for CO2 emissions for power plants. Existing cap-and-trade programs in US and Europe for Greenhouse Gases have recently been plagued by over-allocation. Carbon prices recently collapsed in all these markets during the global recession. Since then, there have been significant policy changes, which have resulted in the adoption of aggressive emission cap targets by most major carbon emission markets. This is expected to make carbon emissions availability more restrictive, raising the prices of these credits. These emissions markets are expected to have a major impact on the wholesale electricity markets. Two models to study the interaction of these two markets are presented. These models assess the impact of the emissions market on wholesale electricity prices. The first model characterizes the competition between two types of power plants (coal and gas) in both the electricity and emissions markets as a dynamic game using the Cournot approximation. Under this approximation, we find that in the Nash equilibrium the plants increase their permit allocation to high-demand periods and the marginal value of each credit for a plant is identical in all periods under their optimal equilibrium strategy. The second numerical model allows us to explicitly evaluate the closed loop equilibrium of the dynamic interaction of two competitors in these markets. We find that plants often try to corner the market and push prices all the way to the price cap. Power plants derive most of their profits from these extreme price regimes. In the experiments where trading is allowed, plants can collude to keep prices at the price cap. These problems can be averted by careful allocation of credits and strong regulation to deter market manipulation.

Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous Vehicles

DTIC Science & Technology

2007-11-01

Tolerant Overactuated Autonomous Vehicles Casavola, A.; Garone, E. (2007) Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous ...Adaptive Control Allocation for Fault Tolerant Overactuated Autonomous Vehicles 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Tolerant Overactuated Autonomous Vehicles 3.2 - 2 RTO-MP-AVT-145 UNCLASSIFIED/UNLIMITED Control allocation problem (CAP) - Given a virtual input v(t

Reducing power consumption during execution of an application on a plurality of compute nodes

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Peters, Amanda E.; Ratterman, Joseph D.; Smith, Brian E.

2013-09-10

Methods, apparatus, and products are disclosed for reducing power consumption during execution of an application on a plurality of compute nodes that include: powering up, during compute node initialization, only a portion of computer memory of the compute node, including configuring an operating system for the compute node in the powered up portion of computer memory; receiving, by the operating system, an instruction to load an application for execution; allocating, by the operating system, additional portions of computer memory to the application for use during execution; powering up the additional portions of computer memory allocated for use by the application during execution; and loading, by the operating system, the application into the powered up additional portions of computer memory.

Econophysics of a ranked demand and supply resource allocation problem

NASA Astrophysics Data System (ADS)

Priel, Avner; Tamir, Boaz

2018-01-01

We present a two sided resource allocation problem, between demands and supplies, where both parties are ranked. For example, in Big Data problems where a set of different computational tasks is divided between a set of computers each with its own resources, or between employees and employers where both parties are ranked, the employees by their fitness and the employers by their package benefits. The allocation process can be viewed as a repeated game where in each iteration the strategy is decided by a meta-rule, based on the ranks of both parties and the results of the previous games. We show the existence of a phase transition between an absorbing state, where all demands are satisfied, and an active one where part of the demands are always left unsatisfied. The phase transition is governed by the ratio between supplies and demand. In a job allocation problem we find positive correlation between the rank of the workers and the rank of the factories; higher rank workers are usually allocated to higher ranked factories. These all suggest global emergent properties stemming from local variables. To demonstrate the global versus local relations, we introduce a local inertial force that increases the rank of employees in proportion to their persistence time in the same factory. We show that such a local force induces non trivial global effects, mostly to benefit the lower ranked employees.

Toward allocative efficiency in the prescription drug industry.

PubMed

Guell, R C; Fischbaum, M

1995-01-01

Traditionally, monopoly power in the pharmaceutical industry has been measured by profits. An alternative method estimates the deadweight loss of consumer surplus associated with the exercise of monopoly power. Although upper and lower bound estimates for this inefficiency are far apart, they at least suggest a dramatically greater welfare loss than measures of industry profitability would imply. A proposed system would have the U.S. government employing its power of eminent domain to "take" and distribute pharmaceutical patents, providing as "just compensation" the present value of the patent's expected future monopoly profits. Given the allocative inefficiency of raising taxes to pay for the program, the impact of the proposal on allocative efficiency would be at least as good at our lower bound estimate of monopoly costs while substantially improving efficiency at or near our upper bound estimate.

Metro-access integrated network based on optical OFDMA with dynamic sub-carrier allocation and power distribution.

PubMed

Zhang, Chongfu; Zhang, Qiongli; Chen, Chen; Jiang, Ning; Liu, Deming; Qiu, Kun; Liu, Shuang; Wu, Baojian

2013-01-28

We propose and demonstrate a novel optical orthogonal frequency-division multiple access (OFDMA)-based metro-access integrated network with dynamic resource allocation. It consists of a single fiber OFDMA ring and many single fiber OFDMA trees, which transparently integrates metropolitan area networks with optical access networks. The single fiber OFDMA ring connects the core network and the central nodes (CNs), the CNs are on demand reconfigurable and use multiple orthogonal sub-carriers to realize parallel data transmission and dynamic resource allocation, meanwhile, they can also implement flexible power distribution. The remote nodes (RNs) distributed in the user side are connected by the single fiber OFDMA trees with the corresponding CN. The obtained results indicate that our proposed metro-access integrated network is feasible and the power distribution is agile.

Less power or powerless? Egocentric empathy gaps and the irony of having little versus no power in social decision making.

PubMed

Handgraaf, Michel J J; Van Dijk, Eric; Vermunt, Riël C; Wilke, Henk A M; De Dreu, Carsten K W

2008-11-01

The authors investigate the effect of power differences and associated expectations in social decision making. Using a modified ultimatum game, the authors show that allocators lower their offers to recipients when the power difference shifts in favor of the allocator. Remarkably, however, when recipients are completely powerless, offers increase. This effect is mediated by a change in framing of the situation: When the opponent is without power, feelings of social responsibility are evoked. On the recipient side, the authors show that recipients do not anticipate these higher outcomes resulting from powerlessness. They prefer more power over less, expecting higher outcomes when they are more powerful, especially when less power entails powerlessness. Results are discussed in relation to empathy gaps and social responsibility. (c) 2008 APA, all rights reserved.

Flexible operation strategy for environment control system in abnormal supply power condition

NASA Astrophysics Data System (ADS)

Liping, Pang; Guoxiang, Li; Hongquan, Qu; Yufeng, Fang

2017-04-01

This paper establishes an optimization method that can be applied to the flexible operation of the environment control system in an abnormal supply power condition. A proposed conception of lifespan is used to evaluate the depletion time of the non-regenerative substance. The optimization objective function is to maximize the lifespans. The optimization variables are the allocated powers of subsystems. The improved Non-dominated Sorting Genetic Algorithm is adopted to obtain the pareto optimization frontier with the constraints of the cabin environmental parameters and the adjustable operating parameters of the subsystems. Based on the same importance of objective functions, the preferred power allocation of subsystems can be optimized. Then the corresponding running parameters of subsystems can be determined to ensure the maximum lifespans. A long-duration space station with three astronauts is used to show the implementation of the proposed optimization method. Three different CO2 partial pressure levels are taken into consideration in this study. The optimization results show that the proposed optimization method can obtain the preferred power allocation for the subsystems when the supply power is at a less-than-nominal value. The method can be applied to the autonomous control for the emergency response of the environment control system.

Pollution control costs of a transboundary river basin: Empirical tests of the fairness and stability of cost allocation mechanisms using game theory.

PubMed

Shi, Guang-Ming; Wang, Jin-Nan; Zhang, Bing; Zhang, Zhe; Zhang, Yong-Liang

2016-07-15

With rapid economic growth, transboundary river basin pollution in China has become a very serious problem. Based on practical experience in other countries, cooperation among regions is an economic way to control the emission of pollutants. This study develops a game theoretic simulation model to analyze the cost effectiveness of reducing water pollutant emissions in four regions of the Jialu River basin while considering the stability and fairness of four cost allocation schemes. Different schemes (the nucleolus, the weak nucleolus, the Shapley value and the Separable Cost Remaining Benefit (SCRB) principle) are used to allocate regionally agreed-upon water pollutant abatement costs. The main results show that the fully cooperative coalition yielded the highest incremental gain for regions willing to cooperate if each region agreed to negotiate by transferring part of the incremental gain obtained from the cooperation to cover the losses of other regions. In addition, these allocation schemes produce different outcomes in terms of their fairness to the players and in terms of their derived stability, as measured by the Shapley-Shubik Power Index and the Propensity to Disrupt. Although the Shapley value and the SCRB principle exhibit superior fairness and stabilization to the other methods, only the SCRB principle may maintains full cooperation among regions over the long term. The results provide clear empirical evidence that regional gain allocation may affect the sustainability of cooperation. Therefore, it is implied that not only the cost-effectiveness but also the long-term sustainability should be considered while formulating and implementing environmental policies. Copyright © 2016 Elsevier Ltd. All rights reserved.

A woman's place: household labour allocation in rural Kenya.

PubMed

Neitzert, M

1994-01-01

This article synthesizes the literature on household labor allocation. The review reveals that development policies impacting on the labor market favor men over women. Male favoritism also occurs in household decision-making. Data from the 1988 Rural Labor Force Survey were used to examine rural household labor allocation in 1988 and the extent of female and male participation in home and market production and the degree of labor market discrimination against women. It is argued that the standard neoclassical model of economics does not recognize the unequal bargaining power of each member of the household in arriving at a solution to the joint welfare maximization problem. Women's position is expected to worsen during economic development. Women will have less than full participation in the labor market. Women's distinct role in household welfare provision is often disregarded. Development policy mainly focuses on market activities where women hold few positions. Labor allocation in the empirical analysis pertains to the mean hours per week in farm activities, household activities, schooling, and paid or unpaid non-farm work. Findings indicate that average earnings were lower for females than males and that returns to education and training were higher for males than females. Wage discrimination accounted for 30-66% of the earnings gap between rural men and women. Women faced discrimination on their returns to human capital and occupational choices. The concentration of women in low-paying jobs accounted for 21% of the wage gap. Women's lower education accounted for over 10%. Findings suggest that Kenyan households respond to market incentives. Women worked longer hours than men and contributed more to household welfare. Policy should focus on models of household provisioning and not on a joint utility function. Policy should encourage households to revise labor allocation strategies.

Analysis and Research on the Optimal Allocation of Regional Water Resources

NASA Astrophysics Data System (ADS)

rui-chao, Xi; yu-jie, Gu

2018-06-01

Starting from the basic concept of optimal allocation of water resources, taking the allocation of water resources in Tianjin as an example, the present situation of water resources in Tianjin is analyzed, and the multi-objective optimal allocation model of water resources is used to optimize the allocation of water resources. We use LINGO to solve the model, get the optimal allocation plan that meets the economic and social benefits, and put forward relevant policies and regulations, so as to provide theoretical which is basis for alleviating and solving the problem of water shortage.

Two essays on efficiency in the electric power industry: Measurement of technical and allocative efficiency

NASA Astrophysics Data System (ADS)

Gardiner, John Corby

The electric power industry market structure has changed over the last twenty years since the passage of the Public Utility Regulatory Policies Act (PURPA). These changes include the entry by unregulated generator plants and, more recently, the deregulation of entry and price in the retail generation market. Such changes have introduced and expanded competitive forces on the incumbent electric power plants. Proponents of this deregulation argued that the enhanced competition would lead to a more efficient allocation of resources. Previous studies of power plant technical and allocative efficiency have failed to measure technical and allocative efficiency at the plant level. In contrast, this study uses panel data on 35 power plants over 59 years to estimate technical and allocative efficiency of each plant. By using a flexible functional form, which is not constrained by the assumption that regulation is constant over the 59 years sampled, the estimation procedure accounts for changes in both state and national regulatory/energy policies that may have occurred over the sample period. The empirical evidence presented shows that most of the power plants examined have operated more efficiently since the passage of PURPA and the resultant increase of competitive forces. Chapter 2 extends the model used in Chapter 1 and clarifies some issues in the efficiency literature by addressing the case where homogeneity does not hold. A more general model is developed for estimating both input and output inefficiency simultaneously. This approach reveals more information about firm inefficiency than the single estimation approach that has previously been used in the literature. Using the more general model, estimates are provided on the type of inefficiency that occurs as well as the cost of inefficiency by type of inefficiency. In previous studies, the ranking of firms by inefficiency has been difficult because of the cardinal and ordinal differences between different types of inefficiency estimates. However, using the general approach, this study illustrates that plants can be ranked by overall efficiency.

Nash Social Welfare in Multiagent Resource Allocation

NASA Astrophysics Data System (ADS)

Ramezani, Sara; Endriss, Ulle

We study different aspects of the multiagent resource allocation problem when the objective is to find an allocation that maximizes Nash social welfare, the product of the utilities of the individual agents. The Nash solution is an important welfare criterion that combines efficiency and fairness considerations. We show that the problem of finding an optimal outcome is NP-hard for a number of different languages for representing agent preferences; we establish new results regarding convergence to Nash-optimal outcomes in a distributed negotiation framework; and we design and test algorithms similar to those applied in combinatorial auctions for computing such an outcome directly.

A review of distributed parameter groundwater management modeling methods

USGS Publications Warehouse

Gorelick, Steven M.

1983-01-01

Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

Bayesian adaptive phase II screening design for combination trials

PubMed Central

Cai, Chunyan; Yuan, Ying; Johnson, Valen E

2013-01-01

Background Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Methods Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Results Simulation studies show that the proposed design substantially outperforms the conventional multiarm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while allocating substantially more patients to efficacious treatments. Limitations The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. Conclusions The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while providing higher power to identify the best treatment at the end of the trial. PMID:23359875

A Review of Distributed Parameter Groundwater Management Modeling Methods

NASA Astrophysics Data System (ADS)

Gorelick, Steven M.

1983-04-01

Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

NASA Astrophysics Data System (ADS)

Prada, Jose Fernando

Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm posted prices. It is price-based but does not rely on multiple iterations, minimizes information exchange and simplifies the market clearing process. Simulations of the distributed method performed on a six-bus test system showed that, using an appropriate set of prices, it is possible to emulate the results of a conventional centralized solution, without need of providing make-whole payments to generators. Likewise, they showed that the distributed method can accommodate transactions with different products and complex security constraints.

Ant Colony Optimization Algorithm for Centralized Dynamic Channel Allocation in Multi-Cell OFDMA Systems

NASA Astrophysics Data System (ADS)

Kim, Hyo-Su; Kim, Dong-Hoi

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

Steps Toward Optimal Competitive Scheduling

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Crawford, James; Khatib, Lina; Brafman, Ronen

2006-01-01

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum of users preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum ofsers preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.

Multi-objective evolutionary optimization for the joint operation of reservoirs of water supply under water-food-energy nexus management

NASA Astrophysics Data System (ADS)

Uen, T. S.; Tsai, W. P.; Chang, F. J.; Huang, A.

2016-12-01

In recent years, urbanization had a great effect on the growth of population and the resource management scheme of water, food and energy nexus (WFE nexus) in Taiwan. Resource shortages of WFE become a long-term and thorny issue due to the complex interactions of WFE nexus. In consideration of rapid socio-economic development, it is imperative to explore an efficient and practical approach for WFE resources management. This study aims to search the optimal solution to WFE nexus and construct a stable water supply system for multiple stakeholders. The Shimen Reservoir and Feitsui Reservoir in northern Taiwan are chosen to conduct the joint operation of the two reservoirs for water supply. This study intends to achieve water resource allocation from the two reservoirs subject to different operating rules and restrictions of resource allocation. The multi-objectives of the joint operation aim at maximizing hydro-power synergistic gains while minimizing water supply deficiency as well as food shortages. We propose to build a multi-objective evolutionary optimization model for analyzing the hydro-power synergistic gains to suggest the most favorable solutions in terms of tradeoffs between WFE. First, this study collected data from two reservoirs and Taiwan power company. Next, we built a WFE nexus model based on system dynamics. Finally, this study optimized the joint operation of the two reservoirs and calculated the synergy of hydro-power generation. The proposed methodology can tackle the complex joint reservoir operation problems. Results can suggest a reliable policy for joint reservoir operation for creating a green economic city under the lowest risks of water supply.

W-MAC: A Workload-Aware MAC Protocol for Heterogeneous Convergecast in Wireless Sensor Networks

PubMed Central

Xia, Ming; Dong, Yabo; Lu, Dongming

2011-01-01

The power consumption and latency of existing MAC protocols for wireless sensor networks (WSNs) are high in heterogeneous convergecast, where each sensor node generates different amounts of data in one convergecast operation. To solve this problem, we present W-MAC, a workload-aware MAC protocol for heterogeneous convergecast in WSNs. A subtree-based iterative cascading scheduling mechanism and a workload-aware time slice allocation mechanism are proposed to minimize the power consumption of nodes, while offering a low data latency. In addition, an efficient schedule adjustment mechanism is provided for adapting to data traffic variation and network topology change. Analytical and simulation results show that the proposed protocol provides a significant energy saving and latency reduction in heterogeneous convergecast, and can effectively support data aggregation to further improve the performance. PMID:22163753

MIMO radar waveform design with peak and sum power constraints

NASA Astrophysics Data System (ADS)

Arulraj, Merline; Jeyaraman, Thiruvengadam S.

2013-12-01

Optimal power allocation for multiple-input multiple-output radar waveform design subject to combined peak and sum power constraints using two different criteria is addressed in this paper. The first one is by maximizing the mutual information between the random target impulse response and the reflected waveforms, and the second one is by minimizing the mean square error in estimating the target impulse response. It is assumed that the radar transmitter has knowledge of the target's second-order statistics. Conventionally, the power is allocated to transmit antennas based on the sum power constraint at the transmitter. However, the wide power variations across the transmit antenna pose a severe constraint on the dynamic range and peak power of the power amplifier at each antenna. In practice, each antenna has the same absolute peak power limitation. So it is desirable to consider the peak power constraint on the transmit antennas. A generalized constraint that jointly meets both the peak power constraint and the average sum power constraint to bound the dynamic range of the power amplifier at each transmit antenna is proposed recently. The optimal power allocation using the concept of waterfilling, based on the sum power constraint, is the special case of p = 1. The optimal solution for maximizing the mutual information and minimizing the mean square error is obtained through the Karush-Kuhn-Tucker (KKT) approach, and the numerical solutions are found through a nested Newton-type algorithm. The simulation results show that the detection performance of the system with both sum and peak power constraints gives better detection performance than considering only the sum power constraint at low signal-to-noise ratio.

Spectrum sensing and resource allocation for multicarrier cognitive radio systems under interference and power constraints

NASA Astrophysics Data System (ADS)

Dikmese, Sener; Srinivasan, Sudharsan; Shaat, Musbah; Bader, Faouzi; Renfors, Markku

2014-12-01

Multicarrier waveforms have been commonly recognized as strong candidates for cognitive radio. In this paper, we study the dynamics of spectrum sensing and spectrum allocation functions in cognitive radio context using very practical signal models for the primary users (PUs), including the effects of power amplifier nonlinearities. We start by sensing the spectrum with energy detection-based wideband multichannel spectrum sensing algorithm and continue by investigating optimal resource allocation methods. Along the way, we examine the effects of spectral regrowth due to the inevitable power amplifier nonlinearities of the PU transmitters. The signal model includes frequency selective block-fading channel models for both secondary and primary transmissions. Filter bank-based wideband spectrum sensing techniques are applied for detecting spectral holes and filter bank-based multicarrier (FBMC) modulation is selected for transmission as an alternative multicarrier waveform to avoid the disadvantage of limited spectral containment of orthogonal frequency-division multiplexing (OFDM)-based multicarrier systems. The optimization technique used for the resource allocation approach considered in this study utilizes the information obtained through spectrum sensing and knowledge of spectrum leakage effects of the underlying waveforms, including a practical power amplifier model for the PU transmitter. This study utilizes a computationally efficient algorithm to maximize the SU link capacity with power and interference constraints. It is seen that the SU transmission capacity depends critically on the spectral containment of the PU waveform, and these effects are quantified in a case study using an 802.11-g WLAN scenario.

Two‐phase designs for joint quantitative‐trait‐dependent and genotype‐dependent sampling in post‐GWAS regional sequencing

PubMed Central

Espin‐Garcia, Osvaldo; Craiu, Radu V.

2017-01-01

ABSTRACT We evaluate two‐phase designs to follow‐up findings from genome‐wide association study (GWAS) when the cost of regional sequencing in the entire cohort is prohibitive. We develop novel expectation‐maximization‐based inference under a semiparametric maximum likelihood formulation tailored for post‐GWAS inference. A GWAS‐SNP (where SNP is single nucleotide polymorphism) serves as a surrogate covariate in inferring association between a sequence variant and a normally distributed quantitative trait (QT). We assess test validity and quantify efficiency and power of joint QT‐SNP‐dependent sampling and analysis under alternative sample allocations by simulations. Joint allocation balanced on SNP genotype and extreme‐QT strata yields significant power improvements compared to marginal QT‐ or SNP‐based allocations. We illustrate the proposed method and evaluate the sensitivity of sample allocation to sampling variation using data from a sequencing study of systolic blood pressure. PMID:29239496

77 FR 35671 - Conformed Power Marketing Criteria or Regulations for the Boulder Canyon Project

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-14

... DEPARTMENT OF ENERGY Western Area Power Administration Conformed Power Marketing Criteria or... of power marketing criteria in accordance with the Hoover Power Allocation Act of 2011. SUMMARY: The Western Area Power Administration (Western), a Federal power marketing agency of the Department of Energy...

New Approach to Optimize the Apfs Placement Based on Instantaneous Reactive Power Theory by Genetic Algorithm

NASA Astrophysics Data System (ADS)

Hashemi-Dezaki, Hamed; Mohammadalizadeh-Shabestary, Masoud; Askarian-Abyaneh, Hossein; Rezaei-Jegarluei, Mohammad

2014-01-01

In electrical distribution systems, a great amount of power are wasting across the lines, also nowadays power factors, voltage profiles and total harmonic distortions (THDs) of most loads are not as would be desired. So these important parameters of a system play highly important role in wasting money and energy, and besides both consumers and sources are suffering from a high rate of distortions and even instabilities. Active power filters (APFs) are innovative ideas for solving of this adversity which have recently used instantaneous reactive power theory. In this paper, a novel method is proposed to optimize the allocation of APFs. The introduced method is based on the instantaneous reactive power theory in vectorial representation. By use of this representation, it is possible to asses different compensation strategies. Also, APFs proper placement in the system plays a crucial role in either reducing the losses costs and power quality improvement. To optimize the APFs placement, a new objective function has been defined on the basis of five terms: total losses, power factor, voltage profile, THD and cost. Genetic algorithm has been used to solve the optimization problem. The results of applying this method to a distribution network illustrate the method advantages.

Performance impact of mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems.

PubMed

Liu, Chun; Kroll, Andreas

2016-01-01

Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems.

The solar power satellite - A programme for development aid

NASA Astrophysics Data System (ADS)

Meiner, R. C.

It is pointed out that there are essentially four types of foreign aid. These types include the transfer of knowledge, the transfer of materials, the transfer of funds, and the provision of preferential agreements. A great number of studies have been conducted to assess the pros and cons of a Solar Power Satellite System (SPSS). According to many, the most difficult problems which have to be solved in connection with such a project are related to environmental, societal, political, and institutional aspects. The present investigation is concerned with the initiation of a gradual, phased approach toward a Solar Power Satellite (SPS). Phase I of such an approach would involve the set-up of an organization and the allocation of studies. The building of photovoltaic farms and of an SPS pilot project would occur during the second phase, while development and deployment of a full SPSS would take place during the third phase. The developments are to be financed under foreign aid.

Modeling Power Systems as Complex Adaptive Systems

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

Chassin, David P.; Malard, Joel M.; Posse, Christian

2004-12-30

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We reviewmore » and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.« less

Design and Implementation of USAF Avionics Integration Support Facilities

DTIC Science & Technology

1981-12-01

specification for taking the bbranch Vt -Routing indicator (No activity): Allocate Node: All’ocation of resources: R= Allocation rule. Res Resource type number...problems, and the integration and testing of the ECS. The purpose of this investigation is to establish a standard software development system...Corrections to equipment problems. -Compensation for equipment degradation. -New Developments . This approach is intended to centralize essential

Multi-Objective Optimization for Trustworthy Tactical Networks: A Survey and Insights

DTIC Science & Technology

2013-06-01

existing data sources, gathering and maintaining the data needed , and completing and reviewing the collection of information. Send comments regarding...problems: using repeated cooperative games [12], hedonic games [25], and nontransferable utility cooperative games [27]. It should be noted that trust...examined an optimal task allocation problem in a distributed computing system where program modules need to be allocated to different processors to

A Battery-Aware Algorithm for Supporting Collaborative Applications

NASA Astrophysics Data System (ADS)

Rollins, Sami; Chang-Yit, Cheryl

Battery-powered devices such as laptops, cell phones, and MP3 players are becoming ubiquitous. There are several significant ways in which the ubiquity of battery-powered technology impacts the field of collaborative computing. First, applications such as collaborative data gathering, become possible. Also, existing applications that depend on collaborating devices to maintain the system infrastructure must be reconsidered. Fundamentally, the problem lies in the fact that collaborative applications often require end-user computing devices to perform tasks that happen in the background and are not directly advantageous to the user. In this work, we seek to better understand how laptop users use the batteries attached to their devices and analyze a battery-aware alternative to Gnutella’s ultrapeer selection algorithm. Our algorithm provides insight into how system maintenance tasks can be allocated to battery-powered nodes. The most significant result of our study indicates that a large portion of laptop users can participate in system maintenance without sacrificing any of their battery. These results show great promise for existing collaborative applications as well as new applications, such as collaborative data gathering, that rely upon battery-powered devices.

Integration and Task Allocation: Evidence from Patient Care*

PubMed Central

David, Guy; Rawley, Evan; Polsky, Daniel

2013-01-01

Using the universe of patient transitions from inpatient hospital care to skilled nursing facilities and home health care in 2005, we show how integration eliminates task misallocation problems between organizations. We find that vertical integration allows hospitals to shift patient recovery tasks downstream to lower-cost organizations by discharging patients earlier (and in poorer health) and increasing post-hospitalization service intensity. While integration facilitates a shift in the allocation of tasks and resources, health outcomes either improved or were unaffected by integration on average. The evidence suggests that integration solves coordination problems that arise in market exchange through improvements in the allocation of tasks across care settings. PMID:24415893

Resource allocation for multichannel broadcasting visible light communication

NASA Astrophysics Data System (ADS)

Le, Nam-Tuan; Jang, Yeong Min

2015-11-01

Visible light communication (VLC), which offers the possibility of using light sources for both illumination and data communications simultaneously, will be a promising incorporation technique with lighting applications. However, it still remains some challenges especially coverage because of field-of-view limitation. In this paper, we focus on this issue by suggesting a resource allocation scheme for VLC broadcasting system. By using frame synchronization and a network calculus QoS approximation, as well as diversity technology, the proposed VLC architecture and QoS resource allocation for the multichannel-broadcasting MAC (medium access control) protocol can solve the coverage limitation problem and the link switching problem of exhibition service.

Does hospital at home for palliative care facilitate death at home? Randomised controlled trial

PubMed Central

Grande, Gunn E; Todd, Chris J; Barclay, Stephen I G; Farquhar, Morag C

1999-01-01

Objective To evaluate the impact on place of death of a hospital at home service for palliative care. Design Pragmatic randomised controlled trial. Setting Former Cambridge health district. Participants 229 patients referred to the hospital at home service; 43 randomised to control group (standard care), 186 randomised to hospital at home. Intervention Hospital at home versus standard care. Main outcome measures Place of death. Results Twenty five (58%) control patients died at home compared with 124 (67%) patients allocated to hospital at home. This difference was not significant; intention to treat analysis did not show that hospital at home increased the number of deaths at home. Seventy three patients randomised to hospital at home were not admitted to the service. Patients admitted to hospital at home were significantly more likely to die at home (88/113; 78%) than control patients. It is not possible to determine whether this was due to hospital at home itself or other characteristics of the patients admitted to the service. The study attained less statistical power than initially planned. Conclusion In a locality with good provision of standard community care we could not show that hospital at home allowed more patients to die at home, although neither does the study refute this. Problems relating to recruitment, attrition, and the vulnerability of the patient group make randomised controlled trials in palliative care difficult. While these difficulties have to be recognised they are not insurmountable with the appropriate resourcing and setting. Key messagesTerminally ill patients allocated to hospital at home were no more likely to die at home than patients receiving standard careAlthough the subsample of patients actually admitted to hospital at home did show a significant increase in likelihood of dying at home, whether this was due to the service itself or the characteristics of patients admitted to hospital at home could not be determinedThe need to balance ideal research design against the realities of evaluation of palliative care had the effect that the trial achieved less statistical power than originally plannedParticular problems were that many patients failed to receive the allocated intervention because of the unpredictable nature of terminal illness, inclusion of other service input alongside hospital at home, and the wide range of standard care availableThe trial illustrated problems associated with randomised controlled trials in palliative care, none of which are insurmountable but which require careful consideration and resourcing before future trials are planned PMID:10582932

Mathematical analysis and coordinated current allocation control in battery power module systems

NASA Astrophysics Data System (ADS)

Han, Weiji; Zhang, Liang

2017-12-01

As the major energy storage device and power supply source in numerous energy applications, such as solar panels, wind plants, and electric vehicles, battery systems often face the issue of charge imbalance among battery cells/modules, which can accelerate battery degradation, cause more energy loss, and even incur fire hazard. To tackle this issue, various circuit designs have been developed to enable charge equalization among battery cells/modules. Recently, the battery power module (BPM) design has emerged to be one of the promising solutions for its capability of independent control of individual battery cells/modules. In this paper, we propose a new current allocation method based on charging/discharging space (CDS) for performance control in BPM systems. Based on the proposed method, the properties of CDS-based current allocation with constant parameters are analyzed. Then, real-time external total power requirement is taken into account and an algorithm is developed for coordinated system performance control. By choosing appropriate control parameters, the desired system performance can be achieved by coordinating the module charge balance and total power efficiency. Besides, the proposed algorithm has complete analytical solutions, and thus is very computationally efficient. Finally, the efficacy of the proposed algorithm is demonstrated using simulations.

Operations Research Applied to Libraries.

ERIC Educational Resources Information Center

Nussbaum, Harvey

This report discusses the seven basic types of problems found in business and industry as they apply to library institutions. These seven basic types are: (1) inventory problems, (2) allocation problems, (3) queueing problems, (4) sequencing problems, (5) routing problems, (6) replacement problems and (7) search problems. (MF)

Distributed Multi-Cell Resource Allocation with Price Based ICI Coordination in Downlink OFDMA Networks

NASA Astrophysics Data System (ADS)

Lv, Gangming; Zhu, Shihua; Hui, Hui

Multi-cell resource allocation under minimum rate request for each user in OFDMA networks is addressed in this paper. Based on Lagrange dual decomposition theory, the joint multi-cell resource allocation problem is decomposed and modeled as a limited-cooperative game, and a distributed multi-cell resource allocation algorithm is thus proposed. Analysis and simulation results show that, compared with non-cooperative iterative water-filling algorithm, the proposed algorithm can remarkably reduce the ICI level and improve overall system performances.

A Study on Cost Allocation in Nuclear Power Coupled with Desalination

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

Lee, ManKi; Kim, SeungSu; Moon, KeeHwan

As for a single-purpose desalination plant, there is no particular difficulty in computing the unit cost of the water, which is obtained by dividing the annual total costs by the output of fresh water. When it comes to a dual-purpose plant, cost allocation is needed between the two products. No cost allocation is needed in some cases where two alternatives producing the same water and electricity output are to be compared. In these cases, the consideration of the total cost is then sufficient. This study assumes MED (Multi-Effect Distillation) technology is adopted when nuclear power is coupled with desalination. Themore » total production cost of the two commodities in dual-purpose plant can easily be obtained by using costing methods, if the necessary raw data are available. However, it is not easy to calculate a separate cost for each product, because high-pressure steam plant costs cannot be allocated to one or the other without adopting arbitrary methods. Investigation on power credit method is carried out focusing on the cost allocation of combined benefits due to dual production, electricity and water. The illustrative calculation is taken from Preliminary Economic Feasibility Study of Nuclear Desalination in Madura Island, Indonesia. The study is being performed by BATAN (National Nuclear Energy Agency), KAERI (Korean Atomic Energy Research Institute) and under support of the IAEA (International Atomic Energy Agency) started in the year 2002 in order to perform a preliminary economic feasibility in providing the Madurese with sufficient power and potable water for the public and to support industrialization and tourism in Madura Region. The SMART reactor coupled with MED is considered to be an option to produce electricity and potable water. This study indicates that the correct recognition of combined benefits attributable to dual production is important in carrying out economics of desalination coupled with nuclear power. (authors)« less

Summary of Research 1997 Department of Systems Management.

DTIC Science & Technology

1999-01-01

formulation and execution; impacts of budget allocation , reallocation, and reduction; imple- mentation of Defense Resource Management Systems; and the...flexible structure that can be applied to a wide range of resource allocation problems. PUBLICATIONS: Dolk, D., Murphy, M., and Thomas, G...policies, procedures, and rationale in deter- mining recruiting resource allocation decisions. The methodology relies on a review of the literature

Innovative Approach for Developing Spacecraft Interior Acoustic Requirement Allocation

NASA Technical Reports Server (NTRS)

Chu, S. Reynold; Dandaroy, Indranil; Allen, Christopher S.

2016-01-01

The Orion Multi-Purpose Crew Vehicle (MPCV) is an American spacecraft for carrying four astronauts during deep space missions. This paper describes an innovative application of Power Injection Method (PIM) for allocating Orion cabin continuous noise Sound Pressure Level (SPL) limits to the sound power level (PWL) limits of major noise sources in the Environmental Control and Life Support System (ECLSS) during all mission phases. PIM is simulated using both Statistical Energy Analysis (SEA) and Hybrid Statistical Energy Analysis-Finite Element (SEA-FE) models of the Orion MPCV to obtain the transfer matrix from the PWL of the noise sources to the acoustic energies of the receivers, i.e., the cavities associated with the cabin habitable volume. The goal of the allocation strategy is to control the total energy of cabin habitable volume for maintaining the required SPL limits. Simulations are used to demonstrate that applying the allocated PWLs to the noise sources in the models indeed reproduces the SPL limits in the habitable volume. The effects of Noise Control Treatment (NCT) on allocated noise source PWLs are investigated. The measurement of source PWLs of involved fan and pump development units are also discussed as it is related to some case-specific details of the allocation strategy discussed here.

Report on Transmission Cost Allocation for RTOs and Others (Presentation)

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

Coles, L.

2011-06-01

Presented at the MARC 2011 Annual Conference, 6 June 2011, Rapid City, South Dakota. This presentation provides an overview of the latest research findings and policy developments pertaining to cost allocation and new variable generation resources on the power grid.

Optimal sample sizes for the design of reliability studies: power consideration.

PubMed

Shieh, Gwowen

2014-09-01

Intraclass correlation coefficients are used extensively to measure the reliability or degree of resemblance among group members in multilevel research. This study concerns the problem of the necessary sample size to ensure adequate statistical power for hypothesis tests concerning the intraclass correlation coefficient in the one-way random-effects model. In view of the incomplete and problematic numerical results in the literature, the approximate sample size formula constructed from Fisher's transformation is reevaluated and compared with an exact approach across a wide range of model configurations. These comprehensive examinations showed that the Fisher transformation method is appropriate only under limited circumstances, and therefore it is not recommended as a general method in practice. For advance design planning of reliability studies, the exact sample size procedures are fully described and illustrated for various allocation and cost schemes. Corresponding computer programs are also developed to implement the suggested algorithms.

Three essays on pricing and risk management in electricity markets

NASA Astrophysics Data System (ADS)

Kotsan, Serhiy

2005-07-01

A set of three papers forms this dissertation. In the first paper I analyze an electricity market that does not clear. The system operator satisfies fixed demand at a fixed price, and attempts to minimize "cost" as indicated by independent generators' supply bids. No equilibrium exists in this situation, and the operator lacks information sufficient to minimize actual cost. As a remedy, we propose a simple efficient tax mechanism. With the tax, Nash equilibrium bids still diverge from marginal cost but nonetheless provide sufficient information to minimize actual cost, regardless of the tax rate or number of generators. The second paper examines a price mechanism with one price assigned for each level of bundled real and reactive power. Equilibrium allocation under this pricing approach raises system efficiency via better allocation of the reactive power reserves, neglected in the traditional pricing approach. Pricing reactive power should be considered in the bundle with real power since its cost is highly dependent on real power output. The efficiency of pricing approach is shown in the general case, and tested on the 30-bus IEEE network with piecewise linear cost functions of the generators. Finally the third paper addresses the problem of optimal investment in generation based on mean-variance portfolio analysis. It is assumed the investor can freely create a portfolio of shares in generation located on buses of the electrical network. Investors are risk averse, and seek to minimize the variance of the weighted average Locational Marginal Price (LMP) in their portfolio, and to maximize its expected value. I conduct simulations using a standard IEEE 68-bus network that resembles the New York - New England system and calculate LMPs in accordance with the PJM methodology for a fully optimal AC power flow solution. Results indicate that the network topology is a crucial determinant of the investment decision as line congestion makes it difficult to deliver power to certain nodes at system peak load. Determining those nodes is an important task for an investor in generation as well as the transmission system operator.

Methods for Allocating Highway Costs

DOT National Transportation Integrated Search

1981-04-01

Microeconomic theory and other concepts related to pricing are reviewed and applied to the problem of designing highway user charges. In view of the emphasis in the Congressional request for the Highway Cost Allocation Study on setting charges in acc...

Asynchronous Incremental Stochastic Dual Descent Algorithm for Network Resource Allocation

NASA Astrophysics Data System (ADS)

Bedi, Amrit Singh; Rajawat, Ketan

2018-05-01

Stochastic network optimization problems entail finding resource allocation policies that are optimum on an average but must be designed in an online fashion. Such problems are ubiquitous in communication networks, where resources such as energy and bandwidth are divided among nodes to satisfy certain long-term objectives. This paper proposes an asynchronous incremental dual decent resource allocation algorithm that utilizes delayed stochastic {gradients} for carrying out its updates. The proposed algorithm is well-suited to heterogeneous networks as it allows the computationally-challenged or energy-starved nodes to, at times, postpone the updates. The asymptotic analysis of the proposed algorithm is carried out, establishing dual convergence under both, constant and diminishing step sizes. It is also shown that with constant step size, the proposed resource allocation policy is asymptotically near-optimal. An application involving multi-cell coordinated beamforming is detailed, demonstrating the usefulness of the proposed algorithm.

Arithmetic and algebraic problem solving and resource allocation: the distinct impact of fluid and numerical intelligence.

PubMed

Dix, Annika; van der Meer, Elke

2015-04-01

This study investigates cognitive resource allocation dependent on fluid and numerical intelligence in arithmetic/algebraic tasks varying in difficulty. Sixty-six 11th grade students participated in a mathematical verification paradigm, while pupil dilation as a measure of resource allocation was collected. Students with high fluid intelligence solved the tasks faster and more accurately than those with average fluid intelligence, as did students with high compared to average numerical intelligence. However, fluid intelligence sped up response times only in students with average but not high numerical intelligence. Further, high fluid but not numerical intelligence led to greater task-related pupil dilation. We assume that fluid intelligence serves as a domain-general resource that helps to tackle problems for which domain-specific knowledge (numerical intelligence) is missing. The allocation of this resource can be measured by pupil dilation. Copyright © 2014 Society for Psychophysiological Research.

Communication on SWIPT and EH Using Electromagnetic Behaviour for Power Allocation in Wireless Networks

NASA Astrophysics Data System (ADS)

Khan, Sohel Rana; Ajij, Sayyad

2017-12-01

This review paper focuses on the basic relations between wireless power transfer, wireless information transfer and combined phenomenon of simultaneous wireless information and power transfer. The authors reviewed and discussed electromagnetic fields behaviour (EMB) for enhancing the power allocation strategies (PAS) in energy harvesting (EH) wireless communication systems. Further, this paper presents relations between Friis transmission equation and Maxwell's equations to be used in propagation models for reduction in specific absorption rate (SAR). This paper provides a review of various methods and concepts reported in earlier works. This paper also reviews Poynting vector and power densities along with boundary conditions for antennas and human body. Finally, this paper explores the usage of electromagnetic behaviour for the possible enhancement in power saving methods for electromagnetic behaviour centered-wireless energy harvesting (EMBC-WEH). At the same time, possibilities of PAS for reduction in SAR are discussed.

A Review of Function Allocation and En Route Separation Assurance

NASA Technical Reports Server (NTRS)

Lewis, Timothy A.; Aweiss, Arwa S.; Guerreiro, Nelson M.; Daiker, Ronald J.

2016-01-01

Today's air traffic control system has reached a limit to the number of aircraft that can be safely managed at the same time. This air traffic capacity bottleneck is a critical problem along the path to modernization for air transportation. The design of the next separation assurance system to address this problem is a cornerstone of air traffic management research today. This report reviews recent work by NASA and others in the areas of function allocation and en route separation assurance. This includes: separation assurance algorithms and technology prototypes; concepts of operations and designs for advanced separation assurance systems; and specific investigations into air-ground and human-automation function allocation.

A note on resource allocation scheduling with group technology and learning effects on a single machine

NASA Astrophysics Data System (ADS)

Lu, Yuan-Yuan; Wang, Ji-Bo; Ji, Ping; He, Hongyu

2017-09-01

In this article, single-machine group scheduling with learning effects and convex resource allocation is studied. The goal is to find the optimal job schedule, the optimal group schedule, and resource allocations of jobs and groups. For the problem of minimizing the makespan subject to limited resource availability, it is proved that the problem can be solved in polynomial time under the condition that the setup times of groups are independent. For the general setup times of groups, a heuristic algorithm and a branch-and-bound algorithm are proposed, respectively. Computational experiments show that the performance of the heuristic algorithm is fairly accurate in obtaining near-optimal solutions.

Divergence in plant and microbial allocation strategies explains continental patterns in microbial allocation and biogeochemical fluxes.

PubMed

Averill, Colin

2014-10-01

Allocation trade-offs shape ecological and biogeochemical phenomena at local to global scale. Plant allocation strategies drive major changes in ecosystem carbon cycling. Microbial allocation to enzymes that decompose carbon vs. organic nutrients may similarly affect ecosystem carbon cycling. Current solutions to this allocation problem prioritise stoichiometric tradeoffs implemented in plant ecology. These solutions may not maximise microbial growth and fitness under all conditions, because organic nutrients are also a significant carbon resource for microbes. I created multiple allocation frameworks and simulated microbial growth using a microbial explicit biogeochemical model. I demonstrate that prioritising stoichiometric trade-offs does not optimise microbial allocation, while exploiting organic nutrients as carbon resources does. Analysis of continental-scale enzyme data supports the allocation patterns predicted by this framework, and modelling suggests large deviations in soil C loss based on which strategy is implemented. Therefore, understanding microbial allocation strategies will likely improve our understanding of carbon cycling and climate. © 2014 John Wiley & Sons Ltd/CNRS.

The discourses of incidents: Cougars on Mt. Elden and in Sabino Canyon, Arizona

USGS Publications Warehouse

Mattson, David J.; Clark, Susan G.

2012-01-01

Incidents are relatively short periods of intensified discourse that arise from public responses to symbolically important actions by public officials, and an important part of the conflict that increasingly surrounds state wildlife management in the West. In an effort to better understand incidents as a facet of this conflict, we analyzed the discourses of two incidents in Arizona that were precipitated by the intended removal of cougars by managers in response to public safety concerns. We used newspaper content, 1999–2007, to elucidate seminal patterns of public discourses and discourse coalitions as well as differences in discursive focus between incident periods and background periods. Cougars were mentioned in newspaper articles 13–33 times more often during incidents compared with background periods. State wildlife agency commissioners and hunters were part of a discourse coalition that advocated killing cougars to solve problems, blamed cougars and those who promoted the animals’ intrinsic value and sought to retain power to define and solve cougar-related problems. Personnel from affected state and federal agencies expressed a similar discourse. Environmentalists, animal protection activists, and some elected officials were of a coalition that defined “the problem” primarily in terms of people’s behaviors, including behaviors associated with current institutional arrangements. This discourse advocated decentralizing power over cougar management. The discourses reflected different preferences for the allocations of power and use of lethal versus non-lethal methods, which aligned with apparent core beliefs and participants’ enfranchisement or disenfranchisement by current state-level management power arrangements.

Decision rules for allocation of finances to health systems strengthening

PubMed Central

Morton, Alec; Thomas, Ranjeeta; Smith, Peter C.

2017-01-01

A key dilemma in global health is how to allocate funds between disease-specific “vertical projects” on the one hand and “horizontal programmes” which aim to strengthen the entire health system on the other. While economic evaluation provides a way of approaching the prioritisation of vertical projects, it provides less guidance on how to prioritise between horizontal and vertical spending. We approach this problem by formulating a mathematical program which captures the complementary benefits of funding both vertical projects and horizontal programmes. We show that our solution to this math program has an appealing intuitive structure. We illustrate our model by computationally solving two specialised versions of this problem, with illustrations based on the problem of allocating funding for infectious diseases in sub-Saharan Africa. We conclude by reflecting on how such a model may be developed in the future and used to guide empirical data collection and theory development. PMID:27394006

Efficient Simulation Budget Allocation for Selecting an Optimal Subset

NASA Technical Reports Server (NTRS)

Chen, Chun-Hung; He, Donghai; Fu, Michael; Lee, Loo Hay

2008-01-01

We consider a class of the subset selection problem in ranking and selection. The objective is to identify the top m out of k designs based on simulated output. Traditional procedures are conservative and inefficient. Using the optimal computing budget allocation framework, we formulate the problem as that of maximizing the probability of correc tly selecting all of the top-m designs subject to a constraint on the total number of samples available. For an approximation of this corre ct selection probability, we derive an asymptotically optimal allocat ion and propose an easy-to-implement heuristic sequential allocation procedure. Numerical experiments indicate that the resulting allocatio ns are superior to other methods in the literature that we tested, and the relative efficiency increases for larger problems. In addition, preliminary numerical results indicate that the proposed new procedur e has the potential to enhance computational efficiency for simulation optimization.

Distributed Optimal Consensus Over Resource Allocation Network and Its Application to Dynamical Economic Dispatch.

PubMed

Li, Chaojie; Yu, Xinghuo; Huang, Tingwen; He, Xing; Chaojie Li; Xinghuo Yu; Tingwen Huang; Xing He; Li, Chaojie; Huang, Tingwen; He, Xing; Yu, Xinghuo

2018-06-01

The resource allocation problem is studied and reformulated by a distributed interior point method via a -logarithmic barrier. By the facilitation of the graph Laplacian, a fully distributed continuous-time multiagent system is developed for solving the problem. Specifically, to avoid high singularity of the -logarithmic barrier at boundary, an adaptive parameter switching strategy is introduced into this dynamical multiagent system. The convergence rate of the distributed algorithm is obtained. Moreover, a novel distributed primal-dual dynamical multiagent system is designed in a smart grid scenario to seek the saddle point of dynamical economic dispatch, which coincides with the optimal solution. The dual decomposition technique is applied to transform the optimization problem into easily solvable resource allocation subproblems with local inequality constraints. The good performance of the new dynamical systems is, respectively, verified by a numerical example and the IEEE six-bus test system-based simulations.

Control Law-Control Allocation Interaction: F/A-18 PA Simulation Test - Bed

NASA Technical Reports Server (NTRS)

Durham, Wayne; Nelson, Mark

2001-01-01

This report documents the first stage of research into Control Law - Control Allocation Interactions. A three-year research effort was originally proposed: 1. Create a desktop flight simulation environment under which experiments related to the open questions may be conducted. 2. Conduct research to determine which aspects of control allocation have impact upon control law design that merits further research. 3. Conduct research into those aspects of control allocation identified above, and their impacts upon control law design. Simulation code was written utilizing the F/A-18 airframe in the power approach (PA) configuration. A dynamic inversion control law was implemented and used to drive a state-of-the-art control allocation subroutine.

Two-phase designs for joint quantitative-trait-dependent and genotype-dependent sampling in post-GWAS regional sequencing.

PubMed

Espin-Garcia, Osvaldo; Craiu, Radu V; Bull, Shelley B

2018-02-01

We evaluate two-phase designs to follow-up findings from genome-wide association study (GWAS) when the cost of regional sequencing in the entire cohort is prohibitive. We develop novel expectation-maximization-based inference under a semiparametric maximum likelihood formulation tailored for post-GWAS inference. A GWAS-SNP (where SNP is single nucleotide polymorphism) serves as a surrogate covariate in inferring association between a sequence variant and a normally distributed quantitative trait (QT). We assess test validity and quantify efficiency and power of joint QT-SNP-dependent sampling and analysis under alternative sample allocations by simulations. Joint allocation balanced on SNP genotype and extreme-QT strata yields significant power improvements compared to marginal QT- or SNP-based allocations. We illustrate the proposed method and evaluate the sensitivity of sample allocation to sampling variation using data from a sequencing study of systolic blood pressure. © 2017 The Authors. Genetic Epidemiology Published by Wiley Periodicals, Inc.

Market-Based Coordination of Thermostatically Controlled Loads—Part I: A Mechanism Design Formulation

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

Li, Sen; Zhang, Wei; Lian, Jianming

This paper focuses on the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. Using the mechanism design approach, we propose a market-based coordination framework, which can effectively incorporate heterogeneous load dynamics, systematically deal with user preferences, account for the unknown load model parameters, and enable the real-world implementation with limited communication resources. This paper is divided into two parts. Part I presents a mathematical formulation of themore » problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations.« less

Torque blending and wheel slip control in EVs with in-wheel motors

NASA Astrophysics Data System (ADS)

de Castro, Ricardo; Araújo, Rui E.; Tanelli, Mara; Savaresi, Sergio M.; Freitas, Diamantino

2012-01-01

Among the many opportunities offered by electric vehicles (EVs), the design of power trains based on in-wheel electric motors represents, from the vehicle dynamics point of view, a very attractive prospect, mainly due to the torque-vectoring capabilities. However, this distributed propulsion also poses some practical challenges, owing to the constraints arising from motor installation in a confined space, to the increased unsprung mass weight and to the integration of the electric motor with the friction brakes. This last issue is the main theme of this work, which, in particular, focuses on the design of the anti-lock braking system (ABS). The proposed structure for the ABS is composed of a tyre slip controller, a wheel torque allocator and a braking supervisor. To address the slip regulation problem, an adaptive controller is devised, offering robustness to uncertainties in the tyre-road friction and featuring a gain-scheduling mechanism based on the vehicle velocity. Further, an optimisation framework is employed in the torque allocator to determine the optimal split between electric and friction brake torque based on energy performance metrics, actuator constraints and different actuators bandwidth. Finally, based on the EV working condition, the priorities of this allocation scheme are adapted by the braking supervisor unit. Simulation results obtained with the CarSim vehicle model, demonstrate the effectiveness of the overall approach.

Robust Rate Maximization for Heterogeneous Wireless Networks under Channel Uncertainties

PubMed Central

Xu, Yongjun; Hu, Yuan; Li, Guoquan

2018-01-01

Heterogeneous wireless networks are a promising technology in next generation wireless communication networks, which has been shown to efficiently reduce the blind area of mobile communication and improve network coverage compared with the traditional wireless communication networks. In this paper, a robust power allocation problem for a two-tier heterogeneous wireless networks is formulated based on orthogonal frequency-division multiplexing technology. Under the consideration of imperfect channel state information (CSI), the robust sum-rate maximization problem is built while avoiding sever cross-tier interference to macrocell user and maintaining the minimum rate requirement of each femtocell user. To be practical, both of channel estimation errors from the femtocells to the macrocell and link uncertainties of each femtocell user are simultaneously considered in terms of outage probabilities of users. The optimization problem is analyzed under no CSI feedback with some cumulative distribution function and partial CSI with Gaussian distribution of channel estimation error. The robust optimization problem is converted into the convex optimization problem which is solved by using Lagrange dual theory and subgradient algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm by the impact of channel uncertainties on the system performance. PMID:29466315

Concurrent airline fleet allocation and aircraft design with profit modeling for multiple airlines

NASA Astrophysics Data System (ADS)

Govindaraju, Parithi

A "System of Systems" (SoS) approach is particularly beneficial in analyzing complex large scale systems comprised of numerous independent systems -- each capable of independent operations in their own right -- that when brought in conjunction offer capabilities and performance beyond the constituents of the individual systems. The variable resource allocation problem is a type of SoS problem, which includes the allocation of "yet-to-be-designed" systems in addition to existing resources and systems. The methodology presented here expands upon earlier work that demonstrated a decomposition approach that sought to simultaneously design a new aircraft and allocate this new aircraft along with existing aircraft in an effort to meet passenger demand at minimum fleet level operating cost for a single airline. The result of this describes important characteristics of the new aircraft. The ticket price model developed and implemented here enables analysis of the system using profit maximization studies instead of cost minimization. A multiobjective problem formulation has been implemented to determine characteristics of a new aircraft that maximizes the profit of multiple airlines to recognize the fact that aircraft manufacturers sell their aircraft to multiple customers and seldom design aircraft customized to a single airline's operations. The route network characteristics of two simple airlines serve as the example problem for the initial studies. The resulting problem formulation is a mixed-integer nonlinear programming problem, which is typically difficult to solve. A sequential decomposition strategy is applied as a solution methodology by segregating the allocation (integer programming) and aircraft design (non-linear programming) subspaces. After solving a simple problem considering two airlines, the decomposition approach is then applied to two larger airline route networks representing actual airline operations in the year 2005. The decomposition strategy serves as a promising technique for future detailed analyses. Results from the profit maximization studies favor a smaller aircraft in terms of passenger capacity due to its higher yield generation capability on shorter routes while results from the cost minimization studies favor a larger aircraft due to its lower direct operating cost per seat mile.

Decomposition method for zonal resource allocation problems in telecommunication networks

NASA Astrophysics Data System (ADS)

Konnov, I. V.; Kashuba, A. Yu

2016-11-01

We consider problems of optimal resource allocation in telecommunication networks. We first give an optimization formulation for the case where the network manager aims to distribute some homogeneous resource (bandwidth) among users of one region with quadratic charge and fee functions and present simple and efficient solution methods. Next, we consider a more general problem for a provider of a wireless communication network divided into zones (clusters) with common capacity constraints. We obtain a convex quadratic optimization problem involving capacity and balance constraints. By using the dual Lagrangian method with respect to the capacity constraint, we suggest to reduce the initial problem to a single-dimensional optimization problem, but calculation of the cost function value leads to independent solution of zonal problems, which coincide with the above single region problem. Some results of computational experiments confirm the applicability of the new methods.

Joint Interference Alignment and Power Allocation for K-User Multicell MIMO Channel through Staggered Antenna Switching.

PubMed

Selvaprabhu, Poongundran; Chinnadurai, Sunil; Sarker, Md Abdul Latif; Lee, Moon Ho

2018-01-28

In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K -user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the power allocation and feasibility condition for cooperative cell-edge (CE) mobile users (MUs) by assuming that the channel state information is unknown. The new insight behind the transmission strategy of the proposed scheme is premeditated (randomly generated transmission strategy) and partial cooperative CE MUs, where the transmitter is equipped with a conventional antenna, the receiver is equipped with a reconfigurable multimode antenna (staggered antenna switching pattern), and the receiver switches between preset T modes. Our proposed scheme assists and aligns the desired signals and interference signals to cancel the common interference signals because the received signal must have a corresponding independent signal subspace. The capacity for a K -user multicell MIMO Gaussian interference channel with reconfigurable multimode antennas is completely characterised. Furthermore, we show that the proposed K -user multicell MIMO scheduling and K -user L -cell CEUs partial cooperation algorithms elaborate the generalisation of K -user IA and power allocation strategies. The numerical results demonstrate that the proposed intercell interference scheme with partial-cooperative CE MUs achieves better capacity and signal-to-interference plus noise ratio (SINR) performance compared to noncooperative CE MUs and without intercell interference schemes.

Joint Interference Alignment and Power Allocation for K-User Multicell MIMO Channel through Staggered Antenna Switching

PubMed Central

2018-01-01

In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K-user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the power allocation and feasibility condition for cooperative cell-edge (CE) mobile users (MUs) by assuming that the channel state information is unknown. The new insight behind the transmission strategy of the proposed scheme is premeditated (randomly generated transmission strategy) and partial cooperative CE MUs, where the transmitter is equipped with a conventional antenna, the receiver is equipped with a reconfigurable multimode antenna (staggered antenna switching pattern), and the receiver switches between preset T modes. Our proposed scheme assists and aligns the desired signals and interference signals to cancel the common interference signals because the received signal must have a corresponding independent signal subspace. The capacity for a K-user multicell MIMO Gaussian interference channel with reconfigurable multimode antennas is completely characterised. Furthermore, we show that the proposed K-user multicell MIMO scheduling and K-user L-cell CEUs partial cooperation algorithms elaborate the generalisation of K-user IA and power allocation strategies. The numerical results demonstrate that the proposed intercell interference scheme with partial-cooperative CE MUs achieves better capacity and signal-to-interference plus noise ratio (SINR) performance compared to noncooperative CE MUs and without intercell interference schemes. PMID:29382100

Non-Orthogonal Random Access in MIMO Cognitive Radio Networks: Beamforming, Power Allocation, and Opportunistic Transmission

PubMed Central

Lin, Huifa; Shin, Won-Yong

2017-01-01

We study secondary random access in multi-input multi-output cognitive radio networks, where a slotted ALOHA-type protocol and successive interference cancellation are used. We first introduce three types of transmit beamforming performed by secondary users, where multiple antennas are used to suppress the interference at the primary base station and/or to increase the received signal power at the secondary base station. Then, we show a simple decentralized power allocation along with the equivalent single-antenna conversion. To exploit the multiuser diversity gain, an opportunistic transmission protocol is proposed, where the secondary users generating less interference are opportunistically selected, resulting in a further reduction of the interference temperature. The proposed methods are validated via computer simulations. Numerical results show that increasing the number of transmit antennas can greatly reduce the interference temperature, while increasing the number of receive antennas leads to a reduction of the total transmit power. Optimal parameter values of the opportunistic transmission protocol are examined according to three types of beamforming and different antenna configurations, in terms of maximizing the cognitive transmission capacity. All the beamforming, decentralized power allocation, and opportunistic transmission protocol are performed by the secondary users in a decentralized manner, thus resulting in an easy implementation in practice. PMID:28076402

Non-Orthogonal Random Access in MIMO Cognitive Radio Networks: Beamforming, Power Allocation, and Opportunistic Transmission.

PubMed

Lin, Huifa; Shin, Won-Yong

2017-01-01

We study secondary random access in multi-input multi-output cognitive radio networks, where a slotted ALOHA-type protocol and successive interference cancellation are used. We first introduce three types of transmit beamforming performed by secondary users, where multiple antennas are used to suppress the interference at the primary base station and/or to increase the received signal power at the secondary base station. Then, we show a simple decentralized power allocation along with the equivalent single-antenna conversion. To exploit the multiuser diversity gain, an opportunistic transmission protocol is proposed, where the secondary users generating less interference are opportunistically selected, resulting in a further reduction of the interference temperature. The proposed methods are validated via computer simulations. Numerical results show that increasing the number of transmit antennas can greatly reduce the interference temperature, while increasing the number of receive antennas leads to a reduction of the total transmit power. Optimal parameter values of the opportunistic transmission protocol are examined according to three types of beamforming and different antenna configurations, in terms of maximizing the cognitive transmission capacity. All the beamforming, decentralized power allocation, and opportunistic transmission protocol are performed by the secondary users in a decentralized manner, thus resulting in an easy implementation in practice.

Multicriterion problem of allocation of resources in the heterogeneous distributed information processing systems

NASA Astrophysics Data System (ADS)

Antamoshkin, O. A.; Kilochitskaya, T. R.; Ontuzheva, G. A.; Stupina, A. A.; Tynchenko, V. S.

2018-05-01

This study reviews the problem of allocation of resources in the heterogeneous distributed information processing systems, which may be formalized in the form of a multicriterion multi-index problem with the linear constraints of the transport type. The algorithms for solution of this problem suggest a search for the entire set of Pareto-optimal solutions. For some classes of hierarchical systems, it is possible to significantly speed up the procedure of verification of a system of linear algebraic inequalities for consistency due to the reducibility of them to the stream models or the application of other solution schemes (for strongly connected structures) that take into account the specifics of the hierarchies under consideration.

A Solution Method of Scheduling Problem with Worker Allocation by a Genetic Algorithm

NASA Astrophysics Data System (ADS)

Osawa, Akira; Ida, Kenichi

In a scheduling problem with worker allocation (SPWA) proposed by Iima et al, the worker's skill level to each machine is all the same. However, each worker has a different skill level for each machine in the real world. For that reason, we propose a new model of SPWA in which a worker has the different skill level to each machine. To solve the problem, we propose a new GA for SPWA consisting of the following new three procedures, shortening of idle time, modifying infeasible solution to feasible solution, and a new selection method for GA. The effectiveness of the proposed algorithm is clarified by numerical experiments using benchmark problems for job-shop scheduling.

Optimal allocation of trend following strategies

NASA Astrophysics Data System (ADS)

Grebenkov, Denis S.; Serror, Jeremy

2015-09-01

We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.

Power corrupts co-operation: cognitive and motivational effects in a double EEG paradigm.

PubMed

Kanso, Riam; Hewstone, Miles; Hawkins, Erin; Waszczuk, Monika; Nobre, Anna Christina

2014-02-01

This study investigated the effect of interpersonal power on co-operative performance. We used a paired electro-encephalogram paradigm: pairs of participants performed an attention task, followed by feedback indicating monetary loss or gain on every trial. Participants were randomly allocated to the power-holder, subordinate or neutral group by creating different levels of control over how a joint monetary reward would be allocated. We found that power was associated with reduced behavioural accuracy. Event-related potential analysis showed that power-holders devoted less motivational resources to their targets than did subordinates or neutrals, but did not differ at the level of early conflict detection. Their feedback potential results showed a greater expectation of rewards but reduced subjective magnitude attributed to losses. Subordinates, on the other hand, were asymmetrically sensitive to power-holders' targets. They expected fewer rewards, but attributed greater significance to losses. Our study shows that power corrupts balanced co-operation with subordinates.

Power corrupts co-operation: cognitive and motivational effects in a double EEG paradigm

PubMed Central

Kanso, Riam; Hewstone, Miles; Hawkins, Erin; Waszczuk, Monika; Nobre, Anna Christina

2014-01-01

This study investigated the effect of interpersonal power on co-operative performance. We used a paired electro-encephalogram paradigm: pairs of participants performed an attention task, followed by feedback indicating monetary loss or gain on every trial. Participants were randomly allocated to the power-holder, subordinate or neutral group by creating different levels of control over how a joint monetary reward would be allocated. We found that power was associated with reduced behavioural accuracy. Event-related potential analysis showed that power-holders devoted less motivational resources to their targets than did subordinates or neutrals, but did not differ at the level of early conflict detection. Their feedback potential results showed a greater expectation of rewards but reduced subjective magnitude attributed to losses. Subordinates, on the other hand, were asymmetrically sensitive to power-holders’ targets. They expected fewer rewards, but attributed greater significance to losses. Our study shows that power corrupts balanced co-operation with subordinates. PMID:23160813

Power plant allocation in East Kalimantan considering total cost and emissions

NASA Astrophysics Data System (ADS)

Muslimin; Utomo, D. S.

2018-04-01

The fulfillment of electricity need in East Kalimantan is the responsibility of State Electricity Company/Perusahaan Listrik Negara (PLN). But PLN faces constraints in the lack of generating capacity it has. So the allocation of power loads in East Kalimantan has its own challenges. Additional power supplies from other parties are required. In this study, there are four scenarios tested to meet the electricity needs in East Kalimantan with the goal of minimizing costs and emissions. The first scenario is only by using PLN power plant. The second scenario is by combining PLN + Independent Power Producer (IPP) power plants. The third scenario is by using PLN + Rented power plants. The fourth scenario is by using PLN + Excess capacity generation. Numerical experiment using nonlinear programming is conducted with the help of the solver. The result shows that in the peak load condition, the best combination is scenario 2 (PLN + IPP). While at the lowest load condition, the cheapest scenario is PLN + IPP while the lowest emission is PLN + Rent.

Profitability primer: a guide to profitability analysis in the electric power industry

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

Woo, C.K.; Lloyd-Zannetti, D.; Martin, J.

1996-06-01

As the electric power industry is opened to forces of competition, increased attention must be focused to develop products and services that deliver good value to customers and to identify customer segments that are profitable to serve. This primer introduces the concept of profitability analysis and its application to the electric power industry. The primer recognizes that some segments of the business will remain monopolistic and subject to regulations, while other segments will become competitive. The primer also recognizes that customer profitability is critically dependent on a host of related issues such as how internal costs are allocated to variousmore » functions and how revenues are collected and allocated.« less

77 FR 65681 - Boulder Canyon Project-Post-2017 Resource Pool

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-30

... marketing criteria must submit written comments to Western's Desert Southwest Customer Service Regional... defined as ``Schedule D'' to be allocated to new allottees. In accordance with the HPAA, Western allocated... allottee may purchase power only upon the execution of an electric service contract and satisfaction of all...

Status Valued Goal Objects and Performance Expectations

ERIC Educational Resources Information Center

Hysom, Stuart J.

2009-01-01

I designed an experiment to test predictions, derived from expectation states theories, that the unequal allocation of social rewards among collective task-focused actors will affect the actors' rates of power and prestige behavior. Past research shows that allocations of exchangeable resources can have these effects. The prediction, however, is…

Graph theoretical stable allocation as a tool for reproduction of control by human operators

NASA Astrophysics Data System (ADS)

van Nooijen, Ronald; Ertsen, Maurits; Kolechkina, Alla

2016-04-01

During the design of central control algorithms for existing water resource systems under manual control it is important to consider the interaction with parts of the system that remain under manual control and to compare the proposed new system with the existing manual methods. In graph theory the "stable allocation" problem has good solution algorithms and allows for formulation of flow distribution problems in terms of priorities. As a test case for the use of this approach we used the algorithm to derive water allocation rules for the Gezira Scheme, an irrigation system located between the Blue and White Niles south of Khartoum. In 1925, Gezira started with 300,000 acres; currently it covers close to two million acres.

Energy-efficient downlink resource management in self-organized OFDMA-based two-tier femtocell networks

NASA Astrophysics Data System (ADS)

Shahid, Adnan; Aslam, Saleem; Kim, Hyung Seok; Lee, Kyung-Geun

2015-12-01

Femtocell is a novel technology that is used for escalating indoor coverage as well as the capacity of traditional cellular networks. However, interference is the limiting factor for performance improvement due to co-channel deployment between macrocells and femtocells. The traditional network planning is not feasible because of the random deployment of femtocells. Therefore, self-organization approaches are the key to having successful deployment of femtocells. This study presents the joint resource block (RB) and power allocation task for the two-tier femtocell network in a self-organizing manner, with the concern to minimizing the impact of interference and maximizing the energy efficiency. In this study, we analyze the performance of the system in terms of the energy efficiency, which is composed of both the transmission and circuit power. Most of the previous studies investigate the performance regarding the throughput requirement of the two-tier femtocell network while the energy efficiency aspect is largely ignored. Here, the joint allocation task is modeled as a non-cooperative game which is demonstrated to exhibit pure and unique Nash equilibrium. In order to reduce the complexity of the proposed non-cooperative game, the joint RB and power allocation task is divided into two subproblems: an RB allocation and a particle swarm optimization-based power allocation. The analysis of the proposed game is carried out in terms of not only energy efficiency but also throughput. With practical 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) parameters, the simulation results illustrate the superior performance of the proposed game as compared to the traditional methods. Also, the comparison is carried out with the joint allocation scheme which only considers the throughput as the objective function. The results illustrate that significant performance improvement is achieved in terms of energy efficiency with slight loss in the throughput. The analysis in regard to energy efficiency and throughput of the two-tier femtocell network is carried out in terms of the performance metrics, which include convergence, impact of varying RBs, impact of femtocell density, and the fairness index.

How Managers' everyday decisions create or destroy your company's strategy.

PubMed

Bower, Joseph L; Gilbert, Clark G

2007-02-01

Senior executives have long been frustrated by the disconnection between the plans and strategies they devise and the actual behavior of the managers throughout the company. This article approaches the problem from the ground up, recognizing that every time a manager allocates resources, that decision moves the company either into or out of alignment with its announced strategy. A well-known story--Intel's exit from the memory business--illustrates this point. When discussing what businesses Intel should be in, Andy Grove asked Gordon Moore what they would do if Intel were a company that they had just acquired. When Moore answered, "Get out of memory," they decided to do just that. It turned out, though, that Intel's revenues from memory were by this time only 4% of total sales. Intel's lower-level managers had already exited the business. What Intel hadn't done was to shut down the flow of research funding into memory (which was still eating up one-third of all research expenditures); nor had the company announced its exit to the outside world. Because divisional and operating managers-as well as customers and capital markets-have such a powerful impact on the realized strategy of the firm, senior management might consider focusing less on the company's formal strategy and more on the processes by which the company allocates resources. Top managers must know the track record of the people who are making resource allocation proposals; recognize the strategic issues at stake; reach down to operational managers to work across division lines; frame resource questions to reflect the corporate perspective, especially when large sums of money are involved and conditions are highly uncertain; and create a new context that allows top executives to circumvent the regular resource allocation process when necessary.

7 CFR 1767.22 - Other income and deductions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Cooperative Capital Credits 424Other Capital Credits and Patronage Capital Allocations 425Miscellaneous... Transmission Cooperative Capital Credits This account shall be credited with the annual capital furnished the power supply cooperative through payment of power bills. The amount of capital furnished the power...

7 CFR 1767.22 - Other income and deductions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Cooperative Capital Credits 424Other Capital Credits and Patronage Capital Allocations 425Miscellaneous... Transmission Cooperative Capital Credits This account shall be credited with the annual capital furnished the power supply cooperative through payment of power bills. The amount of capital furnished the power...

Land use allocation model considering climate change impact

NASA Astrophysics Data System (ADS)

Lee, D. K.; Yoon, E. J.; Song, Y. I.

2017-12-01

In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

Evaluation of power system security and development of transmission pricing method

NASA Astrophysics Data System (ADS)

Kim, Hyungchul

The electric power utility industry is presently undergoing a change towards the deregulated environment. This has resulted in unbundling of generation, transmission and distribution services. The introduction of competition into unbundled electricity services may lead system operation closer to its security boundaries resulting in smaller operating safety margins. The competitive environment is expected to lead to lower price rates for customers and higher efficiency for power suppliers in the long run. Under this deregulated environment, security assessment and pricing of transmission services have become important issues in power systems. This dissertation provides new methods for power system security assessment and transmission pricing. In power system security assessment, the following issues are discussed (1) The description of probabilistic methods for power system security assessment; (2) The computation time of simulation methods; (3) on-line security assessment for operation. A probabilistic method using Monte-Carlo simulation is proposed for power system security assessment. This method takes into account dynamic and static effects corresponding to contingencies. Two different Kohonen networks, Self-Organizing Maps and Learning Vector Quantization, are employed to speed up the probabilistic method. The combination of Kohonen networks and Monte-Carlo simulation can reduce computation time in comparison with straight Monte-Carlo simulation. A technique for security assessment employing Bayes classifier is also proposed. This method can be useful for system operators to make security decisions during on-line power system operation. This dissertation also suggests an approach for allocating transmission transaction costs based on reliability benefits in transmission services. The proposed method shows the transmission transaction cost of reliability benefits when transmission line capacities are considered. The ratio between allocation by transmission line capacity-use and allocation by reliability benefits is computed using the probability of system failure.

The kidney allocation score: methodological problems, moral concerns and unintended consequences.

PubMed

Hippen, B

2009-07-01

The growing disparity between the demand for and supply of kidneys for transplantation has generated interest in alternative systems of allocating kidneys from deceased donors. This personal viewpoint focuses attention on the Kidney Allocation Score (KAS) proposal promulgated by the UNOS/OPTN Kidney Committee. I identify several methodological and moral flaws in the proposed system, concluding that any iteration of the KAS proposal should be met with more skepticism than sanguinity.

Financial Resource Allocation in Higher Education

ERIC Educational Resources Information Center

Ušpuriene, Ana; Sakalauskas, Leonidas; Dumskis, Valerijonas

2017-01-01

The paper considers a problem of financial resource allocation in a higher education institution. The basic financial management instruments and the multi-stage cost minimization model created are described involving financial instruments to constraints. Both societal and institutional factors that determine the costs of educating students are…

Interactive Land-Use Optimization Using Laguerre Voronoi Diagram with Dynamic Generating Point Allocation

NASA Astrophysics Data System (ADS)

Chaidee, S.; Pakawanwong, P.; Suppakitpaisarn, V.; Teerasawat, P.

2017-09-01

In this work, we devise an efficient method for the land-use optimization problem based on Laguerre Voronoi diagram. Previous Voronoi diagram-based methods are more efficient and more suitable for interactive design than discrete optimization-based method, but, in many cases, their outputs do not satisfy area constraints. To cope with the problem, we propose a force-directed graph drawing algorithm, which automatically allocates generating points of Voronoi diagram to appropriate positions. Then, we construct a Laguerre Voronoi diagram based on these generating points, use linear programs to adjust each cell, and reconstruct the diagram based on the adjustment. We adopt the proposed method to the practical case study of Chiang Mai University's allocated land for a mixed-use complex. For this case study, compared to other Voronoi diagram-based method, we decrease the land allocation error by 62.557 %. Although our computation time is larger than the previous Voronoi-diagram-based method, it is still suitable for interactive design.

Strategic planning for disaster recovery with stochastic last mile distribution

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

Bent, Russell Whitford; Van Hentenryck, Pascal; Coffrin, Carleton

2010-01-01

This paper considers the single commodity allocation problem (SCAP) for disaster recovery, a fundamental problem faced by all populated areas. SCAPs are complex stochastic optimization problems that combine resource allocation, warehouse routing, and parallel fleet routing. Moreover, these problems must be solved under tight runtime constraints to be practical in real-world disaster situations. This paper formalizes the specification of SCAPs and introduces a novel multi-stage hybrid-optimization algorithm that utilizes the strengths of mixed integer programming, constraint programming, and large neighborhood search. The algorithm was validated on hurricane disaster scenarios generated by Los Alamos National Laboratory using state-of-the-art disaster simulation toolsmore » and is deployed to aid federal organizations in the US.« less

Networked Rectenna Array for Smart Material Actuators

NASA Technical Reports Server (NTRS)

Choi, Sang H.; Golembiewski, Walter T.; Song, Kyo D.

2000-01-01

The concept of microwave-driven smart material actuators is envisioned as the best option to alleviate the complexity associated with hard-wired control circuitry. Networked rectenna patch array receives and converts microwave power into a DC power for an array of smart actuators. To use microwave power effectively, the concept of a power allocation and distribution (PAD) circuit is adopted for networking a rectenna/actuator patch array. The PAD circuit is imbedded into a single embodiment of rectenna and actuator array. The thin-film microcircuit embodiment of PAD circuit adds insignificant amount of rigidity to membrane flexibility. Preliminary design and fabrication of PAD circuitry that consists of a few nodal elements were made for laboratory testing. The networked actuators were tested to correlate the network coupling effect, power allocation and distribution, and response time. The features of preliminary design are 16-channel computer control of actuators by a PCI board and the compensator for a power failure or leakage of one or more rectennas.

Conserving mangrove ecosystems in the Philippines: transcending disciplinary and institutional borders.

PubMed

Farley, Joshua; Batker, David; de la Torre, Isabel; Hudspeth, Tom

2010-01-01

Humans are rapidly depleting critical ecosystems and the life support functions they provide, increasing the urgency of developing effective conservation tools. Using a case study of the conversion of mangrove ecosystems to shrimp aquaculture, this article describes an effort to develop a transdisciplinary, transinstitutional approach to conservation that simultaneously trains future generations of environmental problem solvers. We worked in close collaboration with academics, non-government organizations, local government and local communities to organize a workshop in Puerto Princesa, Palawan, Philippines. The primary objectives of the workshop were to: (1) train participants in the basic principles of ecological economics and its goals of sustainable scale, just distribution and efficient allocation; (2) learn from local community stakeholders and participating scientists about the problems surrounding conversion of mangrove ecosystems to shrimp aquaculture; (3) draw on the skills and knowledge of all participants to develop potential solutions to the problem; and (4) communicate results to those with the power and authority to act on them. We found that the economic and ecological benefits of intact mangroves outweigh the returns to aquaculture. Perversely, however, private property rights to mangrove ecosystems favor inefficient, unjust and unsustainable allocation of the resource-a tragedy of the non-commons. We presented the workshop results to the press and local government, which shut down the aquaculture ponds to conserve the threatened ecosystem. Effective communication to appropriate audiences was essential for transforming research into action. Our approach is promising and can be readily applied to conservation research and advocacy projects worldwide, but should be improved through adaptive management-practitioners must continually build on those elements that work and discard or improve those that fail.

Conserving Mangrove Ecosystems in the Philippines: Transcending Disciplinary and Institutional Borders

NASA Astrophysics Data System (ADS)

Farley, Joshua; Batker, David; de La Torre, Isabel; Hudspeth, Tom

2010-01-01

Humans are rapidly depleting critical ecosystems and the life support functions they provide, increasing the urgency of developing effective conservation tools. Using a case study of the conversion of mangrove ecosystems to shrimp aquaculture, this article describes an effort to develop a transdisciplinary, transinstitutional approach to conservation that simultaneously trains future generations of environmental problem solvers. We worked in close collaboration with academics, non-government organizations, local government and local communities to organize a workshop in Puerto Princesa, Palawan, Philippines. The primary objectives of the workshop were to: (1) train participants in the basic principles of ecological economics and its goals of sustainable scale, just distribution and efficient allocation; (2) learn from local community stakeholders and participating scientists about the problems surrounding conversion of mangrove ecosystems to shrimp aquaculture; (3) draw on the skills and knowledge of all participants to develop potential solutions to the problem; and (4) communicate results to those with the power and authority to act on them. We found that the economic and ecological benefits of intact mangroves outweigh the returns to aquaculture. Perversely, however, private property rights to mangrove ecosystems favor inefficient, unjust and unsustainable allocation of the resource—a tragedy of the non-commons. We presented the workshop results to the press and local government, which shut down the aquaculture ponds to conserve the threatened ecosystem. Effective communication to appropriate audiences was essential for transforming research into action. Our approach is promising and can be readily applied to conservation research and advocacy projects worldwide, but should be improved through adaptive management—practitioners must continually build on those elements that work and discard or improve those that fail.

Three-level global resource allocation model for hiv control: A hierarchical decision system approach.

PubMed

Kassa, Semu Mitiku

2018-02-01

Funds from various global organizations, such as, The Global Fund, The World Bank, etc. are not directly distributed to the targeted risk groups. Especially in the so-called third-world-countries, the major part of the fund in HIV prevention programs comes from these global funding organizations. The allocations of these funds usually pass through several levels of decision making bodies that have their own specific parameters to control and specific objectives to achieve. However, these decisions are made mostly in a heuristic manner and this may lead to a non-optimal allocation of the scarce resources. In this paper, a hierarchical mathematical optimization model is proposed to solve such a problem. Combining existing epidemiological models with the kind of interventions being on practice, a 3-level hierarchical decision making model in optimally allocating such resources has been developed and analyzed. When the impact of antiretroviral therapy (ART) is included in the model, it has been shown that the objective function of the lower level decision making structure is a non-convex minimization problem in the allocation variables even if all the production functions for the intervention programs are assumed to be linear.

Optimal Time Allocation in Backscatter Assisted Wireless Powered Communication Networks.

PubMed

Lyu, Bin; Yang, Zhen; Gui, Guan; Sari, Hikmet

2017-06-01

This paper proposes a wireless powered communication network (WPCN) assisted by backscatter communication (BackCom). This model consists of a power station, an information receiver and multiple users that can work in either BackCom mode or harvest-then-transmit (HTT) mode. The time block is mainly divided into two parts corresponding to the data backscattering and transmission periods, respectively. The users first backscatter data to the information receiver in time division multiple access (TDMA) during the data backscattering period. When one user works in the BackCom mode, the other users harvest energy from the power station. During the data transmission period, two schemes, i.e., non-orthogonal multiple access (NOMA) and TDMA, are considered. To maximize the system throughput, the optimal time allocation policies are obtained. Simulation results demonstrate the superiority of the proposed model.

Optimal Time Allocation in Backscatter Assisted Wireless Powered Communication Networks

PubMed Central

Lyu, Bin; Yang, Zhen; Gui, Guan; Sari, Hikmet

2017-01-01

This paper proposes a wireless powered communication network (WPCN) assisted by backscatter communication (BackCom). This model consists of a power station, an information receiver and multiple users that can work in either BackCom mode or harvest-then-transmit (HTT) mode. The time block is mainly divided into two parts corresponding to the data backscattering and transmission periods, respectively. The users first backscatter data to the information receiver in time division multiple access (TDMA) during the data backscattering period. When one user works in the BackCom mode, the other users harvest energy from the power station. During the data transmission period, two schemes, i.e., non-orthogonal multiple access (NOMA) and TDMA, are considered. To maximize the system throughput, the optimal time allocation policies are obtained. Simulation results demonstrate the superiority of the proposed model. PMID:28587171

Budget Allocation in a Competitive Communication Spectrum Economy

NASA Astrophysics Data System (ADS)

Lin, Ming-Hua; Tsai, Jung-Fa; Ye, Yinyu

2009-12-01

This study discusses how to adjust "monetary budget" to meet each user's physical power demand, or balance all individual utilities in a competitive "spectrum market" of a communication system. In the market, multiple users share a common frequency or tone band and each of them uses the budget to purchase its own transmit power spectra (taking others as given) in maximizing its Shannon utility or pay-off function that includes the effect of interferences. A market equilibrium is a budget allocation, price spectrum, and tone power distribution that independently and simultaneously maximizes each user's utility. The equilibrium conditions of the market are formulated and analyzed, and the existence of an equilibrium is proved. Computational results and comparisons between the competitive equilibrium and Nash equilibrium solutions are also presented, which show that the competitive market equilibrium solution often provides more efficient power distribution.

Radio Resource Allocation on Complex 4G Wireless Cellular Networks

NASA Astrophysics Data System (ADS)

Psannis, Kostas E.

2015-09-01

In this article we consider the heuristic algorithm which improves step by step wireless data delivery over LTE cellular networks by using the total transmit power with the constraint on users’ data rates, and the total throughput with the constraints on the total transmit power as well as users’ data rates, which are jointly integrated into a hybrid-layer design framework to perform radio resource allocation for multiple users, and to effectively decide the optimal system parameter such as modulation and coding scheme (MCS) in order to adapt to the varying channel quality. We propose new heuristic algorithm which balances the accessible data rate, the initial data rates of each user allocated by LTE scheduler, the priority indicator which signals delay- throughput- packet loss awareness of the user, and the buffer fullness by achieving maximization of radio resource allocation for multiple users. It is noted that the overall performance is improved with the increase in the number of users, due to multiuser diversity. Experimental results illustrate and validate the accuracy of the proposed methodology.

A Novel Joint Problem of Routing, Scheduling, and Variable-Width Channel Allocation in WMNs

PubMed Central

Liu, Wan-Yu; Chou, Chun-Hung

2014-01-01

This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems. PMID:24982990

Fuzzy-logic based Q-Learning interference management algorithms in two-tier networks

NASA Astrophysics Data System (ADS)

Xu, Qiang; Xu, Zezhong; Li, Li; Zheng, Yan

2017-10-01

Unloading from macrocell network and enhancing coverage can be realized by deploying femtocells in the indoor scenario. However, the system performance of the two-tier network could be impaired by the co-tier and cross-tier interference. In this paper, a distributed resource allocation scheme is studied when each femtocell base station is self-governed and the resource cannot be assigned centrally through the gateway. A novel Q-Learning interference management scheme is proposed, that is divided into cooperative and independent part. In the cooperative algorithm, the interference information is exchanged between the cell-edge users which are classified by the fuzzy logic in the same cell. Meanwhile, we allocate the orthogonal subchannels to the high-rate cell-edge users to disperse the interference power when the data rate requirement is satisfied. The resource is assigned directly according to the minimum power principle in the independent algorithm. Simulation results are provided to demonstrate the significant performance improvements in terms of the average data rate, interference power and energy efficiency over the cutting-edge resource allocation algorithms.

Approaches to Resource Allocation

ERIC Educational Resources Information Center

Dressel, Paul; Simon, Lou Anna Kimsey

1976-01-01

Various budgeting patterns and strategies are currently in use, each with its own particular strengths and weaknesses. Neither cost-benefit analysis nor cost-effectiveness analysis offers any better solution to the allocation problem than do the unsupported contentions of departments or the historical unit costs. An operable model that performs…

The misnomer of attention-deficit hyperactivity disorder.

PubMed

Wasserman, Theodore; Wasserman, Lori Drucker

2015-01-01

We propose that attention-deficit disorder represents an inefficiency of an integrated system designed to allocate working memory to designated tasks rather than the absence or dysfunction of a particular form of attention. A significant portion of this inefficiency in the allocation of working memory represents poor engagement of the reward circuit with distinct circuits of learning and performance that control instrumental conditioning (learning). Efficient attention requires the interaction of these circuits. For a significant percentage of individuals who present with attention-deficit disorder, their problems represent the engagement, or lack thereof, of the motivational and reward circuit as opposed to problems, or disorders of attention traditionally defined as problems with orienting, focusing, and sustaining. We demonstrate that there is an integrated system of working-memory allocation that responds by recruiting relevant aspects of both cortex and subcortex to the demands of the task being encountered. In this model, attention is viewed as a gating function determined by novelty, flight-or-fight response, and reward history/valence affecting motivation. We view the traditional models of attention, rather than describe specific types of attention per se, as representing the description of the behavioral output of this integrated orienting and engagement system designed to allocate working memory to task-specific stimuli.

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization.

PubMed

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Wong, Wai Peng; Chen, Chun-Hung

2017-04-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort.

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

NASA Astrophysics Data System (ADS)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization

PubMed Central

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Chen, Chun-Hung

2017-01-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort. PMID:29170617

Dynamic task allocation for a man-machine symbiotic system

NASA Technical Reports Server (NTRS)

Parker, L. E.; Pin, F. G.

1987-01-01

This report presents a methodological approach to the dynamic allocation of tasks in a man-machine symbiotic system in the context of dexterous manipulation and teleoperation. This report addresses a symbiotic system containing two symbiotic partners which work toward controlling a single manipulator arm for the execution of a series of sequential manipulation tasks. It is proposed that an automated task allocator use knowledge about the constraints/criteria of the problem, the available resources, the tasks to be performed, and the environment to dynamically allocate task recommendations for the man and the machine. The presentation of the methodology includes discussions concerning the interaction of the knowledge areas, the flow of control, the necessary communication links, and the replanning of the task allocation. Examples of task allocation are presented to illustrate the results of this methodolgy.

Optimal resource allocation for defense of targets based on differing measures of attractiveness.

PubMed

Bier, Vicki M; Haphuriwat, Naraphorn; Menoyo, Jaime; Zimmerman, Rae; Culpen, Alison M

2008-06-01

This article describes the results of applying a rigorous computational model to the problem of the optimal defensive resource allocation among potential terrorist targets. In particular, our study explores how the optimal budget allocation depends on the cost effectiveness of security investments, the defender's valuations of the various targets, and the extent of the defender's uncertainty about the attacker's target valuations. We use expected property damage, expected fatalities, and two metrics of critical infrastructure (airports and bridges) as our measures of target attractiveness. Our results show that the cost effectiveness of security investment has a large impact on the optimal budget allocation. Also, different measures of target attractiveness yield different optimal budget allocations, emphasizing the importance of developing more realistic terrorist objective functions for use in budget allocation decisions for homeland security.

Optimum Allocation of Water to the Cultivation Farms Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Saeidian, B.; Saadi Mesgari, M.; Ghodousi, M.

2015-12-01

The water scarcity crises in the world and specifically in Iran, requires the proper management of this valuable resource. According to the official reports, around 90 percent of the water in Iran is used for agriculture. Therefore, the adequate management and usage of water in this section can help significantly to overcome the above crises. The most important aspect of agricultural water management is related to the irrigation planning, which is basically an allocation problem. The proper allocation of water to the farms is not a simple and trivial problem, because of the limited amount of available water, the effect of different parameters, nonlinear characteristics of the objective function, and the wideness of the solution space. Usually To solve such complex problems, a meta-heuristic method such as genetic algorithm could be a good candidate. In this paper, Genetic Algorithm (GA) is used for the allocation of different amount of water to a number of farms. In this model, the amount of water transferable using canals of level one, in one period of irrigation is specified. In addition, the amount of water required by each farm is calculated using crop type, stage of crop development, and other parameters. Using these, the water production function of each farm is determined. Then, using the water production function, farm areas, and the revenue and cost of each crop type, the objective function is calculated. This objective function is used by GA for the allocation of water to the farms. The objective function is defined such that the economical profit extracted from all farms is maximized. Moreover, the limitation related to the amount of available water is considered as a constraint. In general, the total amount of allocated water should be less than the finally available water (the water transferred trough the level one canals). Because of the intensive scarcity of water, the deficit irrigation method are considered. In this method, the planning is on the basis of the optimum and limited allocation of water, and not on the basis of the each crop water requirement. According to the available literature, in the condition of water scarcity, the implementation of deficit irrigation strategy results in higher economical income. The main difference of this research with others is the allocation of water to the farms. Whilst, most of similar researches concentrate on the allocation of water to different water consumption sections (such as agriculture, industry etc.), networks and crops. Using the GA for the optimization of the water allocation, proper solutions were generated that maximize the total economical income in the entire study area. In addition, although the search space was considerably wide, the results of the implementation showed an adequate convergence speed. The repeatability test of the algorithm also proved that the algorithm is reasonably stable. In general the usage of GA algorithm can be considered as an efficient and trustable method for such irrigation planning problems. By optimum allocation of the water to the farms with different areas and crop types, and considering the deficit irrigation method, the general income of the entire area can be improved substantially.

Efficient Execution of Microscopy Image Analysis on CPU, GPU, and MIC Equipped Cluster Systems.

PubMed

Andrade, G; Ferreira, R; Teodoro, George; Rocha, Leonardo; Saltz, Joel H; Kurc, Tahsin

2014-10-01

High performance computing is experiencing a major paradigm shift with the introduction of accelerators, such as graphics processing units (GPUs) and Intel Xeon Phi (MIC). These processors have made available a tremendous computing power at low cost, and are transforming machines into hybrid systems equipped with CPUs and accelerators. Although these systems can deliver a very high peak performance, making full use of its resources in real-world applications is a complex problem. Most current applications deployed to these machines are still being executed in a single processor, leaving other devices underutilized. In this paper we explore a scenario in which applications are composed of hierarchical data flow tasks which are allocated to nodes of a distributed memory machine in coarse-grain, but each of them may be composed of several finer-grain tasks which can be allocated to different devices within the node. We propose and implement novel performance aware scheduling techniques that can be used to allocate tasks to devices. We evaluate our techniques using a pathology image analysis application used to investigate brain cancer morphology, and our experimental evaluation shows that the proposed scheduling strategies significantly outperforms other efficient scheduling techniques, such as Heterogeneous Earliest Finish Time - HEFT, in cooperative executions using CPUs, GPUs, and MICs. We also experimentally show that our strategies are less sensitive to inaccuracy in the scheduling input data and that the performance gains are maintained as the application scales.

Efficient Execution of Microscopy Image Analysis on CPU, GPU, and MIC Equipped Cluster Systems

PubMed Central

Andrade, G.; Ferreira, R.; Teodoro, George; Rocha, Leonardo; Saltz, Joel H.; Kurc, Tahsin

2015-01-01

High performance computing is experiencing a major paradigm shift with the introduction of accelerators, such as graphics processing units (GPUs) and Intel Xeon Phi (MIC). These processors have made available a tremendous computing power at low cost, and are transforming machines into hybrid systems equipped with CPUs and accelerators. Although these systems can deliver a very high peak performance, making full use of its resources in real-world applications is a complex problem. Most current applications deployed to these machines are still being executed in a single processor, leaving other devices underutilized. In this paper we explore a scenario in which applications are composed of hierarchical data flow tasks which are allocated to nodes of a distributed memory machine in coarse-grain, but each of them may be composed of several finer-grain tasks which can be allocated to different devices within the node. We propose and implement novel performance aware scheduling techniques that can be used to allocate tasks to devices. We evaluate our techniques using a pathology image analysis application used to investigate brain cancer morphology, and our experimental evaluation shows that the proposed scheduling strategies significantly outperforms other efficient scheduling techniques, such as Heterogeneous Earliest Finish Time - HEFT, in cooperative executions using CPUs, GPUs, and MICs. We also experimentally show that our strategies are less sensitive to inaccuracy in the scheduling input data and that the performance gains are maintained as the application scales. PMID:26640423

MTR,TRA603. EXPERIMENTERS' SPACE ALLOCATIONS IN BASEMENT AS OF 1963. SHIELDED ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

MTR,TRA-603. EXPERIMENTERS' SPACE ALLOCATIONS IN BASEMENT AS OF 1963. SHIELDED CUBICLES WERE IDENTIFIED BY SPONSORING LABORATORY AND ITS TEST HOLE NUMBER IN THE REACTOR, IE, "KAPL HB-1" SIGNIFIED KNOLLS ATOMIC POWER LABORATORY, HORIZONTAL BEAM NO. 1. "WAPD" WAS WESTINGHOUSE ATOMIC POWER DIVISION. CATCH TANKS AND SAMPLE STATIONS FOR TEST LOOPS WERE ASSOCIATED WITH THESE CUBICLES. NOTE DESKS, STORAGE CABINETS, SWITCH GEAR, INSTRUMENT PANELS. PHILLIPS PETROLEUM COMPANY MTR-E-5205, 4/1963. INL INDEX NO. 531-0603-00-706-009757, REV. 5. - Idaho National Engineering Laboratory, Test Reactor Area, Materials & Engineering Test Reactors, Scoville, Butte County, ID

Gender Discrimination in the Allocation of Migrant Household Resources.

PubMed

Antman, Francisca M

2015-07-01

This paper considers the relationship between international migration and gender discrimination through the lens of decision-making power over intrahousehold resource allocation. The endogeneity of migration is addressed with a difference-in-differences style identification strategy and a model with household fixed effects. The results suggest that while a migrant household head is away, a greater share of resources is spent on girls relative to boys and his spouse commands greater decision-making power. Once the head returns home, however, a greater share of resources goes to boys and there is suggestive evidence of greater authority for the head of household.

IDMA-Based MAC Protocol for Satellite Networks with Consideration on Channel Quality

PubMed Central

2014-01-01

In order to overcome the shortcomings of existing medium access control (MAC) protocols based on TDMA or CDMA in satellite networks, interleave division multiple access (IDMA) technique is introduced into satellite communication networks. Therefore, a novel wide-band IDMA MAC protocol based on channel quality is proposed in this paper, consisting of a dynamic power allocation algorithm, a rate adaptation algorithm, and a call admission control (CAC) scheme. Firstly, the power allocation algorithm combining the technique of IDMA SINR-evolution and channel quality prediction is developed to guarantee high power efficiency even in terrible channel conditions. Secondly, the effective rate adaptation algorithm, based on accurate channel information per timeslot and by the means of rate degradation, can be realized. What is more, based on channel quality prediction, the CAC scheme, combining the new power allocation algorithm, rate scheduling, and buffering strategies together, is proposed for the emerging IDMA systems, which can support a variety of traffic types, and offering quality of service (QoS) requirements corresponding to different priority levels. Simulation results show that the new wide-band IDMA MAC protocol can make accurate estimation of available resource considering the effect of multiuser detection (MUD) and QoS requirements of multimedia traffic, leading to low outage probability as well as high overall system throughput. PMID:25126592

Time for a new budget allocation model for hospital care in Stockholm?

PubMed

Andersson, Per-Åke; Bruce, Daniel; Walander, Anders; Viberg, Inga

2011-03-01

In Stockholm County Council (SLL), budgets for hospital care have been allocated to geographically responsible authorities for a long time. This hospital care includes all publicly financed specialist care, also privately owned hospitals, except private practitioner care. The old needs-index model, a 6D capitation matrix based on demography and socio-economy, was generated on linked individual data for 1994-96. In this paper the power of the old allocation model is evaluated by the use of new data for 2006. The analysis shows that most of the socioeconomic variables have lost their descriptive power in 10 years. Using a methodical search we also find an improved need-based allocation model for hospital care using the new data for 2006. By focusing on costly diagnoses, where the descriptive power has increased between 1996 and 2006, and by using some new socioeconomic variables, and by relying on birth and death prognoses, we are able to generate a matrix model with much higher coefficients-of-determinations in 1 year predictions. In addition, a more careful modelling of multi-morbidity, part-of-the-year inhabitants, episode definition and cost transformation is developed. The area-level cost residuals of registered versus predicted costs show stable signs over the years, indicating unexplained systematics. For the reduction of the residuals, accepting proven inpatient diagnoses but not the full costs, a mixed capitation/fee-for-service strategy is discussed. Once equivalent (e.g. full-year) observations are determined, the link between background and consumption is not on individual-level but on cell-level, as in current resource allocation studies in the United Kingdom.

Energy-efficient orthogonal frequency division multiplexing-based passive optical network based on adaptive sleep-mode control and dynamic bandwidth allocation

NASA Astrophysics Data System (ADS)

Zhang, Chongfu; Xiao, Nengwu; Chen, Chen; Yuan, Weicheng; Qiu, Kun

2016-02-01

We propose an energy-efficient orthogonal frequency division multiplexing-based passive optical network (OFDM-PON) using adaptive sleep-mode control and dynamic bandwidth allocation. In this scheme, a bidirectional-centralized algorithm named the receiver and transmitter accurate sleep control and dynamic bandwidth allocation (RTASC-DBA), which has an overall bandwidth scheduling policy, is employed to enhance the energy efficiency of the OFDM-PON. The RTASC-DBA algorithm is used in an optical line terminal (OLT) to control the sleep mode of an optical network unit (ONU) sleep and guarantee the quality of service of different services of the OFDM-PON. The obtained results show that, by using the proposed scheme, the average power consumption of the ONU is reduced by ˜40% when the normalized ONU load is less than 80%, compared with the average power consumption without using the proposed scheme.

An intelligent allocation algorithm for parallel processing

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Homaifar, Abdollah; Ananthram, Kishan G.

1988-01-01

The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.

Claim Your Powers.

ERIC Educational Resources Information Center

Update on Law-Related Education, 1986

1986-01-01

Presents a game which has students interpret Articles I, II, and III of the U.S. Constitution to understand the allocation of powers among the 3 branches of government. The game helps students understand the interaction between the 3 branches of government, stressing the separation of powers and the system of checks and balances. (JDH)

General form of a cooperative gradual maximal covering location problem

NASA Astrophysics Data System (ADS)

Bagherinejad, Jafar; Bashiri, Mahdi; Nikzad, Hamideh

2018-07-01

Cooperative and gradual covering are two new methods for developing covering location models. In this paper, a cooperative maximal covering location-allocation model is developed (CMCLAP). In addition, both cooperative and gradual covering concepts are applied to the maximal covering location simultaneously (CGMCLP). Then, we develop an integrated form of a cooperative gradual maximal covering location problem, which is called a general CGMCLP. By setting the model parameters, the proposed general model can easily be transformed into other existing models, facilitating general comparisons. The proposed models are developed without allocation for physical signals and with allocation for non-physical signals in discrete location space. Comparison of the previously introduced gradual maximal covering location problem (GMCLP) and cooperative maximal covering location problem (CMCLP) models with our proposed CGMCLP model in similar data sets shows that the proposed model can cover more demands and acts more efficiently. Sensitivity analyses are performed to show the effect of related parameters and the model's validity. Simulated annealing (SA) and a tabu search (TS) are proposed as solution algorithms for the developed models for large-sized instances. The results show that the proposed algorithms are efficient solution approaches, considering solution quality and running time.

On-Line Allocation Of Robot Resources To Task Plans

NASA Astrophysics Data System (ADS)

Lyons, Damian M.

1989-02-01

In this paper, I present an approach to representing plans that make on-line decisions about resource allocation. An on-line decision is the evaluation of a conditional expression involving sensory information as the plan is being executed. I use a plan representation called 7ZS10'1 1,12that has been especially designed for the domain of robot programming, and in particular, for the problem of on-line decisions. The resource allocation example is based on the robot assembly cell architecture outlined by Venkataraman and Lyons16. I begin by setting forth a definition of on-line decision making and some arguments as to why this form of decision making is important and useful. To set the context for the resource allocation example, I take some care in categorizing the types of on-line decision making and the approaches adopted by other workers so far. In particular, I justify a plan-based approach to the study of on-line decision making. From that, the focus shifts to one type of decision making: on-line allocation of robot resources to task plans. Robot resources are the physical manipulators (grippers, wrists, arms, feeders, etc) that are available to carry out the task. I formulate the assembly cell architecture of Venkataraman and Lyons16 as an R.S plan schema, and show how the on-line allocation specified in that architecture can be implemented. Finally, I show how considering the on-line allocation of logical resources, that is a physical resource plus some model information, can be used as a non-traditional approach to some problems in robot task planning.

Alternative mathematical programming formulations for FSS synthesis

NASA Technical Reports Server (NTRS)

Reilly, C. H.; Mount-Campbell, C. A.; Gonsalvez, D. J. A.; Levis, C. A.

1986-01-01

A variety of mathematical programming models and two solution strategies are suggested for the problem of allocating orbital positions to (synthesizing) satellites in the Fixed Satellite Service. Mixed integer programming and almost linear programming formulations are presented in detail for each of two objectives: (1) positioning satellites as closely as possible to specified desired locations, and (2) minimizing the total length of the geostationary arc allocated to the satellites whose positions are to be determined. Computational results for mixed integer and almost linear programming models, with the objective of positioning satellites as closely as possible to their desired locations, are reported for three six-administration test problems and a thirteen-administration test problem.

A centre-free approach for resource allocation with lower bounds

NASA Astrophysics Data System (ADS)

Obando, Germán; Quijano, Nicanor; Rakoto-Ravalontsalama, Naly

2017-09-01

Since complexity and scale of systems are continuously increasing, there is a growing interest in developing distributed algorithms that are capable to address information constraints, specially for solving optimisation and decision-making problems. In this paper, we propose a novel method to solve distributed resource allocation problems that include lower bound constraints. The optimisation process is carried out by a set of agents that use a communication network to coordinate their decisions. Convergence and optimality of the method are guaranteed under some mild assumptions related to the convexity of the problem and the connectivity of the underlying graph. Finally, we compare our approach with other techniques reported in the literature, and we present some engineering applications.

Social problem-solving plus psychoeducation for adults with personality disorder: pragmatic randomised controlled trial.

PubMed

Huband, Nick; McMurran, Mary; Evans, Chris; Duggan, Conor

2007-04-01

Social problem-solving therapy may be relevant in the treatment of personality disorder, although assessments of its effectiveness are uncommon. To determine the effectiveness of a problem-solving intervention for adults with personality disorder in the community under conditions resembling routine clinical practice. Participants were randomly allocated to brief psychoeducation plus 16 problem-solving group sessions (n=87) or to waiting-list control (n=89). Primary outcome was comparison of scores on the Social Problem Solving Inventory and the Social Functioning Questionnaire between intervention and control arms at the conclusion of treatment, on average at 24 weeks after randomisation. In intention-to-treat analysis, those allocated to intervention showed significantly better problem-solving skills (P<0.001), higher overall social functioning (P=0.031) and lower anger expression (P=0.039) compared with controls. No significant differences were found on use of services during the intervention period. Problem-solving plus psychoeducation has potential as a preliminary intervention for adults with personality disorder.

Problems, Perplexities, and Politics of Program Evaluation.

ERIC Educational Resources Information Center

Schneider, Gail Thierbach

All educational evaluations share common problems, perplexities, and political considerations. Logistic problems include incomplete definition of purpose, unclear timelines and personnel allocations, inadequate support services, and the lack of a program plan. Interpersonal dynamics and conflicts plus unwieldy committee structures are perplexities…

The dominance of big pharma: power.

PubMed

Edgar, Andrew

2013-05-01

The purpose of this paper is to provide a normative model for the assessment of the exercise of power by Big Pharma. By drawing on the work of Steven Lukes, it will be argued that while Big Pharma is overtly highly regulated, so that its power is indeed restricted in the interests of patients and the general public, the industry is still able to exercise what Lukes describes as a third dimension of power. This entails concealing the conflicts of interest and grievances that Big Pharma may have with the health care system, physicians and patients, crucially through rhetorical engagements with Patient Advocacy Groups that seek to shape public opinion, and also by marginalising certain groups, excluding them from debates over health care resource allocation. Three issues will be examined: the construction of a conception of the patient as expert patient or consumer; the phenomenon of disease mongering; the suppression or distortion of debates over resource allocation.

Playing Games with Optimal Competitive Scheduling

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Crawford, James; Khatib, Lina; Brafman, Ronen

2005-01-01

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, selfish preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource.

Solving the optimal attention allocation problem in manual control

NASA Technical Reports Server (NTRS)

Kleinman, D. L.

1976-01-01

Within the context of the optimal control model of human response, analytic expressions for the gradients of closed-loop performance metrics with respect to human operator attention allocation are derived. These derivatives serve as the basis for a gradient algorithm that determines the optimal attention that a human should allocate among several display indicators in a steady-state manual control task. Application of the human modeling techniques are made to study the hover control task for a CH-46 VTOL flight tested by NASA.

Annual Review of Progress in Applied Computational Electromagnetics (6th), Held in Monterey, California on March 19-22, 1990

DTIC Science & Technology

1990-01-01

the six fields will have two million cell locations. The table below shows the total allocation of 392 chips across fields and banks. To allow for...future growth, we allocate 16 wires for addressing both the rows and columns. eU 4 MBit locations bytes bits Chips (millions) (millions) (millions) per...sources apt to appear in most problems. If material parameters change during a run, then time must be allocated to read these constants into their

Mutual information-based LPI optimisation for radar network

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Zhou, Jianjiang; Wang, Fei; Chen, Jun

2015-07-01

Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.

Power train and emission control: allocation procedure by OBD-II system for automotive technology

NASA Astrophysics Data System (ADS)

Kalita, Porag

2017-06-01

OBD-II, systems were designed to maintain low emissions of in use vehicles, including light and medium duty vehicles. In 1989, the California code of Regulations (CCR) known as OBD - II was adopted by the California Air Resource Board (CARB) and the objective to reduce hydrocarbon (HC) emission caused by malfunction of the vehicles emission control systems. OBD-II provides additional information to engineer for diagnosis and repair of emissions related problems. OBD-II, standardizes on the amount of memory (Freeze Frame) it uses to store the readings of the vehicle sensor when it logs on emission related Intermittent Trouble code (IT). The intent of OBD-II, systems is to detect most vehicle malfunctions when performance of a power train component or system deteriorates to the point that the vehicle’s HC emission exceed standard. The vehicle operator is notified at the time when the vehicle begins to marginally exceed emission standards, by illuminating the Malfunctions Indicator Light (MIL).

From ideals to deals-The effect of impartiality experience on stakeholder behavior.

PubMed

Halko, Marja-Liisa; Miettinen, Topi

2017-01-01

In this paper, we study a two-party pie-sharing problem in the presence of asymmetries in the stakeholders' private endowments. Both the two stakeholders and third-party arbitrators may influence the outcome. We consider Nash-demand negotiations, where the two stakeholders place demands and share the pie accordingly if demands are compatible, and elicit dictatorial allocations from the stakeholders and the arbitrators. The Nash demands by stakeholders are strategic; the dictatorial allocations by stakeholders and arbitrators are non-strategic. We are interested in the influence of the past arbitrator experience on stakeholder allocations and demands and the past stakeholder experience on third-party arbitration allocations. We find that the ex-arbitrators' stakeholder allocations differ more from the impartial ideal than the stakeholder allocations by those without arbitration experience. In contrast with previous findings, the arbitration outcomes do not depend on the asymmetries in the previous stakeholder roles.

From ideals to deals—The effect of impartiality experience on stakeholder behavior

PubMed Central

2017-01-01

In this paper, we study a two-party pie-sharing problem in the presence of asymmetries in the stakeholders' private endowments. Both the two stakeholders and third-party arbitrators may influence the outcome. We consider Nash-demand negotiations, where the two stakeholders place demands and share the pie accordingly if demands are compatible, and elicit dictatorial allocations from the stakeholders and the arbitrators. The Nash demands by stakeholders are strategic; the dictatorial allocations by stakeholders and arbitrators are non-strategic. We are interested in the influence of the past arbitrator experience on stakeholder allocations and demands and the past stakeholder experience on third-party arbitration allocations. We find that the ex-arbitrators' stakeholder allocations differ more from the impartial ideal than the stakeholder allocations by those without arbitration experience. In contrast with previous findings, the arbitration outcomes do not depend on the asymmetries in the previous stakeholder roles. PMID:28786988

Robust Inversion and Data Compression in Control Allocation

NASA Technical Reports Server (NTRS)

Hodel, A. Scottedward

2000-01-01

We present an off-line computational method for control allocation design. The control allocation function delta = F(z)tau = delta (sub 0) (z) mapping commanded body-frame torques to actuator commands is implicitly specified by trim condition delta (sub 0) (z) and by a robust pseudo-inverse problem double vertical line I - G(z) F(z) double vertical line less than epsilon (z) where G(z) is a system Jacobian evaluated at operating point z, z circumflex is an estimate of z, and epsilon (z) less than 1 is a specified error tolerance. The allocation function F(z) = sigma (sub i) psi (z) F (sub i) is computed using a heuristic technique for selecting wavelet basis functions psi and a constrained least-squares criterion for selecting the allocation matrices F (sub i). The method is applied to entry trajectory control allocation for a reusable launch vehicle (X-33).

Optimization, Monotonicity and the Determination of Nash Equilibria — An Algorithmic Analysis

NASA Astrophysics Data System (ADS)

Lozovanu, D.; Pickl, S. W.; Weber, G.-W.

2004-08-01

This paper is concerned with the optimization of a nonlinear time-discrete model exploiting the special structure of the underlying cost game and the property of inverse matrices. The costs are interlinked by a system of linear inequalities. It is shown that, if the players cooperate, i.e., minimize the sum of all the costs, they achieve a Nash equilibrium. In order to determine Nash equilibria, the simplex method can be applied with respect to the dual problem. An introduction into the TEM model and its relationship to an economic Joint Implementation program is given. The equivalence problem is presented. The construction of the emission cost game and the allocation problem is explained. The assumption of inverse monotony for the matrices leads to a new result in the area of such allocation problems. A generalization of such problems is presented.

A Parallel Finite Set Statistical Simulator for Multi-Target Detection and Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; MacMillan, R.

2014-09-01

Finite Set Statistics (FISST) is a powerful Bayesian inference tool for the joint detection, classification and tracking of multi-target environments. FISST is capable of handling phenomena such as clutter, misdetections, and target birth and decay. Implicit within the approach are solutions to the data association and target label-tracking problems. Finally, FISST provides generalized information measures that can be used for sensor allocation across different types of tasks such as: searching for new targets, and classification and tracking of known targets. These FISST capabilities have been demonstrated on several small-scale illustrative examples. However, for implementation in a large-scale system as in the Space Situational Awareness problem, these capabilities require a lot of computational power. In this paper, we implement FISST in a parallel environment for the joint detection and tracking of multi-target systems. In this implementation, false alarms and misdetections will be modeled. Target birth and decay will not be modeled in the present paper. We will demonstrate the success of the method for as many targets as we possibly can in a desktop parallel environment. Performance measures will include: number of targets in the simulation, certainty of detected target tracks, computational time as a function of clutter returns and number of targets, among other factors.

Optimized maritime emergency resource allocation under dynamic demand.

PubMed

Zhang, Wenfen; Yan, Xinping; Yang, Jiaqi

2017-01-01

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.

Optimized maritime emergency resource allocation under dynamic demand

PubMed Central

Yan, Xinping; Yang, Jiaqi

2017-01-01

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand. PMID:29240792

Titrating versus targeting home care services to frail elderly clients: an application of agency theory and cost-benefit analysis to home care policy.

PubMed

Weissert, William; Chernew, Michael; Hirth, Richard

2003-02-01

The article summarizes the shortcomings of current home care targeting policy, provides a conceptual framework for understanding the sources of its problems, and proposes an alternative resource allocation method. Methods required for different aspects of the study included synthesis of the published literature, regression analysis of risk predictors, and comparison of actual resource allocations with simulated budgets. Problems of imperfect agency ranging from unclear goals and inappropriate incentives to lack of information about the marginal effectiveness of home care could be mitigated with an improved budgeting method that combines client selection and resource allocation. No program can produce its best outcome performance when its goals are unclear and its technology is unstandardized. Titration of care would reallocate resources to maximize marginal benefit for marginal cost.

A QoS Aware Resource Allocation Strategy for 3D A/V Streaming in OFDMA Based Wireless Systems

PubMed Central

Chung, Young-uk; Choi, Yong-Hoon; Park, Suwon; Lee, Hyukjoon

2014-01-01

Three-dimensional (3D) video is expected to be a “killer app” for OFDMA-based broadband wireless systems. The main limitation of 3D video streaming over a wireless system is the shortage of radio resources due to the large size of the 3D traffic. This paper presents a novel resource allocation strategy to address this problem. In the paper, the video-plus-depth 3D traffic type is considered. The proposed resource allocation strategy focuses on the relationship between 2D video and the depth map, handling them with different priorities. It is formulated as an optimization problem and is solved using a suboptimal heuristic algorithm. Numerical results show that the proposed scheme provides a better quality of service compared to conventional schemes. PMID:25250377

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.

Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

NASA Astrophysics Data System (ADS)

Schäfer, Mirko; Tranberg, Bo; Hempel, Sabrina; Schramm, Stefan; Greiner, Martin

2017-08-01

The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

NASA Astrophysics Data System (ADS)

Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

2018-02-01

The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

Optimal allocation of resources for suppressing epidemic spreading on networks

NASA Astrophysics Data System (ADS)

Chen, Hanshuang; Li, Guofeng; Zhang, Haifeng; Hou, Zhonghuai

2017-07-01

Efficient allocation of limited medical resources is crucial for controlling epidemic spreading on networks. Based on the susceptible-infected-susceptible model, we solve the optimization problem of how best to allocate the limited resources so as to minimize prevalence, providing that the curing rate of each node is positively correlated to its medical resource. By quenched mean-field theory and heterogeneous mean-field (HMF) theory, we prove that an epidemic outbreak will be suppressed to the greatest extent if the curing rate of each node is directly proportional to its degree, under which the effective infection rate λ has a maximal threshold λcopt=1 / , where is the average degree of the underlying network. For a weak infection region (λ ≳λcopt ), we combine perturbation theory with the Lagrange multiplier method (LMM) to derive the analytical expression of optimal allocation of the curing rates and the corresponding minimized prevalence. For a general infection region (λ >λcopt ), the high-dimensional optimization problem is converted into numerically solving low-dimensional nonlinear equations by the HMF theory and LMM. Counterintuitively, in the strong infection region the low-degree nodes should be allocated more medical resources than the high-degree nodes to minimize prevalence. Finally, we use simulated annealing to validate the theoretical results.

Superframe Duration Allocation Schemes to Improve the Throughput of Cluster-Tree Wireless Sensor Networks

PubMed Central

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-01-01

The use of Wireless Sensor Network (WSN) technologies is an attractive option to support wide-scale monitoring applications, such as the ones that can be found in precision agriculture, environmental monitoring and industrial automation. The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable topology to build wide-scale WSNs. Despite some of its known advantages, including timing synchronisation and duty-cycle operation, cluster-tree networks may suffer from severe network congestion problems due to the convergecast pattern of its communication traffic. Therefore, the careful adjustment of transmission opportunities (superframe durations) allocated to the cluster-heads is an important research issue. This paper proposes a set of proportional Superframe Duration Allocation (SDA) schemes, based on well-defined protocol and timing models, and on the message load imposed by child nodes (Load-SDA scheme), or by number of descendant nodes (Nodes-SDA scheme) of each cluster-head. The underlying reasoning is to adequately allocate transmission opportunities (superframe durations) and parametrize buffer sizes, in order to improve the network throughput and avoid typical problems, such as: network congestion, high end-to-end communication delays and discarded messages due to buffer overflows. Simulation assessments show how proposed allocation schemes may clearly improve the operation of wide-scale cluster-tree networks. PMID:28134822

Microwave-Driven Multifunctional Capability of Membrane Structures

NASA Technical Reports Server (NTRS)

Choi, Sang H.; Chu, Sang-Hyong; Song, Kyo D.; King, Glen C.

2002-01-01

A large, ultra lightweight space structure, such as solar sails and Gossamer spacecrafts, requires a distributed power source to alleviate wire networks, unlike the localized on-board power infrastructures typically found in most small spacecrafts. The concept of microwave-driven multifunctional capability for membrane structures is envisioned as the best option to alleviate the complexity associated with hard-wired control circuitry and on-board power infrastructures. A rectenna array based on a patch configuration for high voltage output was developed to drive membrane actuators, sensors, probes, or other devices. Networked patch rectenna array receives and converts microwave power into a DC power for an array of smart actuators. To use microwave power effectively, the concept of a power allocation and distribution (PAD) circuit is adopted for networking a rectenna/actuator patch array. The use of patch rectennas adds a significant amount of rigidity to membrane flexibility and they are relatively heavy. A dipole rectenna array (DRA) appears to be ideal for thin-film membrane structures, since DRA is flexible and light. Preliminary design and fabrication of PAD circuitry that consists of a few nodal elements were made for laboratory testing. The networked actuators were tested to correlate the network coupling effect, power allocation and distribution, and response time.

"Catch the Pendulum": The Problem of Asymmetric Data Delivery in Electromagnetic Nanonetworks.

PubMed

Islam, Nabiul; Misra, Sudip

2016-09-01

The network of novel nano-material based nanodevices, known as nanoscale communication networks or nanonetworks has ushered a new communication paradigm in the terahertz band (0.1-10 THz). In this work, first we envisage an architecture of nanonetworks-based Coronary Heart Disease (CHD) monitoring, consisting of nano-macro interface (NM) and nanodevice-embedded Drug Eluting Stents (DESs), termed as nanoDESs. Next, we study the problem of asymmetric data delivery in such nanonetworks-based systems and propose a simple distance-aware power allocation algorithm, named catch-the-pendulum, which optimizes the energy consumption of nanoDESs for communicating data from the underlying nanonetworks to radio frequency (RF) based macro-scale communication networks. The algorithm exploits the periodic change in mean distance between a nanoDES, inserted inside the affected coronary artery, and the NM, fitted in the intercostal space of the rib cage of a patient suffering from a CHD. Extensive simulations confirm superior performance of the proposed algorithm with respect to energy consumption, packet delivery, and shutdown phase.

The potential of crowdsourcing to improve patient-centered care.

PubMed

Weiner, Michael

2014-01-01

Crowdsourcing (CS) is the outsourcing of a problem or task to a crowd. Although patient-centered care (PCC) may aim to be tailored to an individual's needs, the uses of CS for generating ideas, identifying values, solving problems, facilitating research, and educating an audience represent powerful roles that can shape both allocation of shared resources and delivery of personalized care and treatment. CS can often be conducted quickly and at relatively low cost. Pitfalls include bias, risks of research ethics, inadequate quality of data, inadequate metrics, and observer-expectancy effect. Health professionals and consumers in the US should increase their attention to CS for the benefit of PCC. Patients' participation in CS to shape health policy and decisions is one way to pursue PCC itself and may help to improve clinical outcomes through a better understanding of patients' perspectives. CS should especially be used to traverse the quality-cost curve, or decrease costs while preserving or improving quality of care.

Allocation of Playing Time within Team Sports--A Problem for Discussion

ERIC Educational Resources Information Center

Lorentzen, Torbjørn

2017-01-01

The background of the article is the recurrent discussion about allocation of playing time in team sports involving children and young athletes. The objective is to analyse "why" playing time is a topic for discussion among parents, coaches and athletes. The following question is addressed: Under which condition is it "fair" to…

Research versus Advocacy in the Allocation of Resources: Problems, Causes, Solutions.

ERIC Educational Resources Information Center

Menolascino, Frank J.; Stark, Jack A.

1990-01-01

This commentary on EC 231 901 discusses whether resource allocations and service policies for mentally retarded individuals should be based upon purported findings of scientific theory or the purported needs of service systems. The paper calls for improved research utilization and understanding of what makes a social movement work. (JDD)

The Cost Structure of Higher Education: Implications for Governmental Policy in Steady State.

ERIC Educational Resources Information Center

Lyell, Edward H.

The historical pattern of resource allocation in American higher education as exemplified by public colleges in Colorado was examined. The reliance upon average cost information in making resource allocation decisions was critiqued for the special problems that arise from student enrollment decline or steady state. A model of resource allocation…

Distributive Decisions in Education: Goals, Trade-Offs, and Feasibility Constraints

ERIC Educational Resources Information Center

Shores, Kenneth; Loeb, Susanna

2016-01-01

Educators, policymakers, and citizens face questions of how to allocate scarce resources in the pursuit of competing goals for children and youth. Our goal in this article is to provide decision-makers with a framework for considering allocative problems in education, explicitly highlighting the implications of relevant feasibility constraints. We…

Implementation and Incentive of Education Policies: Experience from the High School Admissions Quota Allocation Policy

ERIC Educational Resources Information Center

Shiyue, Wang

2017-01-01

Improving administrative efficiency is the core problem in administrative governance. This case study of quota allocation policy implementation in City A reveals that a set of education policy implementation and incentive mechanisms revolving around responsibility contracts and target evaluations has already taken shape, to guarantee effective…

Carbon allocation and morphology of cherrybark oak seedlings and sprouts under three light regimes

Treesearch

Brian Roy Lockhart; Emile S. Gardiner; John D. Hodges; Andrew W. Ezell

2008-01-01

Continued problems in regenerating oak forests has led to a need for more basic infomation on oak seedling biology.In the present study, carbon allocation and morphology were compared between cherrybark oak (Quercus pagoda Raf.) seedlings and sprouts at I -Lag grown in full, 47%, and 20% sunlight....

Hoover Power Allocation Act of 2009

THOMAS, 111th Congress

Sen. Reid, Harry [D-NV

2009-12-16

Senate - 06/09/2010 Committee on Energy and Natural Resources Subcommittee on Water and Power. Hearings held. With printed Hearing: S.Hrg. 111-707. (All Actions) Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

Optimal water resource allocation modelling in the Lowveld of Zimbabwe

NASA Astrophysics Data System (ADS)

Mhiribidi, Delight; Nobert, Joel; Gumindoga, Webster; Rwasoka, Donald T.

2018-05-01

The management and allocation of water from multi-reservoir systems is complex and thus requires dynamic modelling systems to achieve optimality. A multi-reservoir system in the Southern Lowveld of Zimbabwe is used for irrigation of sugarcane estates that produce sugar for both local and export consumption. The system is burdened with water allocation problems, made worse by decommissioning of dams. Thus the aim of this research was to develop an operating policy model for the Lowveld multi-reservoir system.The Mann Kendall Trend and Wilcoxon Signed-Rank tests were used to assess the variability of historic monthly rainfall and dam inflows for the period 1899-2015. The WEAP model was set up to evaluate the water allocation system of the catchment and come-up with a reference scenario for the 2015/2016 hydrologic year. Stochastic Dynamic Programming approach was used for optimisation of the multi-reservoirs releases.Results showed no significant trend in the rainfall but a significantly decreasing trend in inflows (p < 0.05). The water allocation model (WEAP) showed significant deficits ( ˜ 40 %) in irrigation water allocation in the reference scenario. The optimal rule curves for all the twelve months for each reservoir were obtained and considered to be a proper guideline for solving multi- reservoir management problems within the catchment. The rule curves are effective tools in guiding decision makers in the release of water without emptying the reservoirs but at the same time satisfying the demands based on the inflow, initial storage and end of month storage.

26 CFR 20.2056(b)-5 - Marital deduction; life estate with power of appointment in surviving spouse.

Code of Federal Regulations, 2011 CFR

2011-04-01

... apportionment between the income and remainder beneficiaries of the total return of the trust and that meets the... absence, by the rules for the management of the trust property and the allocation of receipts and... assets and the rules provided for management of the trust that the allocation to income of such receipts...

Nanoscale molecular communication networks: a game-theoretic perspective

NASA Astrophysics Data System (ADS)

Jiang, Chunxiao; Chen, Yan; Ray Liu, K. J.

2015-12-01

Currently, communication between nanomachines is an important topic for the development of novel devices. To implement a nanocommunication system, diffusion-based molecular communication is considered as a promising bio-inspired approach. Various technical issues about molecular communications, including channel capacity, noise and interference, and modulation and coding, have been studied in the literature, while the resource allocation problem among multiple nanomachines has not been well investigated, which is a very important issue since all the nanomachines share the same propagation medium. Considering the limited computation capability of nanomachines and the expensive information exchange cost among them, in this paper, we propose a game-theoretic framework for distributed resource allocation in nanoscale molecular communication systems. We first analyze the inter-symbol and inter-user interference, as well as bit error rate performance, in the molecular communication system. Based on the interference analysis, we formulate the resource allocation problem as a non-cooperative molecule emission control game, where the Nash equilibrium is found and proved to be unique. In order to improve the system efficiency while guaranteeing fairness, we further model the resource allocation problem using a cooperative game based on the Nash bargaining solution, which is proved to be proportionally fair. Simulation results show that the Nash bargaining solution can effectively ensure fairness among multiple nanomachines while achieving comparable social welfare performance with the centralized scheme.

Can self-care health books affect amount of contact with the primary health care team? A randomized controlled trial in general practice.

PubMed

Platts, Amanda; Mitton, Rosly; Boniface, David; Friedli, Karin

2005-09-01

To investigate the effects of two differently styled self-care health books in general practice on the frequency and duration of patients' consultations and their views of the books. Random allocation of patients to either a descriptive or a decision-tree based self-care health book, or a no-book control condition. Three- and 12-months follow-up by postal questionnaire and monitoring of consultations. A large general practice in the South East of England. A total of 1967 volunteer, adult patients who attended the practice in 2001 participated. Demographics; health problems; use of health services; use and perceptions of the trial book; frequency and duration of consultations. Response rates to postal questionnaires at 3 and 12 months were 80% and 74%. In all, 48% consulted their allocated book, compared with 25% who consulted any healthcare book in the Control group. Those reporting health problems were more likely to have consulted their allocated book; 60% reported that the allocated book made them more likely to deal with a problem themselves and 40% reported themselves less likely to consult the practice. However, there were no differences in consultation rates or durations of consultations between the three groups. Handing out of self-care health books may provide qualitative benefits for patients but is unlikely to reduce attendance at the GP practice.

Routing design and fleet allocation optimization of freeway service patrol: Improved results using genetic algorithm

NASA Astrophysics Data System (ADS)

Sun, Xiuqiao; Wang, Jian

2018-07-01

Freeway service patrol (FSP), is considered to be an effective method for incident management and can help transportation agency decision-makers alter existing route coverage and fleet allocation. This paper investigates the FSP problem of patrol routing design and fleet allocation, with the objective of minimizing the overall average incident response time. While the simulated annealing (SA) algorithm and its improvements have been applied to solve this problem, they often become trapped in local optimal solution. Moreover, the issue of searching efficiency remains to be further addressed. In this paper, we employ the genetic algorithm (GA) and SA to solve the FSP problem. To maintain population diversity and avoid premature convergence, niche strategy is incorporated into the traditional genetic algorithm. We also employ elitist strategy to speed up the convergence. Numerical experiments have been conducted with the help of the Sioux Falls network. Results show that the GA slightly outperforms the dual-based greedy (DBG) algorithm, the very large-scale neighborhood searching (VLNS) algorithm, the SA algorithm and the scenario algorithm.

Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks.

PubMed

Shah, Shashi; Kittipiyakul, Somsak; Lim, Yuto; Tan, Yasuo

2018-05-10

The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.

Development of a conceptual integrated traffic safety problem identification database

DOT National Transportation Integrated Search

1999-12-01

The project conceptualized a traffic safety risk management information system and statistical database for improved problem-driver identification, countermeasure development, and resource allocation. The California Department of Motor Vehicles Drive...

Gender Discrimination in the Allocation of Migrant Household Resources*

PubMed Central

Antman, Francisca M.

2016-01-01

This paper considers the relationship between international migration and gender discrimination through the lens of decision-making power over intrahousehold resource allocation. The endogeneity of migration is addressed with a difference-in-differences style identification strategy and a model with household fixed effects. The results suggest that while a migrant household head is away, a greater share of resources is spent on girls relative to boys and his spouse commands greater decision-making power. Once the head returns home, however, a greater share of resources goes to boys and there is suggestive evidence of greater authority for the head of household. PMID:27546986

A Bayesian adaptive design for biomarker trials with linked treatments.

PubMed

Wason, James M S; Abraham, Jean E; Baird, Richard D; Gournaris, Ioannis; Vallier, Anne-Laure; Brenton, James D; Earl, Helena M; Mander, Adrian P

2015-09-01

Response to treatments is highly heterogeneous in cancer. Increased availability of biomarkers and targeted treatments has led to the need for trial designs that efficiently test new treatments in biomarker-stratified patient subgroups. We propose a novel Bayesian adaptive randomisation (BAR) design for use in multi-arm phase II trials where biomarkers exist that are potentially predictive of a linked treatment's effect. The design is motivated in part by two phase II trials that are currently in development. The design starts by randomising patients to the control treatment or to experimental treatments that the biomarker profile suggests should be active. At interim analyses, data from treated patients are used to update the allocation probabilities. If the linked treatments are effective, the allocation remains high; if ineffective, the allocation changes over the course of the trial to unlinked treatments that are more effective. Our proposed design has high power to detect treatment effects if the pairings of treatment with biomarker are correct, but also performs well when alternative pairings are true. The design is consistently more powerful than parallel-groups stratified trials. This BAR design is a powerful approach to use when there are pairings of biomarkers with treatments available for testing simultaneously.

New Mathematical Strategy Using Branch and Bound Method

NASA Astrophysics Data System (ADS)

Tarray, Tanveer Ahmad; Bhat, Muzafar Rasool

In this paper, the problem of optimal allocation in stratified random sampling is used in the presence of nonresponse. The problem is formulated as a nonlinear programming problem (NLPP) and is solved using Branch and Bound method. Also the results are formulated through LINGO.

Scenario-based modeling for multiple allocation hub location problem under disruption risk: multiple cuts Benders decomposition approach

NASA Astrophysics Data System (ADS)

Yahyaei, Mohsen; Bashiri, Mahdi

2017-12-01

The hub location problem arises in a variety of domains such as transportation and telecommunication systems. In many real-world situations, hub facilities are subject to disruption. This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. In the proposed model, the number of scenarios grows exponentially with the number of facilities. To alleviate this issue, two approaches are applied simultaneously. The first approach is to apply sample average approximation to approximate the two stochastic problem via sampling. Then, by applying the multiple cuts Benders decomposition approach, computational performance is enhanced. Numerical studies show the effective performance of the SAA in terms of optimality gap for small problem instances with numerous scenarios. Moreover, performance of multi-cut Benders decomposition is assessed through comparison with the classic version and the computational results reveal the superiority of the multi-cut approach regarding the computational time and number of iterations.

Behavioral Economic Measures of Alcohol Reward Value as Problem Severity Indicators in College Students

PubMed Central

Skidmore, Jessica R.; Murphy, James G.; Martens, Matthew P.

2014-01-01

The aims of the current study were to examine the associations among behavioral economic measures of alcohol value derived from three distinct measurement approaches, and to evaluate their respective relations with traditional indicators of alcohol problem severity in college drinkers. Five behavioral economic metrics were derived from hypothetical demand curves that quantify reward value by plotting consumption and expenditures as a function of price, another metric measured proportional behavioral allocation and enjoyment related to alcohol versus other activities, and a final metric measured relative discretionary expenditures on alcohol. The sample included 207 heavy drinking college students (53% female) who were recruited through an on-campus health center or university courses. Factor analysis revealed that the alcohol valuation construct comprises two factors: one factor that reflects participants’ levels of alcohol price sensitivity (demand persistence), and a second factor that reflects participants’ maximum consumption and monetary and behavioral allocation towards alcohol (amplitude of demand). The demand persistence and behavioral allocation metrics demonstrated the strongest and most consistent multivariate relations with alcohol-related problems, even when controlling for other well-established predictors. The results suggest that behavioral economic indices of reward value show meaningful relations with alcohol problem severity in young adults. Despite the presence of some gender differences, these measures appear to be useful problem indicators for men and women. PMID:24749779

The influence of power and actor relations on priority setting and resource allocation practices at the hospital level in Kenya: a case study.

PubMed

Barasa, Edwine W; Cleary, Susan; English, Mike; Molyneux, Sassy

2016-09-30

Priority setting and resource allocation in healthcare organizations often involves the balancing of competing interests and values in the context of hierarchical and politically complex settings with multiple interacting actor relationships. Despite this, few studies have examined the influence of actor and power dynamics on priority setting practices in healthcare organizations. This paper examines the influence of power relations among different actors on the implementation of priority setting and resource allocation processes in public hospitals in Kenya. We used a qualitative case study approach to examine priority setting and resource allocation practices in two public hospitals in coastal Kenya. We collected data by a combination of in-depth interviews of national level policy makers, hospital managers, and frontline practitioners in the case study hospitals (n = 72), review of documents such as hospital plans and budgets, minutes of meetings and accounting records, and non-participant observations in case study hospitals over a period of 7 months. We applied a combination of two frameworks, Norman Long's actor interface analysis and VeneKlasen and Miller's expressions of power framework to examine and interpret our findings RESULTS: The interactions of actors in the case study hospitals resulted in socially constructed interfaces between: 1) senior managers and middle level managers 2) non-clinical managers and clinicians, and 3) hospital managers and the community. Power imbalances resulted in the exclusion of middle level managers (in one of the hospitals) and clinicians and the community (in both hospitals) from decision making processes. This resulted in, amongst others, perceptions of unfairness, and reduced motivation in hospital staff. It also puts to question the legitimacy of priority setting processes in these hospitals. Designing hospital decision making structures to strengthen participation and inclusion of relevant stakeholders could improve priority setting practices. This should however, be accompanied by measures to empower stakeholders to contribute to decision making. Strengthening soft leadership skills of hospital managers could also contribute to managing the power dynamics among actors in hospital priority setting processes.

Optimal assignment of workers to supporting services in a hospital

NASA Astrophysics Data System (ADS)

Sawik, Bartosz; Mikulik, Jerzy

2008-01-01

Supporting services play an important role in health care institutions such as hospitals. This paper presents an application of operations research model for optimal allocation of workers among supporting services in a public hospital. The services include logistics, inventory management, financial management, operations management, medical analysis, etc. The optimality criterion of the problem is to minimize operations costs of supporting services subject to some specific constraints. The constraints represent specific conditions for resource allocation in a hospital. The overall problem is formulated as an integer program in the literature known as the assignment problem, where the decision variables represent the assignment of people to various jobs. The results of some computational experiments modeled on a real data from a selected Polish hospital are reported.

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.; Chu, Y. Y.; Greenstein, J. S.; Walden, R. S.

1976-01-01

An investigation was made of interaction between a human pilot and automated on-board decision making systems. Research was initiated on the topic of pilot problem solving in automated and semi-automated flight management systems and attempts were made to develop a model of human decision making in a multi-task situation. A study was made of allocation of responsibility between human and computer, and discussed were various pilot performance parameters with varying degrees of automation. Optimal allocation of responsibility between human and computer was considered and some theoretical results found in the literature were presented. The pilot as a problem solver was discussed. Finally the design of displays, controls, procedures, and computer aids for problem solving tasks in automated and semi-automated systems was considered.

Hybrid Resource Allocation Scheme with Proportional Fairness in OFDMA-Based Cognitive Radio Systems

NASA Astrophysics Data System (ADS)

Li, Li; Xu, Changqing; Fan, Pingzhi; He, Jian

In this paper, the resource allocation problem for proportional fairness in hybrid Cognitive Radio (CR) systems is studied. In OFDMA-based CR systems, traditional resource allocation algorithms can not guarantee proportional rates among CR users (CRU) in each OFDM symbol because the number of available subchannels might be smaller than that of CRUs in some OFDM symbols. To deal with this time-varying nature of available spectrum resource, a hybrid CR scheme in which CRUs are allowed to use subchannels in both spectrum holes and primary users (PU) bands is adopted and a resource allocation algorithm is proposed to guarantee proportional rates among CRUs with no undue interference to PUs.

Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration

NASA Astrophysics Data System (ADS)

Altaleb, Hesham

With the introduction of power energy markets deregulation, innovations have transformed once a static network into a more flexible grid. Microgrids have also been deployed to serve various purposes (e.g., reliability, sustainability, etc.). With the rapid deployment of smart grid technologies, it has become possible to measure and record both, the quantity and time of the consumption of electrical power. In addition, capabilities for controlling distributed supply and demand have resulted in complex systems where inefficiencies are possible and where improvements can be made. Electric power like other volatile resources cannot be stored efficiently, therefore, managing such resource requires considerable attention. Such complex systems present a need for decisions that can streamline consumption, delay infrastructure investments, and reduce costs. When renewable power resources and the need for limiting harmful emissions are added to the equation, the search space for decisions becomes increasingly complex. As a result, the need for a comprehensive decision guidance system for electrical power resources consumption and productions becomes evident. In this dissertation, I formulate and implement a comprehensive framework that addresses different aspect of the electrical power generation and consumption using optimization models and utilizing collaboration concepts. Our solution presents a two-prong approach: managing interaction in real-time for the short-term immediate consumption of already allocated resources; and managing the operational planning for the long-run consumption. More specifically, in real-time, we present and implement a model of how to organize a secondary market for peak-demand allocation and describe the properties of the market that guarantees efficient execution and a method for the fair distribution of collaboration gains. We also propose and implement a primary market for peak demand bounds determination problem with the assumption that participants of this market have the ability to collaborate in real-time. Moreover, proposed in this dissertation is an extensible framework to facilitate C&I entities forming a consortium to collaborate on their electric power supply and demand. The collaborative framework includes the structure of market setting, bids, and market resolution that produces a schedule of how power components are controlled as well as the resulting payment. The market resolution must satisfy a number of desirable properties (i.e., feasibility, Nash equilibrium, Pareto optimality, and equal collaboration profitability) which are formally defined in the dissertation. Furthermore, to support the extensible framework components' library, power components such as utility contract, back-up power generator, renewable resource, and power consuming service are formally modeled. Finally, the validity of this framework is evaluated by a case study using simulated load scenarios to examine the ability of the framework to efficiently operate at the specified time intervals with minimal overhead cost.

Some practical problems in implementing randomization.

PubMed

Downs, Matt; Tucker, Kathryn; Christ-Schmidt, Heidi; Wittes, Janet

2010-06-01

While often theoretically simple, implementing randomization to treatment in a masked, but confirmable, fashion can prove difficult in practice. At least three categories of problems occur in randomization: (1) bad judgment in the choice of method, (2) design and programming errors in implementing the method, and (3) human error during the conduct of the trial. This article focuses on these latter two types of errors, dealing operationally with what can go wrong after trial designers have selected the allocation method. We offer several case studies and corresponding recommendations for lessening the frequency of problems in allocating treatment or for mitigating the consequences of errors. Recommendations include: (1) reviewing the randomization schedule before starting a trial, (2) being especially cautious of systems that use on-demand random number generators, (3) drafting unambiguous randomization specifications, (4) performing thorough testing before entering a randomization system into production, (5) maintaining a dataset that captures the values investigators used to randomize participants, thereby allowing the process of treatment allocation to be reproduced and verified, (6) resisting the urge to correct errors that occur in individual treatment assignments, (7) preventing inadvertent unmasking to treatment assignments in kit allocations, and (8) checking a sample of study drug kits to allow detection of errors in drug packaging and labeling. Although we performed a literature search of documented randomization errors, the examples that we provide and the resultant recommendations are based largely on our own experience in industry-sponsored clinical trials. We do not know how representative our experience is or how common errors of the type we have seen occur. Our experience underscores the importance of verifying the integrity of the treatment allocation process before and during a trial. Clinical Trials 2010; 7: 235-245. http://ctj.sagepub.com.

Cooperative vehicle routing problem: an opportunity for cost saving

NASA Astrophysics Data System (ADS)

Zibaei, Sedighe; Hafezalkotob, Ashkan; Ghashami, Seyed Sajad

2016-09-01

In this paper, a novel methodology is proposed to solve a cooperative multi-depot vehicle routing problem. We establish a mathematical model for multi-owner VRP in which each owner (i.e. player) manages single or multiple depots. The basic idea consists of offering an option that owners cooperatively manage the VRP to save their costs. We present cooperative game theory techniques for cost saving allocations which are obtained from various coalitions of owners. The methodology is illustrated with a numerical example in which different coalitions of the players are evaluated along with the results of cooperation and cost saving allocation methods.

The veil of ignorance and health resource allocation.

PubMed

Soto, Carlos

2012-08-01

Some authors view the veil of ignorance as a preferred method for allocating resources because it imposes impartiality by stripping deliberators of knowledge of their personal identity. Using some prominent examples of such reasoning in the health care sector, I will argue for the following claims. First, choice behind a veil of ignorance often fails to provide clear guidance regarding resource allocation. Second, regardless of whether definite results could be derived from the veil, these results do not in themselves have important moral standing. This is partly because the veil does not determine which features are morally relevant for a given distributive problem. Third, even when we have settled the question of what features to count, choice behind a veil of ignorance arguably fails to take persons seriously. Ultimately, we do not need the veil to solve distributive problems, and we have good reason to appeal to some other distributive model.

A Decision Model for Supporting Task Allocation Processes in Global Software Development

NASA Astrophysics Data System (ADS)

Lamersdorf, Ansgar; Münch, Jürgen; Rombach, Dieter

Today, software-intensive systems are increasingly being developed in a globally distributed way. However, besides its benefit, global development also bears a set of risks and problems. One critical factor for successful project management of distributed software development is the allocation of tasks to sites, as this is assumed to have a major influence on the benefits and risks. We introduce a model that aims at improving management processes in globally distributed projects by giving decision support for task allocation that systematically regards multiple criteria. The criteria and causal relationships were identified in a literature study and refined in a qualitative interview study. The model uses existing approaches from distributed systems and statistical modeling. The article gives an overview of the problem and related work, introduces the empirical and theoretical foundations of the model, and shows the use of the model in an example scenario.

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

Mahault, Benoit Alexandre; Saxena, Avadh Behari; Nisoli, Cristiano

We introduce a minimal agent-based model to qualitatively conceptualize the allocation of limited wealth among more abundant opportunities. We study the interplay of power, satisfaction and frustration in the problem of wealth distribution, concentration, and inequality. This framework allows us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from, or lose wealth to, anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity, onlymore » minimally ameliorated by disorder in a non-optimized society. The picture is however dramatically modified when hard constraints are imposed over agents, and they are forced to share wealth with neighbors on a network. We discuss the case of random networks and scale free networks. We then propose an out of equilibrium dynamics of the networks, based on a competition of power and frustration in the decision-making of agents that leads to network evolution. We show that the ratio of power and frustration controls different dynamical regimes separated by kinetic transition and characterized by drastically different values of the indices of equality.« less

Establishing public health security in a postwar Iraq: constitutional obstacles and lessons for other federalizing states.

PubMed

Wilson, Kumanan; Fidler, David P; McDougall, Christopher W; Lazar, Harvey

2009-06-01

The public health consequences of the conflict in Iraq will likely continue after the violence has subsided. Reestablishing public health security will require large investments in infrastructure and the creation of effective systems of governance. On the question of governance, the allocation of powers in the new constitution of Iraq is critical. Given the ease with which public health threats cross borders, the constitution needs to grant to the federal government the legal authority to manage such threats and simultaneously meet international requirements. Unfortunately, the draft constitution does not accomplish this objective. If politically possible, the constitution should be amended to provide the federal government with this authority. If not possible, the Iraqi federal government would have two options. It could attempt to use alternative constitutional powers, such as national security powers. This option would be contentious and the results uncertain. Alternatively, the federal government could attempt to establish collaborative relationships with regional governments. Residual sectarian tensions create potential problems for this option, however. Reflecting on the Iraqi situation, we conclude that other federalizing countries emerging from conflict should ensure that their constitutions provide the federal government with the necessary authority to manage threats to public health security effectively.

Online Job Allocation with Hard Allocation Ratio Requirement (Author’s Manuscript)

DTIC Science & Technology

2016-04-14

where each job can only be served by a subset of servers. Such a problem exists in many emerging Internet services, such as YouTube , Netflix, etc. For...example, in the case of YouTube , each video is replicated only in a small number of servers, and each server can only serve a limited number of...streams simultaneously. When a user accesses YouTube and makes a request to watch a video, this request needs to be allocated to one of the servers that

The Allocation of Federal Expenditures Among States

NASA Technical Reports Server (NTRS)

Lee, Maw Lin

1967-01-01

This study explores factors associated with the allocation offederal expenditures by states and examines the implications of theseexpenditures on the state by state distribution of incomes. Theallocation of federal expenditures is functionally oriented toward theobjectives for which various government programs are set up. Thegeographical distribution of federal expenditures, therefore, washistorically considered to be a problem incidental to governmentactivity. Because of this, relatively little attention was given tothe question of why some states receive more federal allocation thanothers. In addition, the implications of this pattern of allocationamong the several states have not been intensively investigated.

There is no silver bullet: the value of diversification in planning invasive species surveillance

Treesearch

Denys Yemshanov; Frank H. Koch; Bo Lu; D. Barry Lyons; Jeffrey P. Prestemon; Taylor Scarr; Klaus Koehler

2014-01-01

In this study we demonstrate how the notion of diversification can be used in broad-scale resource allocation for surveillance of invasive species. We consider the problem of short-term surveillance for an invasive species in a geographical environment.Wefind the optimal allocation of surveillance resourcesamongmultiple geographical subdivisions via application of a...

Parallel Logic Programming Architecture

DTIC Science & Technology

1990-04-01

Section 3.1. 3.1. A STATIC ALLOCATION SCHEME (SAS) Methods that have been used for decomposing distributed problems in artificial intelligence...multiple agents, knowledge organization and allocation, and cooperative parallel execution. These difficulties are common to distributed artificial ...for the following reasons. First, intellegent backtracking requires much more bookkeeping and is therefore more costly during consult-time and during

Optimal allocation of invasive species surveillance with the maximum expected coverage concept

Treesearch

Denys Yemshanov; Robert G. Haight; Frank H. Koch; Bo Lu; Robert Venette; D. Barry Lyons; Taylor Scarr; Krista Ryall; Brian. Leung

2015-01-01

We address the problem of geographically allocating scarce survey resources to detect pests in their pathways of introduction given information about their likelihood of movement between origins and destinations. We introduce a model for selecting destination sites for survey that departs from the aim of reducing propagule pressure (PP) in pest destinations and instead...

Planning and management of cloud computing networks

NASA Astrophysics Data System (ADS)

Larumbe, Federico

The evolution of the Internet has a great impact on a big part of the population. People use it to communicate, query information, receive news, work, and as entertainment. Its extraordinary usefulness as a communication media made the number of applications and technological resources explode. However, that network expansion comes at the cost of an important power consumption. If the power consumption of telecommunication networks and data centers is considered as the power consumption of a country, it would rank at the 5 th place in the world. Furthermore, the number of servers in the world is expected to grow by a factor of 10 between 2013 and 2020. This context motivates us to study techniques and methods to allocate cloud computing resources in an optimal way with respect to cost, quality of service (QoS), power consumption, and environmental impact. The results we obtained from our test cases show that besides minimizing capital expenditures (CAPEX) and operational expenditures (OPEX), the response time can be reduced up to 6 times, power consumption by 30%, and CO2 emissions by a factor of 60. Cloud computing provides dynamic access to IT resources as a service. In this paradigm, programs are executed in servers connected to the Internet that users access from their computers and mobile devices. The first advantage of this architecture is to reduce the time of application deployment and interoperability, because a new user only needs a web browser and does not need to install software on local computers with specific operating systems. Second, applications and information are available from everywhere and with any device with an Internet access. Also, servers and IT resources can be dynamically allocated depending on the number of users and workload, a feature called elasticity. This thesis studies the resource management of cloud computing networks and is divided in three main stages. We start by analyzing the planning of cloud computing networks to get a comprehensive vision. The first question to be solved is what are the optimal data center locations. We found that the location of each data center has a big impact on cost, QoS, power consumption, and greenhouse gas emissions. An optimization problem with a multi-criteria objective function is proposed to decide jointly the optimal location of data centers and software components, link capacities, and information routing. Once the network planning has been analyzed, the problem of dynamic resource provisioning in real time is addressed. In this context, virtualization is a key technique in cloud computing because each server can be shared by multiple Virtual Machines (VMs) and the total power consumption can be reduced. In the same line of location problems, we propose a Green Cloud Broker that optimizes VM placement across multiple data centers. In fact, when multiple data centers are considered, response time can be reduced by placing VMs close to users, cost can be minimized, power consumption can be optimized by using energy efficient data centers, and CO2 emissions can be decreased by choosing data centers provided with renewable energy sources. The third stage of the analysis is the short-term management of a cloud data center. In particular, a method is proposed to assign VMs to servers by considering communication traffic among VMs. Cloud data centers receive new applications over time and these applications need on-demand resource provisioning. Each application is composed of multiple types of VMs that interact among themselves. A program called scheduler must place each new VM in a server and that impacts the QoS and power consumption. Our method places VMs that communicate among themselves in servers that are close to each other in the network topology, thus reducing communication delay and increasing the throughput available among VMs. Furthermore, the power consumption of each type of server is considered and the most efficient ones are chosen to place the VMs. The number of VMs of each application can be dynamically changed to match the workload and servers not needed in a particular period can be suspended to save energy. The methodology developed is based on Mixed Integer Programming (MIP) models to formalize the problems and use state of the art optimization solvers. Then, heuristics are developed to solve cases with more than 1,000 potential data center locations for the planning problem, 1,000 nodes for the cloud broker, and 128,000 servers for the VM placement problem. Solutions with very short optimality gaps, between 0% and 1.95%, are obtained, and execution time in the order of minutes for the planning problem and less than a second for real time cases. We consider that this thesis on resource provisioning of cloud computing networks includes important contributions on this research area, and innovative commercial applications based on the proposed methods have promising future.

Memory and Energy Optimization Strategies for Multithreaded Operating System on the Resource-Constrained Wireless Sensor Node

PubMed Central

Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Xu, Jun; Yang, Jianfeng; Zhou, Haiying; Shi, Hongling; Zhou, Peng

2015-01-01

Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN) nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS) LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes. PMID:25545264

Foundation for Problem-Based Gaming

ERIC Educational Resources Information Center

Kiili, Kristian

2007-01-01

Educational games may offer a viable strategy for developing students' problem-solving skills. However, the state of art of educational game research does not provide an account for that. Thus, the aim of this research is to develop an empirically allocated model about problem-based gaming that can be utilised to design pedagogically meaningful…

VHF command system study. [spectral analysis of GSFC VHF-PSK and VHF-FSK Command Systems

NASA Technical Reports Server (NTRS)

Gee, T. H.; Geist, J. M.

1973-01-01

Solutions are provided to specific problems arising in the GSFC VHF-PSK and VHF-FSK Command Systems in support of establishment and maintenance of Data Systems Standards. Signal structures which incorporate transmission on the uplink of a clock along with the PSK or FSK data are considered. Strategies are developed for allocating power between the clock and data, and spectral analyses are performed. Bit error probability and other probabilities pertinent to correct transmission of command messages are calculated. Biphase PCM/PM and PCM/FM are considered as candidate modulation techniques on the telemetry downlink, with application to command verification. Comparative performance of PCM/PM and PSK systems is given special attention, including implementation considerations. Gain in bit error performance due to coding is also considered.

Frequency allocations for a new satellite service - Digital audio broadcasting

NASA Technical Reports Server (NTRS)

Reinhart, Edward E.

1992-01-01

The allocation in the range 500-3000 MHz for digital audio broadcasting (DAB) is described in terms of key issues such as the transmission-system architectures. Attention is given to the optimal amount of spectrum for allocation and the technological considerations relevant to downlink bands for satellite and terrestrial transmissions. Proposals for DAB allocations are compared, and reference is made to factors impinging on the provision of ground/satellite feeder links. The allocation proposals describe the implementation of 50-60-MHz bandwidths for broadcasting in the ranges near 800 MHz, below 1525 MHz, near 2350 MHz, and near 2600 MHz. Three specific proposals are examined in terms of characteristics such as service areas, coverage/beam, channels/satellite beam, and FCC license status. Several existing problems are identified including existing services crowded with systems, the need for new bands in the 1000-3000-MHz range, and variations in the nature and intensity of implementations of existing allocations that vary from country to country.

Fair Resource Allocation to Health Research: Priority Topics for Bioethics Scholarship.

PubMed

Pratt, Bridget; Hyder, Adnan A

2017-07-01

This article draws attention to the limited amount of scholarship on what constitutes fairness and equity in resource allocation to health research by individual funders. It identifies three key decisions of ethical significance about resource allocation that research funders make regularly and calls for prioritizing scholarship on those topics - namely, how health resources should be fairly apportioned amongst public health and health care delivery versus health research, how health research resources should be fairly allocated between health problems experienced domestically versus other health problems typically experienced by disadvantaged populations outside the funder's country, and how domestic and non-domestic health research funding should be further apportioned to different areas, e.g. types of research and recipients. These three topics should be priorities for bioethics research because their outcomes have a substantial bearing on the achievement of health justice. The proposed agenda aims to move discussion on the ethics of health research funding beyond its current focus on the mismatch between worldwide basic and clinical research investment and the global burden of disease. Individual funders' decision-making on whether and to what extent to allocate resources to non-domestic health research, health systems research, research on the social determinants of health, capacity development, and recipients in certain countries should also be the focus of ethical scrutiny. © 2017 John Wiley & Sons Ltd.

Design for Warehouse with Product Flow Type Allocation using Linear Programming: A Case Study in a Textile Industry

NASA Astrophysics Data System (ADS)

Khannan, M. S. A.; Nafisah, L.; Palupi, D. L.

2018-03-01

Sari Warna Co. Ltd, a company engaged in the textile industry, is experiencing problems in the allocation and placement of goods in the warehouse. During this time the company has not implemented the product flow type allocation and product placement to the respective products resulting in a high total material handling cost. Therefore, this study aimed to determine the allocation and placement of goods in the warehouse corresponding to product flow type with minimal total material handling cost. This research is a quantitative research based on the theory of storage and warehouse that uses a mathematical model of optimization problem solving using mathematical optimization model approach belongs to Heragu (2005), aided by software LINGO 11.0 in the calculation of the optimization model. Results obtained from this study is the proportion of the distribution for each functional area is the area of cross-docking at 0.0734, the reserve area at 0.1894, and the forward area at 0.7372. The allocation of product flow type 1 is 5 products, the product flow type 2 is 9 products, the product flow type 3 is 2 products, and the product flow type 4 is 6 products. The optimal total material handling cost by using this mathematical model equal to Rp43.079.510 while it is equal to Rp 49.869.728 by using the company’s existing method. It saves Rp6.790.218 for the total material handling cost. Thus, all of the products can be allocated in accordance with the product flow type with minimal total material handling cost.

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

NASA Astrophysics Data System (ADS)

Panfil, Wawrzyniec; Moczulski, Wojciech

2017-10-01

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

47 CFR 2.815 - External radio frequency power amplifiers.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 1 2011-10-01 2011-10-01 false External radio frequency power amplifiers. 2.815 Section 2.815 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL FREQUENCY ALLOCATIONS AND RADIO TREATY MATTERS; GENERAL RULES AND REGULATIONS Marketing of Radio-frequency Devices § 2.815...

47 CFR 2.815 - External radio frequency power amplifiers.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 1 2010-10-01 2010-10-01 false External radio frequency power amplifiers. 2.815 Section 2.815 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL FREQUENCY ALLOCATIONS AND RADIO TREATY MATTERS; GENERAL RULES AND REGULATIONS Marketing of Radio-frequency Devices § 2.815...

Microwave Driven Actuators Power Allocation and Distribution

NASA Technical Reports Server (NTRS)

Forbes, Timothy; Song, Kyo D.

2000-01-01

Design, fabrication and test of a power allocation and distribution (PAD) network for microwave driven actuators is presented in this paper. Development of a circuit that would collect power from a rectenna array amplify and distribute the power to actuators was designed and fabricated for space application in an actuator array driven by a microwave. A P-SPICE model was constructed initially for data reduction purposes, and was followed by a working real-world model. A voltage up - converter (VUC) is used to amplify the voltage from the individual rectenna. The testing yielded a 26:1 voltage amplification ratio with input voltage at 9 volts and a measured output voltage 230VDC. Future work includes the miniaturization of the circuitry, the use of microwave remote control, and voltage amplification technology for each voltage source. The objective of this work is to develop a model system that will collect DC voltage from an array of rectenna and propagate the voltage to an array of actuators.

Neural Network Solves "Traveling-Salesman" Problem

NASA Technical Reports Server (NTRS)

Thakoor, Anilkumar P.; Moopenn, Alexander W.

1990-01-01

Experimental electronic neural network solves "traveling-salesman" problem. Plans round trip of minimum distance among N cities, visiting every city once and only once (without backtracking). This problem is paradigm of many problems of global optimization (e.g., routing or allocation of resources) occuring in industry, business, and government. Applied to large number of cities (or resources), circuits of this kind expected to solve problem faster and more cheaply.

Alpha-Fair Resource Allocation under Incomplete Information and Presence of a Jammer

NASA Astrophysics Data System (ADS)

Altman, Eitan; Avrachenkov, Konstantin; Garnaev, Andrey

In the present work we deal with the concept of alpha-fair resource allocation in the situation where the decision maker (in our case, the base station) does not have complete information about the environment. Namely, we develop a concept of α-fairness under uncertainty to allocate power resource in the presence of a jammer under two types of uncertainty: (a) the decision maker does not have complete knowledge about the parameters of the environment, but knows only their distribution, (b) the jammer can come into the environment with some probability bringing extra background noise. The goal of the decision maker is to maximize the α-fairness utility function with respect to the SNIR (signal to noise-plus-interference ratio). Here we consider a concept of the expected α-fairness utility function (short-term fairness) as well as fairness of expectation (long-term fairness). In the scenario with the unknown parameters of the environment the most adequate approach is a zero-sum game since it can also be viewed as a minimax problem for the decision maker playing against the nature where the decision maker has to apply the best allocation under the worst circumstances. In the scenario with the uncertainty about jamming being in the system the Nash equilibrium concept is employed since the agents have non-zero sum payoffs: the decision maker would like to maximize either the expected fairness or the fairness of expectation while the jammer would like to minimize the fairness if he comes in on the scene. For all the plots the equilibrium strategies in closed form are found. We have shown that for all the scenarios the equilibrium has to be constructed into two steps. In the first step the equilibrium jamming strategy has to be constructed based on a solution of the corresponding modification of the water-filling equation. In the second step the decision maker equilibrium strategy has to be constructed equalizing the induced by jammer background noise.

Energy Harvesting Based Body Area Networks for Smart Health.

PubMed

Hao, Yixue; Peng, Limei; Lu, Huimin; Hassan, Mohammad Mehedi; Alamri, Atif

2017-07-10

Body area networks (BANs) are configured with a great number of ultra-low power consumption wearable devices, which constantly monitor physiological signals of the human body and thus realize intelligent monitoring. However, the collection and transfer of human body signals consume energy, and considering the comfort demand of wearable devices, both the size and the capacity of a wearable device's battery are limited. Thus, minimizing the energy consumption of wearable devices and optimizing the BAN energy efficiency is still a challenging problem. Therefore, in this paper, we propose an energy harvesting-based BAN for smart health and discuss an optimal resource allocation scheme to improve BAN energy efficiency. Specifically, firstly, considering energy harvesting in a BAN and the time limits of human body signal transfer, we formulate the energy efficiency optimization problem of time division for wireless energy transfer and wireless information transfer. Secondly, we convert the optimization problem into a convex optimization problem under a linear constraint and propose a closed-form solution to the problem. Finally, simulation results proved that when the size of data acquired by the wearable devices is small, the proportion of energy consumed by the circuit and signal acquisition of the wearable devices is big, and when the size of data acquired by the wearable devices is big, the energy consumed by the signal transfer of the wearable device is decisive.

Energy Harvesting Based Body Area Networks for Smart Health

PubMed Central

Hao, Yixue; Peng, Limei; Alamri, Atif

2017-01-01

Body area networks (BANs) are configured with a great number of ultra-low power consumption wearable devices, which constantly monitor physiological signals of the human body and thus realize intelligent monitoring. However, the collection and transfer of human body signals consume energy, and considering the comfort demand of wearable devices, both the size and the capacity of a wearable device’s battery are limited. Thus, minimizing the energy consumption of wearable devices and optimizing the BAN energy efficiency is still a challenging problem. Therefore, in this paper, we propose an energy harvesting-based BAN for smart health and discuss an optimal resource allocation scheme to improve BAN energy efficiency. Specifically, firstly, considering energy harvesting in a BAN and the time limits of human body signal transfer, we formulate the energy efficiency optimization problem of time division for wireless energy transfer and wireless information transfer. Secondly, we convert the optimization problem into a convex optimization problem under a linear constraint and propose a closed-form solution to the problem. Finally, simulation results proved that when the size of data acquired by the wearable devices is small, the proportion of energy consumed by the circuit and signal acquisition of the wearable devices is big, and when the size of data acquired by the wearable devices is big, the energy consumed by the signal transfer of the wearable device is decisive. PMID:28698501

Shared and Disorder-Specific Prefrontal Abnormalities in Boys with Pure Attention-Deficit/Hyperactivity Disorder Compared to Boys with Pure CD during Interference Inhibition and Attention Allocation

ERIC Educational Resources Information Center

Rubia, Katya; Halari, Rozmin; Smith, Anna B.; Mohammad, Majeed; Scott, Stephen; Brammer, Michael J.

2009-01-01

Background: Inhibitory and attention deficits have been suggested to be shared problems of disruptive behaviour disorders. Patients with attention deficit hyperactivity disorder (ADHD) and patients with conduct disorder (CD) show deficits in tasks of attention allocation and interference inhibition. However, functional magnetic resonance imaging…

Nonprofit Decision Making and Resource Allocation: The Importance of Membership Preferences, Community Needs, and Interorganizational Ties.

ERIC Educational Resources Information Center

Markham, William T.; Johnson, Margaret A.; Bonjean, Charles M.

1999-01-01

Results of a study of community service organizations (n=12) and their communities indicate that distribution of volunteer funds and time was unrelated to community needs as measured by objective indicators. The most important determinants of resource allocation are members' perceptions of the severity of problems and their willingness to work in…

Auction Mechanism to Allocate Air Traffic Control Slots

NASA Technical Reports Server (NTRS)

Raffarin, Marianne

2003-01-01

This article deals with an auction mechanism for airspace slots, as a means of solving the European airspace congestion problem. A disequilibrium, between Air Traffic Control (ATC) services supply and ATC services demand are at the origin of almost one fourth of delays in the air transport industry in Europe. In order to tackle this congestion problem, we suggest modifying both pricing and allocation of ATC services, by setting up an auction mechanism. Objects of the auction will be the right for airlines to cross a part of the airspace, and then to benefit from ATC services over a period corresponding to the necessary time for the crossing. Allocation and payment rules have to be defined according to the objectives of this auction. The auctioneer is the public authority in charge of ATC services, whose aim is to obtain an efficient allocation. Therefore, the social value will be maximized. Another objective is to internalize congestion costs. To that end, we apply the principle of Clarke-Groves mechanism auction: each winner has to pay the externalities imposed on other bidders. The complex context of ATC leads to a specific design for this auction.

GIS and Game Theory for Water Resource Management

NASA Astrophysics Data System (ADS)

Ganjali, N.; Guney, C.

2017-11-01

In this study, aspects of Game theory and its application on water resources management combined with GIS techniques are detailed. First, each term is explained and the advantages and limitations of its aspect is discussed. Then, the nature of combinations between each pair and literature on the previous studies are given. Several cases were investigated and results were magnified in order to conclude with the applicability and combination of GIS- Game Theory- Water Resources Management. It is concluded that the game theory is used relatively in limited studies of water management fields such as cost/benefit allocation among users, water allocation among trans-boundary users in water resources, water quality management, groundwater management, analysis of water policies, fair allocation of water resources development cost and some other narrow fields. Also, 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. Most of the literature on water allocation and conflict problems uses traditional optimization models to identify the most efficient scheme while the Game Theory, as an optimization method, combined GIS are beneficial platforms for agent based models to be used in solving Water Resources Management problems in the further studies.

Application of a COTS Resource Optimization Framework to the SSN Sensor Tasking Domain - Part I: Problem Definition

NASA Astrophysics Data System (ADS)

Tran, T.

With the onset of the SmallSat era, the RSO catalog is expected to see continuing growth in the near future. This presents a significant challenge to the current sensor tasking of the SSN. The Air Force is in need of a sensor tasking system that is robust, efficient, scalable, and able to respond in real-time to interruptive events that can change the tracking requirements of the RSOs. Furthermore, the system must be capable of using processed data from heterogeneous sensors to improve tasking efficiency. The SSN sensor tasking can be regarded as an economic problem of supply and demand: the amount of tracking data needed by each RSO represents the demand side while the SSN sensor tasking represents the supply side. As the number of RSOs to be tracked grows, demand exceeds supply. The decision-maker is faced with the problem of how to allocate resources in the most efficient manner. Braxton recently developed a framework called Multi-Objective Resource Optimization using Genetic Algorithm (MOROUGA) as one of its modern COTS software products. This optimization framework took advantage of the maturing technology of evolutionary computation in the last 15 years. This framework was applied successfully to address the resource allocation of an AFSCN-like problem. In any resource allocation problem, there are five key elements: (1) the resource pool, (2) the tasks using the resources, (3) a set of constraints on the tasks and the resources, (4) the objective functions to be optimized, and (5) the demand levied on the resources. In this paper we explain in detail how the design features of this optimization framework are directly applicable to address the SSN sensor tasking domain. We also discuss our validation effort as well as present the result of the AFSCN resource allocation domain using a prototype based on this optimization framework.

Resource Allocation Algorithms for the Next Generation Cellular Networks

NASA Astrophysics Data System (ADS)

Amzallag, David; Raz, Danny

This chapter describes recent results addressing resource allocation problems in the context of current and future cellular technologies. We present models that capture several fundamental aspects of planning and operating these networks, and develop new approximation algorithms providing provable good solutions for the corresponding optimization problems. We mainly focus on two families of problems: cell planning and cell selection. Cell planning deals with choosing a network of base stations that can provide the required coverage of the service area with respect to the traffic requirements, available capacities, interference, and the desired QoS. Cell selection is the process of determining the cell(s) that provide service to each mobile station. Optimizing these processes is an important step towards maximizing the utilization of current and future cellular networks.

Who gets how much: funding formulas in federal public health programs.

PubMed

Buehler, James W; Holtgrave, David R

2007-01-01

Federal public health programs use a mix of formula-based and competitive methods to allocate funds among states and other constituent jurisdictions. Characteristics of formula-based allocations used by a convenience sample of four programs, three from the Centers for Disease Control and Prevention and one from the Health Resources and Services Administration, are described to illustrate formula-based allocation methods in public health. Data sources in these public health formulas include population counts and funding proportions based on historical precedent. None include factors that adjust allocations based on variations in the availability of local resources or the cost of delivering services. Formula-funded activities are supplemented by programs that target specific prevention needs or encourage development of innovative methods to address emerging problems, using set-aside funds. A public health finance research agenda should address ways to improve the fit between funding allocation formulas and program objectives.

77 FR 55834 - Notice of Opportunity To Comment on a Methodology for Allocating Greenhouse Gas Emissions to a...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-11

... ethanol plant in Spiritwood, North Dakota, with a nameplate production capacity of 65 million gallons of... factor for the power plant when it is just generating electricity and not diverting steam to the Dakota... from the turbine, and applying the power plant's ``power only'' emissions factor to that value. The...

Optimal traffic resource allocation and management.

DOT National Transportation Integrated Search

2010-05-01

"In this paper, we address the problem of determining the patrol routes of state troopers for maximum coverage of : highway spots with high frequencies of crashes (hot spots). We develop a mixed integer linear programming model : for this problem und...

18 CFR 284.10 - Rates.

Code of Federal Regulations, 2012 CFR

2012-04-01

... based on the average variable costs which are properly allocated to the service to which the rate... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Rates. 284.10 Section 284.10 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF...

18 CFR 284.10 - Rates.

Code of Federal Regulations, 2013 CFR

2013-04-01

... based on the average variable costs which are properly allocated to the service to which the rate... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Rates. 284.10 Section 284.10 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF...

18 CFR 284.10 - Rates.

Code of Federal Regulations, 2010 CFR

2010-04-01

... based on the average variable costs which are properly allocated to the service to which the rate... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Rates. 284.10 Section 284.10 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF...

18 CFR 284.10 - Rates.

Code of Federal Regulations, 2011 CFR

2011-04-01

... based on the average variable costs which are properly allocated to the service to which the rate... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Rates. 284.10 Section 284.10 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF...

18 CFR 284.10 - Rates.

Code of Federal Regulations, 2014 CFR

2014-04-01

... based on the average variable costs which are properly allocated to the service to which the rate... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Rates. 284.10 Section 284.10 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF...

Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines

PubMed Central

Zhang, Guang-Qian; Wang, Jian-Jun; Liu, Ya-Jing

2014-01-01

m unrelated parallel machines scheduling problems with variable job processing times are considered, where the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to determine the optimal resource allocation and the optimal schedule to minimize a total cost function that dependents on the total completion (waiting) time, the total machine load, the total absolute differences in completion (waiting) times on all machines, and total resource cost. If the number of machines is a given constant number, we propose a polynomial time algorithm to solve the problem. PMID:24982933

Dynamism in a Semiconductor Industrial Machine Allocation Problem using a Hybrid of the Bio-inspired and Musical-Harmony Approach

NASA Astrophysics Data System (ADS)

Kalsom Yusof, Umi; Nor Akmal Khalid, Mohd

2015-05-01

Semiconductor industries need to constantly adjust to the rapid pace of change in the market. Most manufactured products usually have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of the machine allocation plan known for its complexity. Various studies have been performed to balance productivity and flexibility in the flexible manufacturing system (FMS). Many approaches have been developed by the researchers to determine the suitable balance between exploration (global improvement) and exploitation (local improvement). However, not much work has been focused on the domain of machine allocation problem that considers the effects of machine breakdowns. This paper develops a model to minimize the effect of machine breakdowns, thus increasing the productivity. The objectives are to minimize system unbalance and makespan as well as increase throughput while satisfying the technological constraints such as machine time availability. To examine the effectiveness of the proposed model, results for throughput, system unbalance and makespan on real industrial datasets were performed with applications of intelligence techniques, that is, a hybrid of genetic algorithm and harmony search. The result aims to obtain a feasible solution to the domain problem.

A Bayesian adaptive design for biomarker trials with linked treatments

PubMed Central

Wason, James M S; Abraham, Jean E; Baird, Richard D; Gournaris, Ioannis; Vallier, Anne-Laure; Brenton, James D; Earl, Helena M; Mander, Adrian P

2015-01-01

Background: Response to treatments is highly heterogeneous in cancer. Increased availability of biomarkers and targeted treatments has led to the need for trial designs that efficiently test new treatments in biomarker-stratified patient subgroups. Methods: We propose a novel Bayesian adaptive randomisation (BAR) design for use in multi-arm phase II trials where biomarkers exist that are potentially predictive of a linked treatment's effect. The design is motivated in part by two phase II trials that are currently in development. The design starts by randomising patients to the control treatment or to experimental treatments that the biomarker profile suggests should be active. At interim analyses, data from treated patients are used to update the allocation probabilities. If the linked treatments are effective, the allocation remains high; if ineffective, the allocation changes over the course of the trial to unlinked treatments that are more effective. Results: Our proposed design has high power to detect treatment effects if the pairings of treatment with biomarker are correct, but also performs well when alternative pairings are true. The design is consistently more powerful than parallel-groups stratified trials. Conclusions: This BAR design is a powerful approach to use when there are pairings of biomarkers with treatments available for testing simultaneously. PMID:26263479

Space Station Freedom resource allocation accommodation of technology payload requirements

NASA Technical Reports Server (NTRS)

Avery, Don E.; Collier, Lisa D.; Gartrell, Charles F.

1990-01-01

An overview of the Office of Aeronautics, Exploration, and Technology (OAET) Space Station Freedom Technology Payload Development Program is provided, and the OAET Station resource requirements are reviewed. The requirements are contrasted with current proposed resource allocations. A discussion of the issues and conclusions are provided. It is concluded that an overall 20 percent resource allocation is appropriate to support OAET's technology development program, that some resources are inadequate even at the 20 percent level, and that bartering resources among U.S. users and international partners and increasing the level of automation may be viable solutions to the resource constraint problem.

Causes of Indoor Air Quality Problems in Schools: Summary of Scientific Research. Revised Edition.

ERIC Educational Resources Information Center

Bayer, Charlene W.; Crow, Sidney A.; Fischer, John

Understanding the primary causes of indoor air quality (IAQ) problems and how controllable factors--proper heating, ventilation and air-conditioning (HVAC) system design, allocation of adequate outdoor air, proper filtration, effective humidity control, and routine maintenance--can avert problems may help all building owners, operators, and…

Algorithm Optimally Allocates Actuation of a Spacecraft

NASA Technical Reports Server (NTRS)

Motaghedi, Shi

2007-01-01

A report presents an algorithm that solves the following problem: Allocate the force and/or torque to be exerted by each thruster and reaction-wheel assembly on a spacecraft for best performance, defined as minimizing the error between (1) the total force and torque commanded by the spacecraft control system and (2) the total of forces and torques actually exerted by all the thrusters and reaction wheels. The algorithm incorporates the matrix vector relationship between (1) the total applied force and torque and (2) the individual actuator force and torque values. It takes account of such constraints as lower and upper limits on the force or torque that can be applied by a given actuator. The algorithm divides the aforementioned problem into two optimization problems that it solves sequentially. These problems are of a type, known in the art as semi-definite programming problems, that involve linear matrix inequalities. The algorithm incorporates, as sub-algorithms, prior algorithms that solve such optimization problems very efficiently. The algorithm affords the additional advantage that the solution requires the minimum rate of consumption of fuel for the given best performance.

Optimizing conjunctive use of surface water and groundwater resources with stochastic dynamic programming

NASA Astrophysics Data System (ADS)

Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Rosbjerg, Dan; Bauer-Gottwein, Peter

2014-05-01

Optimal management of conjunctive use of surface water and groundwater has been attempted with different algorithms in the literature. In this study, a hydro-economic modelling approach to optimize conjunctive use of scarce surface water and groundwater resources under uncertainty is presented. A stochastic dynamic programming (SDP) approach is used to minimize the basin-wide total costs arising from water allocations and water curtailments. Dynamic allocation problems with inclusion of groundwater resources proved to be more complex to solve with SDP than pure surface water allocation problems due to head-dependent pumping costs. These dynamic pumping costs strongly affect the total costs and can lead to non-convexity of the future cost function. The water user groups (agriculture, industry, domestic) are characterized by inelastic demands and fixed water allocation and water supply curtailment costs. As in traditional SDP approaches, one step-ahead sub-problems are solved to find the optimal management at any time knowing the inflow scenario and reservoir/aquifer storage levels. These non-linear sub-problems are solved using a genetic algorithm (GA) that minimizes the sum of the immediate and future costs for given surface water reservoir and groundwater aquifer end storages. The immediate cost is found by solving a simple linear allocation sub-problem, and the future costs are assessed by interpolation in the total cost matrix from the following time step. Total costs for all stages, reservoir states, and inflow scenarios are used as future costs to drive a forward moving simulation under uncertain water availability. The use of a GA to solve the sub-problems is computationally more costly than a traditional SDP approach with linearly interpolated future costs. However, in a two-reservoir system the future cost function would have to be represented by a set of planes, and strict convexity in both the surface water and groundwater dimension cannot be maintained. The optimization framework based on the GA is still computationally feasible and represents a clean and customizable method. The method has been applied to the Ziya River basin, China. The basin is located on the North China Plain and is subject to severe water scarcity, which includes surface water droughts and groundwater over-pumping. The head-dependent groundwater pumping costs will enable assessment of the long-term effects of increased electricity prices on the groundwater pumping. The coupled optimization framework is used to assess realistic alternative development scenarios for the basin. In particular the potential for using electricity pricing policies to reach sustainable groundwater pumping is investigated.

An Energy-Aware Runtime Management of Multi-Core Sensory Swarms.

PubMed

Kim, Sungchan; Yang, Hoeseok

2017-08-24

In sensory swarms, minimizing energy consumption under performance constraint is one of the key objectives. One possible approach to this problem is to monitor application workload that is subject to change at runtime, and to adjust system configuration adaptively to satisfy the performance goal. As today's sensory swarms are usually implemented using multi-core processors with adjustable clock frequency, we propose to monitor the CPU workload periodically and adjust the task-to-core allocation or clock frequency in an energy-efficient way in response to the workload variations. In doing so, we present an online heuristic that determines the most energy-efficient adjustment that satisfies the performance requirement. The proposed method is based on a simple yet effective energy model that is built upon performance prediction using IPC (instructions per cycle) measured online and power equation derived empirically. The use of IPC accounts for memory intensities of a given workload, enabling the accurate prediction of execution time. Hence, the model allows us to rapidly and accurately estimate the effect of the two control knobs, clock frequency adjustment and core allocation. The experiments show that the proposed technique delivers considerable energy saving of up to 45%compared to the state-of-the-art multi-core energy management technique.

An Energy-Aware Runtime Management of Multi-Core Sensory Swarms

PubMed Central

Kim, Sungchan

2017-01-01

In sensory swarms, minimizing energy consumption under performance constraint is one of the key objectives. One possible approach to this problem is to monitor application workload that is subject to change at runtime, and to adjust system configuration adaptively to satisfy the performance goal. As today’s sensory swarms are usually implemented using multi-core processors with adjustable clock frequency, we propose to monitor the CPU workload periodically and adjust the task-to-core allocation or clock frequency in an energy-efficient way in response to the workload variations. In doing so, we present an online heuristic that determines the most energy-efficient adjustment that satisfies the performance requirement. The proposed method is based on a simple yet effective energy model that is built upon performance prediction using IPC (instructions per cycle) measured online and power equation derived empirically. The use of IPC accounts for memory intensities of a given workload, enabling the accurate prediction of execution time. Hence, the model allows us to rapidly and accurately estimate the effect of the two control knobs, clock frequency adjustment and core allocation. The experiments show that the proposed technique delivers considerable energy saving of up to 45%compared to the state-of-the-art multi-core energy management technique. PMID:28837094

Effects of a Meditation Program on Nurses' Power and Quality of Life.

PubMed

Chang, Sun Ju; Kwak, Eun Young; Hahm, Bong-Jin; Seo, Se Hee; Lee, Da Woon; Jang, Sun Joo

2016-07-01

This study evaluated the effects of meditation programs on nurses' power and quality of life. In this study, Barrett's power theory derived from Rogers' unitary human being science was used as a theoretical framework. A randomized controlled design with 50 recruited and randomly allocated participants was used. The results demonstrated that the eight-week meditation program significantly improved nurses' power and quality of life. These results suggest that meditation has positive effects on power and quality of life. © The Author(s) 2016.

CARBON AND NITROGEN ALLOCATION MODEL FOR THE SEAGRASS THALASSIA TESTUDUNUM IN LOWER LAGUNA MADRE

EPA Science Inventory

Inverse modeling methods are a powerful tool for understanding complex physiological relationships between seagrasses and their environment. The power of the method is a result of using ranges of data in a system of constraints to describe the biological system, in this case, t...

Enhancements and Algorithms for Avionic Information Processing System Design Methodology.

DTIC Science & Technology

1982-06-16

programming algorithm is enhanced by incorporating task precedence constraints and hardware failures. Stochastic network methods are used to analyze...allocations in the presence of random fluctuations. Graph theoretic methods are used to analyze hardware designs, and new designs are constructed with...There, spatial dynamic programming (SDP) was used to solve a static, deterministic software allocation problem. Under the current contract the SDP

A review of alternative approaches to healthcare resource allocation.

PubMed

Petrou, S; Wolstenholme, J

2000-07-01

The resources available for healthcare are limited compared with demand, if not need, and all healthcare systems, regardless of their financing and organisation, employ mechanisms to ration or prioritise finite healthcare resources. This paper reviews alternative approaches that can be used to allocate healthcare resources. It discusses the problems encountered when allocating healthcare resources according to free market principles. It then proceeds to discuss the advantages and disadvantages of alternative resource allocation approaches that can be applied to public health systems. These include: (i) approaches based on the concept of meeting the needs of the population to maximising its capacity to benefit from interventions; (ii) economic approaches that identify the most efficient allocation of resources with the view of maximising health benefits or other measures of social welfare; (iii) approaches that seek to ration healthcare by age; and (iv) approaches that resolve resource allocation disputes through debate and bargaining. At present, there appears to be no consensus about the relative importance of the potentially conflicting principles that can be used to guide resource allocation decisions. It is concluded that whatever shape tomorrow's health service takes, the requirement to make equitable and efficient use of finite healthcare resources will remain.

Allocating responsibility for environmental risks: A comparative analysis of examples from water governance.

PubMed

Doorn, Neelke

2017-03-01

The focus of the present study is on the allocation of responsibilities for addressing environmental risks in transboundary water governance. Effective environmental management in transboundary situations requires coordinated and cooperative action among diverse individuals and organizations. Currently, little insight exists on how to foster collective action such that individuals and organizations take the responsibility to address transboundary environmental risks. On the basis of 4 cases of transboundary water governance, it will be shown how certain allocation principles are more likely to encourage cooperative action. The main lesson from these case studies is that the allocation of responsibilities should be seen as a risk distribution problem, including considerations of effectiveness, efficiency, and fairness. Integr Environ Assess Manag 2017;13:371-375. © 2016 SETAC. © 2016 SETAC.

Optimal Resource Allocation under Fair QoS in Multi-tier Server Systems

NASA Astrophysics Data System (ADS)

Akai, Hirokazu; Ushio, Toshimitsu; Hayashi, Naoki

Recent development of network technology realizes multi-tier server systems, where several tiers perform functionally different processing requested by clients. It is an important issue to allocate resources of the systems to clients dynamically based on their current requests. On the other hand, Q-RAM has been proposed for resource allocation in real-time systems. In the server systems, it is important that execution results of all applications requested by clients are the same QoS(quality of service) level. In this paper, we extend Q-RAM to multi-tier server systems and propose a method for optimal resource allocation with fairness of the QoS levels of clients’ requests. We also consider an assignment problem of physical machines to be sleep in each tier sothat the energy consumption is minimized.

Community-aware task allocation for social networked multiagent systems.

PubMed

Wang, Wanyuan; Jiang, Yichuan

2014-09-01

In this paper, we propose a novel community-aware task allocation model for social networked multiagent systems (SN-MASs), where the agent' cooperation domain is constrained in community and each agent can negotiate only with its intracommunity member agents. Under such community-aware scenarios, we prove that it remains NP-hard to maximize system overall profit. To solve this problem effectively, we present a heuristic algorithm that is composed of three phases: 1) task selection: select the desirable task to be allocated preferentially; 2) allocation to community: allocate the selected task to communities based on a significant task-first heuristics; and 3) allocation to agent: negotiate resources for the selected task based on a nonoverlap agent-first and breadth-first resource negotiation mechanism. Through the theoretical analyses and experiments, the advantages of our presented heuristic algorithm and community-aware task allocation model are validated. 1) Our presented heuristic algorithm performs very closely to the benchmark exponential brute-force optimal algorithm and the network flow-based greedy algorithm in terms of system overall profit in small-scale applications. Moreover, in the large-scale applications, the presented heuristic algorithm achieves approximately the same overall system profit, but significantly reduces the computational load compared with the greedy algorithm. 2) Our presented community-aware task allocation model reduces the system communication cost compared with the previous global-aware task allocation model and improves the system overall profit greatly compared with the previous local neighbor-aware task allocation model.

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.

Methodologies for optimal resource allocation to the national space program and new space utilizations. Volume 1: Technical description

NASA Technical Reports Server (NTRS)

1971-01-01

The optimal allocation of resources to the national space program over an extended time period requires the solution of a large combinatorial problem in which the program elements are interdependent. The computer model uses an accelerated search technique to solve this problem. The model contains a large number of options selectable by the user to provide flexible input and a broad range of output for use in sensitivity analyses of all entering elements. Examples of these options are budget smoothing under varied appropriation levels, entry of inflation and discount effects, and probabilistic output which provides quantified degrees of certainty that program costs will remain within planned budget. Criteria and related analytic procedures were established for identifying potential new space program directions. Used in combination with the optimal resource allocation model, new space applications can be analyzed in realistic perspective, including the advantage gain from existing space program plant and on-going programs such as the space transportation system.

Studies in integrated line-and packet-switched computer communication systems

NASA Astrophysics Data System (ADS)

Maglaris, B. S.

1980-06-01

The problem of efficiently allocating the bandwidth of a trunk to both types of traffic is handled for various system and traffic models. A performance analysis is carried out both for variable and fixed frame schemes. It is shown that variable frame schemes, adjusting the frame length according to the traffic variations, offer better trunk utilization at the cost of the additional hardware and software complexity needed because of the lack of synchronization. An optimization study on the fixed frame schemes follows. The problem of dynamically allocating the fixed frame to both types of traffic is formulated as a Markovian Decision process. It is shown that the movable boundary scheme, suggested for commercial implementations of integrated multiplexors, offers optimal or near optimal performance and simplicity of implementation. Finally, the behavior of the movable boundary integrated scheme is studied for tandem link connections. Under the assumptions made for the line-switched traffic, the forward allocation technique is found to offer the best alternative among different path set-up strategies.

A supplier selection and order allocation problem with stochastic demands

NASA Astrophysics Data System (ADS)

Zhou, Yun; Zhao, Lei; Zhao, Xiaobo; Jiang, Jianhua

2011-08-01

We consider a system comprising a retailer and a set of candidate suppliers that operates within a finite planning horizon of multiple periods. The retailer replenishes its inventory from the suppliers and satisfies stochastic customer demands. At the beginning of each period, the retailer makes decisions on the replenishment quantity, supplier selection and order allocation among the selected suppliers. An optimisation problem is formulated to minimise the total expected system cost, which includes an outer level stochastic dynamic program for the optimal replenishment quantity and an inner level integer program for supplier selection and order allocation with a given replenishment quantity. For the inner level subproblem, we develop a polynomial algorithm to obtain optimal decisions. For the outer level subproblem, we propose an efficient heuristic for the system with integer-valued inventory, based on the structural properties of the system with real-valued inventory. We investigate the efficiency of the proposed solution approach, as well as the impact of parameters on the optimal replenishment decision with numerical experiments.

Risk-Based Sampling: I Don't Want to Weight in Vain.

PubMed

Powell, Mark R

2015-12-01

Recently, there has been considerable interest in developing risk-based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk-based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz (1952) laid the foundation for modern portfolio theory based on mean-variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false "optimal" portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out-of-sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk-based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers. © 2015 Society for Risk Analysis.

On the Fair Division of Multiple Stochastic Pies to Multiple Agents within the Nash Bargaining Solution

PubMed Central

Karmperis, Athanasios C.; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios

2012-01-01

The fair division of a surplus is one of the most widely examined problems. This paper focuses on bargaining problems with fixed disagreement payoffs where risk-neutral agents have reached an agreement that is the Nash-bargaining solution (NBS). We consider a stochastic environment, in which the overall return consists of multiple pies with uncertain sizes and we examine how these pies can be allocated with fairness among agents. Specifically, fairness is based on the Aristotle’s maxim: “equals should be treated equally and unequals unequally, in proportion to the relevant inequality”. In this context, fairness is achieved when all the individual stochastic surplus shares which are allocated to agents are distributed in proportion to the NBS. We introduce a novel algorithm, which can be used to compute the ratio of each pie that should be allocated to each agent, in order to ensure fairness within a symmetric or asymmetric NBS. PMID:23024752

System of systems design: Evaluating aircraft in a fleet context using reliability and non-deterministic approaches

NASA Astrophysics Data System (ADS)

Frommer, Joshua B.

This work develops and implements a solution framework that allows for an integrated solution to a resource allocation system-of-systems problem associated with designing vehicles for integration into an existing fleet to extend that fleet's capability while improving efficiency. Typically, aircraft design focuses on using a specific design mission while a fleet perspective would provide a broader capability. Aspects of design for both the vehicles and missions may be, for simplicity, deterministic in nature or, in a model that reflects actual conditions, uncertain. Toward this end, the set of tasks or goals for the to-be-planned system-of-systems will be modeled more accurately with non-deterministic values, and the designed platforms will be evaluated using reliability analysis. The reliability, defined as the probability of a platform or set of platforms to complete possible missions, will contribute to the fitness of the overall system. The framework includes building surrogate models for metrics such as capability and cost, and includes the ideas of reliability in the overall system-level design space. The concurrent design and allocation system-of-systems problem is a multi-objective mixed integer nonlinear programming (MINLP) problem. This study considered two system-of-systems problems that seek to simultaneously design new aircraft and allocate these aircraft into a fleet to provide a desired capability. The Coast Guard's Integrated Deepwater System program inspired the first problem, which consists of a suite of search-and-find missions for aircraft based on descriptions from the National Search and Rescue Manual. The second represents suppression of enemy air defense operations similar to those carried out by the U.S. Air Force, proposed as part of the Department of Defense Network Centric Warfare structure, and depicted in MILSTD-3013. The two problems seem similar, with long surveillance segments, but because of the complex nature of aircraft design, the analysis of the vehicle for high-speed attack combined with a long loiter period is considerably different from that for quick cruise to an area combined with a low speed search. However, the framework developed to solve this class of system-of-systems problem handles both scenarios and leads to a solution type for this kind of problem. On the vehicle-level of the problem, different technology can have an impact on the fleet-level. One such technology is Morphing, the ability to change shape, which is an ideal candidate technology for missions with dissimilar segments, such as the aforementioned two. A framework, using surrogate models based on optimally-sized aircraft, and using probabilistic parameters to define a concept of operations, is investigated; this has provided insight into the setup of the optimization problem, the use of the reliability metric, and the measurement of fleet level impacts of morphing aircraft. The research consisted of four phases. The two initial phases built and defined the framework to solve system-of-systems problem; these investigations used the search-and-find scenario as the example application. The first phase included the design of fixed-geometry and morphing aircraft for a range of missions and evaluated the aircraft capability using non-deterministic mission parameters. The second phase introduced the idea of multiple aircraft in a fleet, but only considered a fleet consisting of one aircraft type. The third phase incorporated the simultaneous design of a new vehicle and allocation into a fleet for the search-and-find scenario; in this phase, multiple types of aircraft are considered. The fourth phase repeated the simultaneous new aircraft design and fleet allocation for the SEAD scenario to show that the approach is not specific to the search-and-find scenario. The framework presented in this work appears to be a viable approach for concurrently designing and allocating constituents in a system, specifically aircraft in a fleet. The research also shows that new technology impact can be assessed at the fleet level using conceptual design principles.

Power Management in Regenerative Life Support Systems

NASA Technical Reports Server (NTRS)

Crawford, Sekou; Pawlowski, Christopher; Finn, Cory; Mead, Susan C. (Technical Monitor)

1999-01-01

Effective management of power can reduce the cost of launch and operation of regenerative life support systems. Variations in power may be quite severe and may manifest as surges or spikes, While the power plant may have some ability to deal with these variations, with batteries for example, over-capacity is expensive and does nothing to address the fundamental issue of excessive demand. Because the power unit must be sized to accommodate the largest demand, avoiding power spikes has the potential to reduce the required size of the power plant while at the same time increasing the dependability of the system. Scheduling of processors can help to reduce potential power spikes. However, not all power-consuming equipment is easily scheduled. Therefore, active power management is needed to further decrease the risk of surges or spikes. We investigate the use of a hierarchical scheme to actively manage power for a model of a regenerative life support system. Local level controllers individually determine subsystem power usage. A higher level controller monitors overall system power and detects surges or spikes. When a surge condition is detected, the higher level controller conducts an 'auction' and describes subsystem power usage to re-allocate power. The result is an overall reduction in total power during a power surge. The auction involves each subsystem making a 'bid' to buy or sell power based on local needs. However, this re-allocation cannot come at the expense of life support function. To this end, participation in the auction is restricted to those processes meeting certain tolerance constraints. These tolerances represent acceptable limits within which system processes can be operated. We present a simulation model and discuss some of our results.

Electricity production from municipal solid waste using microbial fuel cells.

PubMed

Chiu, H Y; Pai, T Y; Liu, M H; Chang, C A; Lo, F C; Chang, T C; Lo, H M; Chiang, C F; Chao, K P; Lo, W Y; Lo, S W; Chu, Y L

2016-07-01

The organic content of municipal solid waste has long been an attractive source of renewable energy, mainly as a solid fuel in waste-to-energy plants. This study focuses on the potential to use microbial fuel cells to convert municipal solid waste organics into energy using various operational conditions. The results showed that two-chamber microbial fuel cells with carbon felt and carbon felt allocation had a higher maximal power density (20.12 and 30.47 mW m(-2) for 1.5 and 4 L, respectively) than those of other electrode plate allocations. Most two-chamber microbial fuel cells (1.5 and 4 L) had a higher maximal power density than single-chamber ones with corresponding electrode plate allocations. Municipal solid waste with alkali hydrolysis pre-treatment and K3Fe(CN)6 as an electron acceptor improved the maximal power density to 1817.88 mW m(-2) (~0.49% coulomb efficiency, from 0.05-0.49%). The maximal power density from experiments using individual 1.5 and 4 L two-chamber microbial fuel cells, and serial and parallel connections of 1.5 and 4 L two-chamber microbial fuel cells, was found to be in the order of individual 4 L (30.47 mW m(-2)) > serial connection of 1.5 and 4 L (27.75) > individual 1.5 L (20.12) > parallel connection of 1.5 and 4 L (17.04) two-chamber microbial fuel cells . The power density using municipal solid waste microbial fuel cells was compared with information in the literature and discussed. © The Author(s) 2016.

Noninferiority trial designs for odds ratios and risk differences.

PubMed

Hilton, Joan F

2010-04-30

This study presents constrained maximum likelihood derivations of the design parameters of noninferiority trials for binary outcomes with the margin defined on the odds ratio (ψ) or risk-difference (δ) scale. The derivations show that, for trials in which the group-specific response rates are equal under the point-alternative hypothesis, the common response rate, π(N), is a fixed design parameter whose value lies between the control and experimental rates hypothesized at the point-null, {π(C), π(E)}. We show that setting π(N) equal to the value of π(C) that holds under H(0) underestimates the overall sample size requirement. Given {π(C), ψ} or {π(C), δ} and the type I and II error rates, or algorithm finds clinically meaningful design values of π(N), and the corresponding minimum asymptotic sample size, N=n(E)+n(C), and optimal allocation ratio, γ=n(E)/n(C). We find that optimal allocations are increasingly imbalanced as ψ increases, with γ(ψ)<1 and γ(δ)≈1/γ(ψ), and that ranges of allocation ratios map to the minimum sample size. The latter characteristic allows trialists to consider trade-offs between optimal allocation at a smaller N and a preferred allocation at a larger N. For designs with relatively large margins (e.g. ψ>2.5), trial results that are presented on both scales will differ in power, with more power lost if the study is designed on the risk-difference scale and reported on the odds ratio scale than vice versa. 2010 John Wiley & Sons, Ltd.

Attention is allocated closely ahead of the target during smooth pursuit eye movements: Evidence from EEG frequency tagging.

PubMed

Chen, Jing; Valsecchi, Matteo; Gegenfurtner, Karl R

2017-07-28

It is under debate whether attention during smooth pursuit is centered right on the pursuit target or allocated preferentially ahead of it. Attentional deployment was previously probed using a secondary task, which might have altered attention allocation and led to inconsistent findings. We measured frequency-tagged steady-state visual evoked potentials (SSVEP) to measure attention allocation in the absence of any secondary probing task. The observers pursued a moving dot while stimuli flickering at different frequencies were presented at various locations ahead or behind the pursuit target. We observed a significant increase in EEG power at the flicker frequency of the stimulus in front of the pursuit target, compared to the frequency of the stimulus behind. When testing many different locations, we found that the enhancement was detectable up to about 1.5° ahead during pursuit, but vanished by 3.5°. In a control condition using attentional cueing during fixation, we did observe an enhanced EEG response to stimuli at this eccentricity, indicating that the focus of attention during pursuit is narrower than allowed for by the resolution of the attentional system. In a third experiment, we ruled out the possibility that the SSVEP enhancement was a byproduct of the catch-up saccades occurring during pursuit. Overall, we showed that attention is on average allocated ahead of the pursuit target during smooth pursuit. EEG frequency tagging seems to be a powerful technique that allows for the investigation of attention/perception implicitly when an overt task would be confounding. Copyright © 2017 Elsevier Ltd. All rights reserved.

Function Allocation in Complex Socio-Technical Systems: Procedure usage in nuclear power and the Context Analysis Method for Identifying Design Solutions (CAMIDS) Model

NASA Astrophysics Data System (ADS)

Schmitt, Kara Anne

This research aims to prove that strict adherence to procedures and rigid compliance to process in the US Nuclear Industry may not prevent incidents or increase safety. According to the Institute of Nuclear Power Operations, the nuclear power industry has seen a recent rise in events, and this research claims that a contributing factor to this rise is organizational, cultural, and based on peoples overreliance on procedures and policy. Understanding the proper balance of function allocation, automation and human decision-making is imperative to creating a nuclear power plant that is safe, efficient, and reliable. This research claims that new generations of operators are less engaged and thinking because they have been instructed to follow procedures to a fault. According to operators, they were once to know the plant and its interrelations, but organizationally more importance is now put on following procedure and policy. Literature reviews were performed, experts were questioned, and a model for context analysis was developed. The Context Analysis Method for Identifying Design Solutions (CAMIDS) Model was created, verified and validated through both peer review and application in real world scenarios in active nuclear power plant simulators. These experiments supported the claim that strict adherence and rigid compliance to procedures may not increase safety by studying the industry's propensity for following incorrect procedures, and when it directly affects the outcome of safety or security of the plant. The findings of this research indicate that the younger generations of operators rely highly on procedures, and the organizational pressures of required compliance to procedures may lead to incidents within the plant because operators feel pressured into following the rules and policy above performing the correct actions in a timely manner. The findings support computer based procedures, efficient alarm systems, and skill of the craft matrices. The solution to the problems facing the industry include in-depth, multiple fault failure training which tests the operator's knowledge of the situation. This builds operator collaboration, competence and confidence to know what to do, and when to do it in response to an emergency situation. Strict adherence to procedures and rigid compliance to process may not prevent incidents or increase safety; building operators' fundamental skills of collaboration, competence and confidence will.

Multi-objective reverse logistics model for integrated computer waste management.

PubMed

Ahluwalia, Poonam Khanijo; Nema, Arvind K

2006-12-01

This study aimed to address the issues involved in the planning and design of a computer waste management system in an integrated manner. A decision-support tool is presented for selecting an optimum configuration of computer waste management facilities (segregation, storage, treatment/processing, reuse/recycle and disposal) and allocation of waste to these facilities. The model is based on an integer linear programming method with the objectives of minimizing environmental risk as well as cost. The issue of uncertainty in the estimated waste quantities from multiple sources is addressed using the Monte Carlo simulation technique. An illustrated example of computer waste management in Delhi, India is presented to demonstrate the usefulness of the proposed model and to study tradeoffs between cost and risk. The results of the example problem show that it is possible to reduce the environmental risk significantly by a marginal increase in the available cost. The proposed model can serve as a powerful tool to address the environmental problems associated with exponentially growing quantities of computer waste which are presently being managed using rudimentary methods of reuse, recovery and disposal by various small-scale vendors.

Assessment of environmental policy implementation in solid waste management in Kathmandu, Nepal.

PubMed

Dangi, Mohan B; Schoenberger, Erica; Boland, John J

2017-06-01

In Nepal, full-fledged environmental legislation was rare before the democratic constitution of 1990. The first law covering the environment and sustainability was the Environment Protection Act 1997. While the Solid Waste Act was introduced in 1987, the problem of solid waste management still surfaces in Kathmandu. In order to understand the bedrock of this unrelenting failure in solid waste management, the manuscript digs deeper into policy implementation by dissecting solid waste rules, environmental legislations, relevant local laws, and solid waste management practices in Kathmandu, Nepal. A very rich field study that included surveys, interviews, site visits, and literature review provided the basis for the article. The study shows that volumes of new Nepalese rules are crafted without effective enforcement of their predecessors and there is a frequent power struggle between local government bodies and central authority in implementing the codes and allocating resources in solid waste management. The study concludes that Kathmandu does not require any new instrument to address solid waste problems; instead, it needs creation of local resources, execution of local codes, and commitment from central government to allow free exercise of these policies.

Optimal Time-Resource Allocation for Energy-Efficient Physical Activity Detection

PubMed Central

Thatte, Gautam; Li, Ming; Lee, Sangwon; Emken, B. Adar; Annavaram, Murali; Narayanan, Shrikanth; Spruijt-Metz, Donna; Mitra, Urbashi

2011-01-01

The optimal allocation of samples for physical activity detection in a wireless body area network for health-monitoring is considered. The number of biometric samples collected at the mobile device fusion center, from both device-internal and external Bluetooth heterogeneous sensors, is optimized to minimize the transmission power for a fixed number of samples, and to meet a performance requirement defined using the probability of misclassification between multiple hypotheses. A filter-based feature selection method determines an optimal feature set for classification, and a correlated Gaussian model is considered. Using experimental data from overweight adolescent subjects, it is found that allocating a greater proportion of samples to sensors which better discriminate between certain activity levels can result in either a lower probability of error or energy-savings ranging from 18% to 22%, in comparison to equal allocation of samples. The current activity of the subjects and the performance requirements do not significantly affect the optimal allocation, but employing personalized models results in improved energy-efficiency. As the number of samples is an integer, an exhaustive search to determine the optimal allocation is typical, but computationally expensive. To this end, an alternate, continuous-valued vector optimization is derived which yields approximately optimal allocations and can be implemented on the mobile fusion center due to its significantly lower complexity. PMID:21796237

A hybrid method for provincial scale energy-related carbon emission allocation in China.

PubMed

Bai, Hongtao; Zhang, Yingxuan; Wang, Huizhi; Huang, Yanying; Xu, He

2014-01-01

Achievement of carbon emission reduction targets proposed by national governments relies on provincial/state allocations. In this study, a hybrid method for provincial energy-related carbon emissions allocation in China was developed to provide a good balance between production- and consumption-based approaches. In this method, provincial energy-related carbon emissions are decomposed into direct emissions of local activities other than thermal power generation and indirect emissions as a result of electricity consumption. Based on the carbon reduction efficiency principle, the responsibility for embodied emissions of provincial product transactions is assigned entirely to the production area. The responsibility for carbon generation during the production of thermal power is borne by the electricity consumption area, which ensures that different regions with resource endowments have rational development space. Empirical studies were conducted to examine the hybrid method and three indices, per capita GDP, resource endowment index and the proportion of energy-intensive industries, were screened to preliminarily interpret the differences among China's regional carbon emissions. Uncertainty analysis and a discussion of this method are also provided herein.

A decision modeling for phasor measurement unit location selection in smart grid systems

NASA Astrophysics Data System (ADS)

Lee, Seung Yup

As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed.

Dynamic programming methods for concurrent design and dynamic allocation of vehicles embedded in a system-of-systems

NASA Astrophysics Data System (ADS)

Nusawardhana

2007-12-01

Recent developments indicate a changing perspective on how systems or vehicles should be designed. Such transition comes from the way decision makers in defense related agencies address complex problems. Complex problems are now often posed in terms of the capabilities desired, rather than in terms of requirements for a single systems. As a result, the way to provide a set of capabilities is through a collection of several individual, independent systems. This collection of individual independent systems is often referred to as a "System of Systems'' (SoS). Because of the independent nature of the constituent systems in an SoS, approaches to design an SoS, and more specifically, approaches to design a new system as a member of an SoS, will likely be different than the traditional design approaches for complex, monolithic (meaning the constituent parts have no ability for independent operation) systems. Because a system of system evolves over time, this simultaneous system design and resource allocation problem should be investigated in a dynamic context. Such dynamic optimization problems are similar to conventional control problems. However, this research considers problems which not only seek optimizing policies but also seek the proper system or vehicle to operate under these policies. This thesis presents a framework and a set of analytical tools to solve a class of SoS problems that involves the simultaneous design of a new system and allocation of the new system along with existing systems. Such a class of problems belongs to the problems of concurrent design and control of a new systems with solutions consisting of both optimal system design and optimal control strategy. Rigorous mathematical arguments show that the proposed framework solves the concurrent design and control problems. Many results exist for dynamic optimization problems of linear systems. In contrary, results on optimal nonlinear dynamic optimization problems are rare. The proposed framework is equipped with the set of analytical tools to solve several cases of nonlinear optimal control problems: continuous- and discrete-time nonlinear problems with applications on both optimal regulation and tracking. These tools are useful when mathematical descriptions of dynamic systems are available. In the absence of such a mathematical model, it is often necessary to derive a solution based on computer simulation. For this case, a set of parameterized decision may constitute a solution. This thesis presents a method to adjust these parameters based on the principle of stochastic approximation simultaneous perturbation using continuous measurements. The set of tools developed here mostly employs the methods of exact dynamic programming. However, due to the complexity of SoS problems, this research also develops suboptimal solution approaches, collectively recognized as approximate dynamic programming solutions, for large scale problems. The thesis presents, explores, and solves problems from an airline industry, in which a new aircraft is to be designed and allocated along with an existing fleet of aircraft. Because the life cycle of an aircraft is on the order of 10 to 20 years, this problem is to be addressed dynamically so that the new aircraft design is the best design for the fleet over a given time horizon.

Study on the optimization allocation of wind-solar in power system based on multi-region production simulation

NASA Astrophysics Data System (ADS)

Xu, Zhicheng; Yuan, Bo; Zhang, Fuqiang

2018-06-01

In this paper, a power supply optimization model is proposed. The model takes the minimum fossil energy consumption as the target, considering the output characteristics of the conventional power supply and the renewable power supply. The optimal capacity ratio of wind-solar in the power supply under various constraints is calculated, and the interrelation between conventional power supply and renewable energy is analyzed in the system of high proportion renewable energy integration. Using the model, we can provide scientific guidance for the coordinated and orderly development of renewable energy and conventional power sources.

Model for the design of distributed data bases

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

Ram, S.

This research focuses on developing a model to solve the File Allocation Problem (FAP). The model integrates two major design issues, namely Concurrently Control and Data Distribution. The central node locking mechanism is incorporated in developing a nonlinear integer programming model. Two solution algorithms are proposed, one of which was implemented in FORTRAN.V. The allocation of data bases and programs are examined using this heuristic. Several decision rules were also formulated based on the results of the heuristic. A second more comprehensive heuristic was proposed, based on the knapsack problem. The development and implementation of this algorithm has been leftmore » as a topic for future research.« less

A Survey of the Problem of Unbalanced High School Educational Resource Allocation within the County Region in Gansu Province--Using Seven High Schools in Three Counties as an Example

ERIC Educational Resources Information Center

Kai, Liu; Gaofu, Du

2015-01-01

The imbalance in allocating high school educational resources within the county region has expanded the imbalances in local high school educational development. This has caused "diseconomies of scale" in high schools, aggravated the "expansion impulse" in building model high schools, limited the growth of effective demand by…

Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth

PubMed Central

Knoop, Henning; Bockmayr, Alexander; Steuer, Ralf

2017-01-01

Cyanobacteria are an integral part of Earth’s biogeochemical cycles and a promising resource for the synthesis of renewable bioproducts from atmospheric CO2. Growth and metabolism of cyanobacteria are inherently tied to the diurnal rhythm of light availability. As yet, however, insight into the stoichiometric and energetic constraints of cyanobacterial diurnal growth is limited. Here, we develop a computational framework to investigate the optimal allocation of cellular resources during diurnal phototrophic growth using a genome-scale metabolic reconstruction of the cyanobacterium Synechococcus elongatus PCC 7942. We formulate phototrophic growth as an autocatalytic process and solve the resulting time-dependent resource allocation problem using constraint-based analysis. Based on a narrow and well-defined set of parameters, our approach results in an ab initio prediction of growth properties over a full diurnal cycle. The computational model allows us to study the optimality of metabolite partitioning during diurnal growth. The cyclic pattern of glycogen accumulation, an emergent property of the model, has timing characteristics that are in qualitative agreement with experimental findings. The approach presented here provides insight into the time-dependent resource allocation problem of phototrophic diurnal growth and may serve as a general framework to assess the optimality of metabolic strategies that evolved in phototrophic organisms under diurnal conditions. PMID:28720699

Design of safety-oriented control allocation strategies for overactuated electric vehicles

NASA Astrophysics Data System (ADS)

de Castro, Ricardo; Tanelli, Mara; Esteves Araújo, Rui; Savaresi, Sergio M.

2014-08-01

The new vehicle platforms for electric vehicles (EVs) that are becoming available are characterised by actuator redundancy, which makes it possible to jointly optimise different aspects of the vehicle motion. To do this, high-level control objectives are first specified and solved with appropriate control strategies. Then, the resulting virtual control action must be translated into actual actuator commands by a control allocation layer that takes care of computing the forces to be applied at the wheels. This step, in general, is quite demanding as far as computational complexity is considered. In this work, a safety-oriented approach to this problem is proposed. Specifically, a four-wheel steer EV with four in-wheel motors is considered, and the high-level motion controller is designed within a sliding mode framework with conditional integrators. For distributing the forces among the tyres, two control allocation approaches are investigated. The first, based on the extension of the cascading generalised inverse method, is computationally efficient but shows some limitations in dealing with unfeasible force values. To solve the problem, a second allocation algorithm is proposed, which relies on the linearisation of the tyre-road friction constraints. Extensive tests, carried out in the CarSim simulation environment, demonstrate the effectiveness of the proposed approach.

A new proposal for greenhouse gas emissions responsibility allocation: best available technologies approach.

PubMed

Berzosa, Álvaro; Barandica, Jesús M; Fernández-Sánchez, Gonzalo

2014-01-01

In recent years, several methodologies have been developed for the quantification of greenhouse gas (GHG) emissions. However, determining who is responsible for these emissions is also quite challenging. The most common approach is to assign emissions to the producer (based on the Kyoto Protocol), but proposals also exist for its allocation to the consumer (based on an ecological footprint perspective) and for a hybrid approach called shared responsibility. In this study, the existing proposals and standards regarding the allocation of GHG emissions responsibilities are analyzed, focusing on their main advantages and problems. A new model of shared responsibility that overcomes some of the existing problems is also proposed. This model is based on applying the best available technologies (BATs). This new approach allocates the responsibility between the producers and the final consumers based on the real capacity of each agent to reduce emissions. The proposed approach is demonstrated using a simple case study of a 4-step life cycle of ammonia nitrate (AN) fertilizer production. The proposed model has the characteristics that the standards and publications for assignment of GHG emissions responsibilities demand. This study presents a new way to assign responsibilities that pushes all the actors in the production chain, including consumers, to reduce pollution. © 2013 SETAC.

Providing appropriate services to individuals in the community: a preliminary case-mix for model allocating personal care services.

PubMed

Phillips, Charles D; Dyer, James; Janousek, Vit; Halperin, Lisa; Hawes, Catherine

2008-01-01

Personal care services are often provided to clients in community settings through highly discretionary processes. Such processes provide little guidance for caseworkers concerning how public resources should be allocated. The results of such processes almost guarantee that individuals with very similar needs will receive very different levels of care resources. Such disparities in treatment open the door to inequity and ineffectiveness. One way to address this problem is through case-mix classification systems that allocate hours of care according to client needs. This paper outlines the preliminary steps taken by one state in its movement toward such a system.

Resource Economics

NASA Astrophysics Data System (ADS)

Conrad, Jon M.

2000-01-01

Resource Economics is a text for students with a background in calculus, intermediate microeconomics, and a familiarity with the spreadsheet software Excel. The book covers basic concepts, shows how to set up spreadsheets to solve dynamic allocation problems, and presents economic models for fisheries, forestry, nonrenewable resources, stock pollutants, option value, and sustainable development. Within the text, numerical examples are posed and solved using Excel's Solver. These problems help make concepts operational, develop economic intuition, and serve as a bridge to the study of real-world problems of resource management. Through these examples and additional exercises at the end of Chapters 1 to 8, students can make dynamic models operational, develop their economic intuition, and learn how to set up spreadsheets for the simulation of optimization of resource and environmental systems. Book is unique in its use of spreadsheet software (Excel) to solve dynamic allocation problems Conrad is co-author of a previous book for the Press on the subject for graduate students Approach is extremely student-friendly; gives students the tools to apply research results to actual environmental issues

Motion-related resource allocation in dynamic wireless visual sensor network environments.

PubMed

Katsenou, Angeliki V; Kondi, Lisimachos P; Parsopoulos, Konstantinos E

2014-01-01

This paper investigates quality-driven cross-layer optimization for resource allocation in direct sequence code division multiple access wireless visual sensor networks. We consider a single-hop network topology, where each sensor transmits directly to a centralized control unit (CCU) that manages the available network resources. Our aim is to enable the CCU to jointly allocate the transmission power and source-channel coding rates for each node, under four different quality-driven criteria that take into consideration the varying motion characteristics of each recorded video. For this purpose, we studied two approaches with a different tradeoff of quality and complexity. The first one allocates the resources individually for each sensor, whereas the second clusters them according to the recorded level of motion. In order to address the dynamic nature of the recorded scenery and re-allocate the resources whenever it is dictated by the changes in the amount of motion in the scenery, we propose a mechanism based on the particle swarm optimization algorithm, combined with two restarting schemes that either exploit the previously determined resource allocation or conduct a rough estimation of it. Experimental simulations demonstrate the efficiency of the proposed approaches.

Redundancy allocation problem for k-out-of- n systems with a choice of redundancy strategies

NASA Astrophysics Data System (ADS)

Aghaei, Mahsa; Zeinal Hamadani, Ali; Abouei Ardakan, Mostafa

2017-03-01

To increase the reliability of a specific system, using redundant components is a common method which is called redundancy allocation problem (RAP). Some of the RAP studies have focused on k-out-of- n systems. However, all of these studies assumed predetermined active or standby strategies for each subsystem. In this paper, for the first time, we propose a k-out-of- n system with a choice of redundancy strategies. Therefore, a k-out-of- n series-parallel system is considered when the redundancy strategy can be chosen for each subsystem. In other words, in the proposed model, the redundancy strategy is considered as an additional decision variable and an exact method based on integer programming is used to obtain the optimal solution of the problem. As the optimization of RAP belongs to the NP-hard class of problems, a modified version of genetic algorithm (GA) is also developed. The exact method and the proposed GA are implemented on a well-known test problem and the results demonstrate the efficiency of the new approach compared with the previous studies.

Optimal Resource Allocation in Electrical Network Defense

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

Yao, Y; Edmunds, T; Papageorgiou, D

2004-01-15

Infrastructure networks supplying electricity, natural gas, water, and other commodities are at risk of disruption due to well-engineered and coordinated terrorist attacks. Countermeasures such as hardening targets, acquisition of spare critical components, and surveillance can be undertaken to detect and deter these attacks. Allocation of available countermeasures resources to sites or activities in a manner that maximizes their effectiveness is a challenging problem. This allocation must take into account the adversary's response after the countermeasure assets are in place and consequence mitigation measures the infrastructure operation can undertake after the attack. The adversary may simply switch strategies to avoid countermeasuresmore » when executing the attack. Stockpiling spares of critical energy infrastructure components has been identified as a key element of a grid infrastructure defense strategy in a recent National Academy of Sciences report [1]. Consider a scenario where an attacker attempts to interrupt the service of an electrical network by disabling some of its facilities while a defender wants to prevent or minimize the effectiveness of any attack. The interaction between the attacker and the defender can be described in three stages: (1) The defender deploys countermeasures, (2) The attacker disrupts the network, and (3) The defender responds to the attack by rerouting power to maintain service while trying to repair damage. In the first stage, the defender considers all possible attack scenarios and deploys countermeasures to defend against the worst scenarios. Countermeasures can include hardening targets, acquiring spare critical components, and installing surveillance devices. In the second stage, the attacker, with full knowledge of the deployed countermeasures, attempts to disable some nodes or links in the network to inflict the greatest loss on the defender. In the third stage, the defender re-dispatches power and restores disabled nodes or links to minimize the loss. The loss can be measured in costs, including the costs of using more expensive generators and the economic losses that can be attributed to loss of load. The defender's goal is to minimize the loss while the attacker wants to maximize it. Assuming some level of budget constraint, each side can only defend or attack a limited number of network elements. When an element is attacked, it is assumed that it will be totally disabled. It is assumed that when an element is defended it cannot be disabled, which may mean that it will be restored in a very short time after being attacked. The rest of the paper is organized as follows. Section 2 will briefly review literature related to multilevel programming and network defense. Section 3 presents a mathematical formulation of the electrical network defense problem. Section 4 describes the solution algorithms. Section 5 discusses computational results. Finally, Sec. 6 explores future research directions.« less

A comparative study of restricted randomization procedures for multiarm trials with equal or unequal treatment allocation ratios.

PubMed

Ryeznik, Yevgen; Sverdlov, Oleksandr

2018-06-04

Randomization designs for multiarm clinical trials are increasingly used in practice, especially in phase II dose-ranging studies. Many new methods have been proposed in the literature; however, there is lack of systematic, head-to-head comparison of the competing designs. In this paper, we systematically investigate statistical properties of various restricted randomization procedures for multiarm trials with fixed and possibly unequal allocation ratios. The design operating characteristics include measures of allocation balance, randomness of treatment assignments, variations in the allocation ratio, and statistical characteristics such as type I error rate and power. The results from the current paper should help clinical investigators select an appropriate randomization procedure for their clinical trial. We also provide a web-based R shiny application that can be used to reproduce all results in this paper and run simulations under additional user-defined experimental scenarios. Copyright © 2018 John Wiley & Sons, Ltd.

The social power of regret: the effect of social appraisal and anticipated emotions on fair and unfair allocations in resource dilemmas.

PubMed

van der Schalk, Job; Kuppens, Toon; Bruder, Martin; Manstead, Antony S R

2015-02-01

We investigated how another person's emotions about resource allocation decisions influence observers' resource allocations by influencing the emotions that observers anticipate feeling if they were to act in the same way. Participants were exposed to an exemplar who made a fair or unfair division in an economic game and expressed pride or regret about this decision. Participants then made their own resource allocation decisions. Exemplar regret about acting fairly decreased the incidence of fair behavior (Studies 1A and 1B). Likewise, exemplar regret about acting unfairly increased the incidence of fair behavior (Study 2). The effect of others' emotions on observers' behavior was mediated by the observers' anticipated emotions. We discuss our findings in light of the view that social appraisal and anticipated emotions are important tools for social learning and may contribute to the formation and maintenance of social norms about greed and fairness.

Optimal Pricing and Power Allocation for Collaborative Jamming with Full Channel Knowledge in Wireless Sensor Networks

PubMed Central

Jeong, Dae-Kyo; Kim, Insook; Kim, Dongwoo

2017-01-01

This paper presents a price-searching model in which a source node (Alice) seeks friendly jammers that prevent eavesdroppers (Eves) from snooping legitimate communications by generating interference or noise. Unlike existing models, the distributed jammers also have data to send to their respective destinations and are allowed to access Alice’s channel if it can transmit sufficient jamming power, which is referred to as collaborative jamming in this paper. For the power used to deliver its own signal, the jammer should pay Alice. The price of the jammers’ signal power is set by Alice and provides a tradeoff between the signal and the jamming power. This paper presents, in closed-form, an optimal price that maximizes Alice’s benefit and the corresponding optimal power allocation from a jammers’ perspective by assuming that the network-wide channel knowledge is shared by Alice and jammers. For a multiple-jammer scenario where Alice hardly has the channel knowledge, this paper provides a distributed and interactive price-searching procedure that geometrically converges to an optimal price and shows that Alice by a greedy selection policy achieves certain diversity gain, which increases log-linearly as the number of (potential) jammers grows. Various numerical examples are presented to illustrate the behavior of the proposed model. PMID:29165373

Optimal Pricing and Power Allocation for Collaborative Jamming with Full Channel Knowledge in Wireless Sensor Networks.

PubMed

Jeong, Dae-Kyo; Kim, Insook; Kim, Dongwoo

2017-11-22

This paper presents a price-searching model in which a source node (Alice) seeks friendly jammers that prevent eavesdroppers (Eves) from snooping legitimate communications by generating interference or noise. Unlike existing models, the distributed jammers also have data to send to their respective destinations and are allowed to access Alice's channel if it can transmit sufficient jamming power, which is referred to as collaborative jamming in this paper. For the power used to deliver its own signal, the jammer should pay Alice. The price of the jammers' signal power is set by Alice and provides a tradeoff between the signal and the jamming power. This paper presents, in closed-form, an optimal price that maximizes Alice's benefit and the corresponding optimal power allocation from a jammers' perspective by assuming that the network-wide channel knowledge is shared by Alice and jammers. For a multiple-jammer scenario where Alice hardly has the channel knowledge, this paper provides a distributed and interactive price-searching procedure that geometrically converges to an optimal price and shows that Alice by a greedy selection policy achieves certain diversity gain, which increases log-linearly as the number of (potential) jammers grows. Various numerical examples are presented to illustrate the behavior of the proposed model.

Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation

NASA Astrophysics Data System (ADS)

Chen, Tianyi; Mokhtari, Aryan; Wang, Xin; Ribeiro, Alejandro; Giannakis, Georgios B.

2017-06-01

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.

Outcome based state budget allocation for diabetes prevention programs using multi-criteria optimization with robust weights.

PubMed

Mehrotra, Sanjay; Kim, Kibaek

2011-12-01

We consider the problem of outcomes based budget allocations to chronic disease prevention programs across the United States (US) to achieve greater geographical healthcare equity. We use Diabetes Prevention and Control Programs (DPCP) by the Center for Disease Control and Prevention (CDC) as an example. We present a multi-criteria robust weighted sum model for such multi-criteria decision making in a group decision setting. The principal component analysis and an inverse linear programming techniques are presented and used to study the actual 2009 budget allocation by CDC. Our results show that the CDC budget allocation process for the DPCPs is not likely model based. In our empirical study, the relative weights for different prevalence and comorbidity factors and the corresponding budgets obtained under different weight regions are discussed. Parametric analysis suggests that money should be allocated to states to promote diabetes education and to increase patient-healthcare provider interactions to reduce disparity across the US.

Shifting orders among suppliers considering risk, price and transportation cost

NASA Astrophysics Data System (ADS)

Revitasari, C.; Pujawan, I. N.

2018-04-01

Supplier order allocation is an important supply chain decision for an enterprise. It is related to the supplier’s function as a raw material provider and other supporting materials that will be used in production process. Most of works on order allocation has been based on costs and other supply chain performance, but very limited of them taking risks into consideration. In this paper we address the problem of order allocation of a single commodity sourced from multiple suppliers considering supply risks in addition to the attempt of minimizing transportation costs. The supply chain risk was investigated and a procedure was proposed in the risk mitigation phase as a form of risk profile. The objective including risk profile in order allocation is to maximize the product flow from a risky supplier to a relatively less risky supplier. The proposed procedure is applied to a sugar company. The result suggests that order allocations should be maximized to suppliers that have a relatively low risk and minimized to suppliers that have a relatively larger risks.

Which patients do I treat? An experimental study with economists and physicians

PubMed Central

2012-01-01

This experiment investigates decisions made by prospective economists and physicians in an allocation problem which can be framed either medically or neutrally. The potential recipients differ with respect to their minimum needs as well as to how much they benefit from a treatment. We classify the allocators as either 'selfish', 'Rawlsian', or 'maximizing the number of recipients'. Economists tend to maximize their own payoff, whereas the physicians' choices are more in line with maximizing the number of recipients and with Rawlsianism. Regarding the framing, we observe that professional norms surface more clearly in familiar settings. Finally, we scrutinize how the probability of being served and the allocated quantity depend on a recipient's characteristics as well as on the allocator type. JEL Classification: A13, I19, C91, C72 PMID:22827912

Radiology diagnostic devices under emergency electric power at disaster base hospitals during the acute phase of the Great East Japan Earthquake: results of a survey of all disaster base hospitals in Miyagi Prefecture.

PubMed

Maezawa, Shota; Kudo, Daisuke; Furukawa, Hajime; Nakagawa, Atsuhiro; Yamanouchi, Satoshi; Matsumura, Takashi; Egawa, Shinichi; Tominaga, Teiji; Kushimoto, Shigeki

2014-12-01

This study aimed to clarify the management of emergency electric power and the operation of radiology diagnostic devices after the Great East Japan Earthquake. Timing of electricity restoration, actual emergency electric power generation, and whether radiology diagnostic devices were operational and the reason if not were investigated through a questionnaire submitted to all 14 disaster base hospitals in Miyagi Prefecture in February and March 2013. Commercial electricity supply resumed within 3 days after the earthquake at 13 of 14 hospitals. Actual emergency electric power generation was lower than pre-disaster estimates at most of the hospitals. Only 4 of 11 hospitals were able to generate 60% of the power normally consumed. Under emergency electric power, conventional X-ray and computed tomography (CT) scanners worked in 9 of 14 (64%) and 8 of 14 (57%) hospitals, respectively. The main reason conventional X-ray and CT scanners did not operate was that hospitals had not planned to use these devices under emergency electric power. Only 2 of the 14 hospitals had a pre-disaster plan to allocate emergency electric power, and all devices operated at these 2 hospitals. Pre-disaster plans to allocate emergency electric power are required for disaster base hospitals to effectively operate radiology diagnostic devices after a disaster. (Disaster Med Public Health Preparedness. 2014;8:548-552).

Propulsion element requirements using electrical power system unscheduled power

NASA Technical Reports Server (NTRS)

Zimmermann, Frank; Hodge, Kathy

1989-01-01

The suitability of using the electrical energy from the Space Station's Electrical Power System (EPS) during the periods of peak solar insolation which is currently not specifically allocated (unscheduled power) to produce propulsion propellants, gaseous hydrogen, and oxygen by electrolyzing water is investigated. Reboost propellant requirements are emphasized, but the results are more generally relevant because the balance of recurring propellant requirements are an order of magnitude smaller and the nonrecurring requirements are not significant on an average basis.

Computer-Aided Group Problem Solving for Unified Life Cycle Engineering (ULCE)

DTIC Science & Technology

1989-02-01

defining the problem, generating alternative solutions, evaluating alternatives, selecting alternatives, and implementing the solution. Systems...specialist in group dynamics, assists the group in formulating the problem and selecting a model framework. The analyst provides the group with computer...allocating resources, evaluating and selecting options, making judgments explicit, and analyzing dynamic systems. c. University of Rhode Island Drs. Geoffery

Generating Data Flow Programs from Nonprocedural Specifications.

DTIC Science & Technology

1983-03-01

With the I-structures, Gajski points out, it is difficult to know ahead of time the optimal memory allocation scheme to pertition large arrays. amory...contention problems may occur for frequently accessed elements stored in the sam memory module. Gajski observes that these are the same problem which

Capacity improvement using simulation optimization approaches: A case study in the thermotechnology industry

NASA Astrophysics Data System (ADS)

Yelkenci Köse, Simge; Demir, Leyla; Tunalı, Semra; Türsel Eliiyi, Deniz

2015-02-01

In manufacturing systems, optimal buffer allocation has a considerable impact on capacity improvement. This study presents a simulation optimization procedure to solve the buffer allocation problem in a heat exchanger production plant so as to improve the capacity of the system. For optimization, three metaheuristic-based search algorithms, i.e. a binary-genetic algorithm (B-GA), a binary-simulated annealing algorithm (B-SA) and a binary-tabu search algorithm (B-TS), are proposed. These algorithms are integrated with the simulation model of the production line. The simulation model, which captures the stochastic and dynamic nature of the production line, is used as an evaluation function for the proposed metaheuristics. The experimental study with benchmark problem instances from the literature and the real-life problem show that the proposed B-TS algorithm outperforms B-GA and B-SA in terms of solution quality.

Pricing Resources in LTE Networks through Multiobjective Optimization

PubMed Central

Lai, Yung-Liang; Jiang, Jehn-Ruey

2014-01-01

The LTE technology offers versatile mobile services that use different numbers of resources. This enables operators to provide subscribers or users with differential quality of service (QoS) to boost their satisfaction. On one hand, LTE operators need to price the resources high for maximizing their profits. On the other hand, pricing also needs to consider user satisfaction with allocated resources and prices to avoid “user churn,” which means subscribers will unsubscribe services due to dissatisfaction with allocated resources or prices. In this paper, we study the pricing resources with profits and satisfaction optimization (PRPSO) problem in the LTE networks, considering the operator profit and subscribers' satisfaction at the same time. The problem is modelled as nonlinear multiobjective optimization with two optimal objectives: (1) maximizing operator profit and (2) maximizing user satisfaction. We propose to solve the problem based on the framework of the NSGA-II. Simulations are conducted for evaluating the proposed solution. PMID:24526889

Pricing resources in LTE networks through multiobjective optimization.

PubMed

Lai, Yung-Liang; Jiang, Jehn-Ruey

2014-01-01

The LTE technology offers versatile mobile services that use different numbers of resources. This enables operators to provide subscribers or users with differential quality of service (QoS) to boost their satisfaction. On one hand, LTE operators need to price the resources high for maximizing their profits. On the other hand, pricing also needs to consider user satisfaction with allocated resources and prices to avoid "user churn," which means subscribers will unsubscribe services due to dissatisfaction with allocated resources or prices. In this paper, we study the pricing resources with profits and satisfaction optimization (PRPSO) problem in the LTE networks, considering the operator profit and subscribers' satisfaction at the same time. The problem is modelled as nonlinear multiobjective optimization with two optimal objectives: (1) maximizing operator profit and (2) maximizing user satisfaction. We propose to solve the problem based on the framework of the NSGA-II. Simulations are conducted for evaluating the proposed solution.

An analysis of choice making in the assessment of young children with severe behavior problems.

PubMed

Harding, J W; Wacker, D P; Berg, W K; Cooper, L J; Asmus, J; Mlela, K; Muller, J

1999-01-01

We examined how positive and negative reinforcement influenced time allocation, occurrence of problem behavior, and completion of parent instructions during a concurrent choice assessment with 2 preschool-aged children who displayed severe problem behavior in their homes. The children were given a series of concurrent choice options that varied availability of parent attention, access to preferred toys, and presentation of parent instructions. The results showed that both children consistently allocated their time to choice areas that included parent attention when no instructions were presented. When parent attention choice areas included the presentation of instructions, the children displayed differential patterns of behavior that appeared to be influenced by the presence or absence of preferred toys. The results extended previous applications of reinforcer assessment procedures by analyzing the relative influence of both positive and negative reinforcement within a concurrent-operants paradigm.

Game theoretic wireless resource allocation for H.264 MGS video transmission over cognitive radio networks

NASA Astrophysics Data System (ADS)

Fragkoulis, Alexandros; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2015-03-01

We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.

Datasets for supplier selection and order allocation with green criteria, all-unit quantity discounts and varying number of suppliers.

PubMed

Hamdan, Sadeque; Cheaitou, Ali

2017-08-01

This data article provides detailed optimization input and output datasets and optimization code for the published research work titled "Dynamic green supplier selection and order allocation with quantity discounts and varying supplier availability" (Hamdan and Cheaitou, 2017, In press) [1]. Researchers may use these datasets as a baseline for future comparison and extensive analysis of the green supplier selection and order allocation problem with all-unit quantity discount and varying number of suppliers. More particularly, the datasets presented in this article allow researchers to generate the exact optimization outputs obtained by the authors of Hamdan and Cheaitou (2017, In press) [1] using the provided optimization code and then to use them for comparison with the outputs of other techniques or methodologies such as heuristic approaches. Moreover, this article includes the randomly generated optimization input data and the related outputs that are used as input data for the statistical analysis presented in Hamdan and Cheaitou (2017 In press) [1] in which two different approaches for ranking potential suppliers are compared. This article also provides the time analysis data used in (Hamdan and Cheaitou (2017, In press) [1] to study the effect of the problem size on the computation time as well as an additional time analysis dataset. The input data for the time study are generated randomly, in which the problem size is changed, and then are used by the optimization problem to obtain the corresponding optimal outputs as well as the corresponding computation time.

Placing invasive species management in a spatiotemporal context.

PubMed

Baker, Christopher M; Bode, Michael

2016-04-01

Invasive species are a worldwide issue, both ecologically and economically. A large body of work focuses on various aspects of invasive species control, including how to allocate control efforts to eradicate an invasive population as cost effectively as possible: There are a diverse range of invasive species management problems, and past mathematical analyses generally focus on isolated examples, making it hard to identify and understand parallels between the different contexts. In this study, we use a single spatiotemporal model to tackle the problem of allocating control effort for invasive species when suppressing an island invasive species, and for long-term spatial suppression projects. Using feral cat suppression as an illustrative example, we identify the optimal resource allocation for island and mainland suppression projects. Our results demonstrate how using a single model to solve different problems reveals similar characteristics of the solutions in different scenarios. As well as illustrating the insights offered by linking problems through a spatiotemporal model, we also derive novel and practically applicable results for our case studies. For temporal suppression projects on islands, we find that lengthy projects are more cost effective and that rapid control projects are only economically cost effective when population growth rates are high or diminishing returns on control effort are low. When suppressing invasive species around conservation assets (e.g., national parks or exclusion fences), we find that the size of buffer zones should depend on the ratio of the species growth and spread rate.

Resource allocation processes at multilateral organizations working in global health

PubMed Central

Chi, Y-Ling; Bump, Jesse B

2018-01-01

Abstract International institutions provide well over US$10 billion in development assistance for health (DAH) annually and between 1990 and 2014, DAH disbursements totaled $458 billion but how do they decide who gets what, and for what purpose? In this article, we explore how allocation decisions were made by the nine convening agencies of the Equitable Access Initiative. We provide clear, plain language descriptions of the complete process from resource mobilization to allocation for the nine multilateral agencies with prominent agendas in global health. Then, through a comparative analysis we illuminate the choices and strategies employed in the nine international institutions. We find that resource allocation in all reviewed institutions follow a similar pattern, which we categorized in a framework of five steps: strategy definition, resource mobilization, eligibility of countries, support type and funds allocation. All the reviewed institutions generate resource allocation decisions through well-structured and fairly complex processes. Variations in those processes seem to reflect differences in institutional principles and goals. However, these processes have serious shortcomings. Technical problems include inadequate flexibility to account for or meet country needs. Although aid effectiveness and value for money are commonly referenced, we find that neither performance nor impact is a major criterion for allocating resources. We found very little formal consideration of the incentives generated by allocation choices. Political issues include non-transparent influence on allocation processes by donors and bureaucrats, and the common practice of earmarking funds to bypass the normal allocation process entirely. Ethical deficiencies include low accountability and transparency at international institutions, and limited participation by affected citizens or their representatives. We find that recipient countries have low influence on allocation processes themselves, although within these processes they have some influence in relatively narrow areas. PMID:29415239

Power Saving Control for Battery-Powered Portable WLAN APs

NASA Astrophysics Data System (ADS)

Ogawa, Masakatsu; Hiraguri, Takefumi

This paper proposes a power saving control function for battery-powered portable wireless LAN (WLAN) access points (APs) to extend the battery life. The IEEE802.11 standard does not support power saving control for APs. To enable a sleep state for an AP, the AP forces the stations (STAs) to refrain from transmitting frames using the network allocation vector (NAV) while the AP is sleeping. Thus the sleep state for the AP can be employed without causing frame loss at the STAs. Numerical analysis and computer simulation reveal that the newly proposed control technique conserves power compared to the conventional control.

Dynamic Changes in Phase-Amplitude Coupling Facilitate Spatial Attention Control in Fronto-Parietal Cortex

PubMed Central

Szczepanski, Sara M.; Crone, Nathan E.; Kuperman, Rachel A.; Auguste, Kurtis I.; Parvizi, Josef; Knight, Robert T.

2014-01-01

Attention is a core cognitive mechanism that allows the brain to allocate limited resources depending on current task demands. A number of frontal and posterior parietal cortical areas, referred to collectively as the fronto-parietal attentional control network, are engaged during attentional allocation in both humans and non-human primates. Numerous studies have examined this network in the human brain using various neuroimaging and scalp electrophysiological techniques. However, little is known about how these frontal and parietal areas interact dynamically to produce behavior on a fine temporal (sub-second) and spatial (sub-centimeter) scale. We addressed how human fronto-parietal regions control visuospatial attention on a fine spatiotemporal scale by recording electrocorticography (ECoG) signals measured directly from subdural electrode arrays that were implanted in patients undergoing intracranial monitoring for localization of epileptic foci. Subjects (n = 8) performed a spatial-cuing task, in which they allocated visuospatial attention to either the right or left visual field and detected the appearance of a target. We found increases in high gamma (HG) power (70–250 Hz) time-locked to trial onset that remained elevated throughout the attentional allocation period over frontal, parietal, and visual areas. These HG power increases were modulated by the phase of the ongoing delta/theta (2–5 Hz) oscillation during attentional allocation. Critically, we found that the strength of this delta/theta phase-HG amplitude coupling predicted reaction times to detected targets on a trial-by-trial basis. These results highlight the role of delta/theta phase-HG amplitude coupling as a mechanism for sub-second facilitation and coordination within human fronto-parietal cortex that is guided by momentary attentional demands. PMID:25157678

Optimized design and analysis of preclinical intervention studies in vivo

PubMed Central

Laajala, Teemu D.; Jumppanen, Mikael; Huhtaniemi, Riikka; Fey, Vidal; Kaur, Amanpreet; Knuuttila, Matias; Aho, Eija; Oksala, Riikka; Westermarck, Jukka; Mäkelä, Sari; Poutanen, Matti; Aittokallio, Tero

2016-01-01

Recent reports have called into question the reproducibility, validity and translatability of the preclinical animal studies due to limitations in their experimental design and statistical analysis. To this end, we implemented a matching-based modelling approach for optimal intervention group allocation, randomization and power calculations, which takes full account of the complex animal characteristics at baseline prior to interventions. In prostate cancer xenograft studies, the method effectively normalized the confounding baseline variability, and resulted in animal allocations which were supported by RNA-seq profiling of the individual tumours. The matching information increased the statistical power to detect true treatment effects at smaller sample sizes in two castration-resistant prostate cancer models, thereby leading to saving of both animal lives and research costs. The novel modelling approach and its open-source and web-based software implementations enable the researchers to conduct adequately-powered and fully-blinded preclinical intervention studies, with the aim to accelerate the discovery of new therapeutic interventions. PMID:27480578

Optimized design and analysis of preclinical intervention studies in vivo.

PubMed

Laajala, Teemu D; Jumppanen, Mikael; Huhtaniemi, Riikka; Fey, Vidal; Kaur, Amanpreet; Knuuttila, Matias; Aho, Eija; Oksala, Riikka; Westermarck, Jukka; Mäkelä, Sari; Poutanen, Matti; Aittokallio, Tero

2016-08-02

Recent reports have called into question the reproducibility, validity and translatability of the preclinical animal studies due to limitations in their experimental design and statistical analysis. To this end, we implemented a matching-based modelling approach for optimal intervention group allocation, randomization and power calculations, which takes full account of the complex animal characteristics at baseline prior to interventions. In prostate cancer xenograft studies, the method effectively normalized the confounding baseline variability, and resulted in animal allocations which were supported by RNA-seq profiling of the individual tumours. The matching information increased the statistical power to detect true treatment effects at smaller sample sizes in two castration-resistant prostate cancer models, thereby leading to saving of both animal lives and research costs. The novel modelling approach and its open-source and web-based software implementations enable the researchers to conduct adequately-powered and fully-blinded preclinical intervention studies, with the aim to accelerate the discovery of new therapeutic interventions.

Optimal allocation of industrial PV-storage micro-grid considering important load

NASA Astrophysics Data System (ADS)

He, Shaohua; Ju, Rong; Yang, Yang; Xu, Shuai; Liang, Lei

2018-03-01

At present, the industrial PV-storage micro-grid has been widely used. This paper presents an optimal allocation model of PV-storage micro-grid capacity considering the important load of industrial users. A multi-objective optimization model is established to promote the local extinction of PV power generation and the maximum investment income of the enterprise as the objective function. Particle swarm optimization (PSO) is used to solve the case of a city in Jiangsu Province, the results are analyzed economically.

Concurrent Reinforcement Schedules for Problem Behavior and Appropriate Behavior: Experimental Applications of the Matching Law

ERIC Educational Resources Information Center

Borrero, Carrie S. W.; Vollmer, Timothy R.; Borrero, John C.; Bourret, Jason C.; Sloman, Kimberly N.; Samaha, Andrew L.; Dallery, Jesse

2010-01-01

This study evaluated how children who exhibited functionally equivalent problem and appropriate behavior allocate responding to experimentally arranged reinforcer rates. Relative reinforcer rates were arranged on concurrent variable-interval schedules and effects on relative response rates were interpreted using the generalized matching equation.…

30 CFR 1220.011 - Schedule of allowable direct and allocable joint costs and credits.

Code of Federal Regulations, 2014 CFR

2014-07-01

... engineering design problems related to equipment or facilities required for NPSL operations. (4) The cost of any contract service related to research and development is specifically excluded, as are contract services calling for feasibility studies not directly related to specific engineering design problems or...

Achieving High Performance in Parallel Applications via Kernel-Application Interaction

DTIC Science & Technology

1996-04-01

time systems include airplane autopilot or nuclear power plant control. New complex, parallel soft real-time applica- tions have been generating...to keep as many sheep on the table as possible, and the more powerful the sheep behavior-models and look-ahead, the better the results. General...fact that it provides considerable flexibility when considering the amount of processing power to allocate to a planner. In this experiment we again

75 FR 33748 - Amateur Radio Use of the Allocation at 5 MHz

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-15

... envelope power (PEP). 3. The existing amateur radio use of the 60 meter band represents a balancing of... Comment Filing System (ECFS), (2) the Federal Government's eRulemaking Portal, or (3) by filing paper... transmitter output power in modern amateur radio transceivers is 100 W PEP, and that the present 50 W PEP...

Direct-current converter for gas-discharge lamps

NASA Technical Reports Server (NTRS)

Lutus, P.

1980-01-01

Metal/halide and similar gas-discharge lamps are powered from low-voltage dc source using small efficient converter. Converter is useful whenever 60-cycle ac power is not available or where space and weight allocations are limited. Possible applications are offshore platforms, mobile homes, and emergency lighting. Design innovations give supply high reliability and efficiency up to 75 percent.

Inventory slack routing application in emergency logistics and relief distributions.

PubMed

Yang, Xianfeng; Hao, Wei; Lu, Yang

2018-01-01

Various natural and manmade disasters during last decades have highlighted the need of further improving on governmental preparedness to emergency events, and a relief supplies distribution problem named Inventory Slack Routing Problem (ISRP) has received increasing attentions. In an ISRP, inventory slack is defined as the duration between reliefs arriving time and estimated inventory stock-out time. Hence, a larger inventory slack could grant more responsive time in facing of various factors (e.g., traffic congestion) that may lead to delivery lateness. In this study, the relief distribution problem is formulated as an optimization model that maximize the minimum slack among all dispensing sites. To efficiently solve this problem, we propose a two-stage approach to tackle the vehicle routing and relief allocation sub-problems. By analyzing the inter-relations between these two sub-problems, a new objective function considering both delivery durations and dispensing rates of demand sites is applied in the first stage to design the vehicle routes. A hierarchical routing approach and a sweep approach are also proposed in this stage. Given the vehicle routing plan, the relief allocation could be easily solved in the second stage. Numerical experiment with a comparison of multi-vehicle Traveling Salesman Problem (TSP) has demonstrated the need of ISRP and the capability of the proposed solution approaches.

Inventory slack routing application in emergency logistics and relief distributions

PubMed Central

Yang, Xianfeng; Lu, Yang

2018-01-01

Various natural and manmade disasters during last decades have highlighted the need of further improving on governmental preparedness to emergency events, and a relief supplies distribution problem named Inventory Slack Routing Problem (ISRP) has received increasing attentions. In an ISRP, inventory slack is defined as the duration between reliefs arriving time and estimated inventory stock-out time. Hence, a larger inventory slack could grant more responsive time in facing of various factors (e.g., traffic congestion) that may lead to delivery lateness. In this study, the relief distribution problem is formulated as an optimization model that maximize the minimum slack among all dispensing sites. To efficiently solve this problem, we propose a two-stage approach to tackle the vehicle routing and relief allocation sub-problems. By analyzing the inter-relations between these two sub-problems, a new objective function considering both delivery durations and dispensing rates of demand sites is applied in the first stage to design the vehicle routes. A hierarchical routing approach and a sweep approach are also proposed in this stage. Given the vehicle routing plan, the relief allocation could be easily solved in the second stage. Numerical experiment with a comparison of multi-vehicle Traveling Salesman Problem (TSP) has demonstrated the need of ISRP and the capability of the proposed solution approaches. PMID:29902196

Allocation of authority in European health policy.

PubMed

Adolph, Christopher; Greer, Scott L; Massard da Fonseca, Elize

2012-11-01

Although many study the effects of different allocations of health policy authority, few ask why countries assign responsibility over different policies as they do. We test two broad theories: fiscal federalism, which predicts rational governments will concentrate information-intensive operations at lower levels, and redistributive and regulatory functions at higher levels; and "politicized federalism", which suggests a combination of systematic and historically idiosyncratic political variables interfere with efficient allocation of authority. Drawing on the WHO Health in Transition country profiles, we present new data on the allocation of responsibility for key health care policy tasks (implementation, provision, finance, regulation, and framework legislation) and policy areas (primary, secondary and tertiary care, public health and pharmaceuticals) in the 27 EU member states and Switzerland. We use a Bayesian multinomial mixed logit model to analyze how different countries arrive at different allocations of authority over each task and area of health policy, and find the allocation of powers broadly follows fiscal federalism. Responsibility for pharmaceuticals, framework legislation, and most finance lodges at the highest levels of government, acute and primary care in the regions, and provision at the local and regional levels. Where allocation does not follow fiscal federalism, it appears to reflect ethnic divisions, the population of states and regions, the presence of mountainous terrain, and the timing of region creation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Balancing Detection and Eradication for Control of Epidemics: Sudden Oak Death in Mixed-Species Stands

PubMed Central

Ndeffo Mbah, Martial L.; Gilligan, Christopher A.

2010-01-01

Culling of infected individuals is a widely used measure for the control of several plant and animal pathogens but culling first requires detection of often cryptically-infected hosts. In this paper, we address the problem of how to allocate resources between detection and culling when the budget for disease management is limited. The results are generic but we motivate the problem for the control of a botanical epidemic in a natural ecosystem: sudden oak death in mixed evergreen forests in coastal California, in which species composition is generally dominated by a spreader species (bay laurel) and a second host species (coast live oak) that is an epidemiological dead-end in that it does not transmit infection but which is frequently a target for preservation. Using a combination of an epidemiological model for two host species with a common pathogen together with optimal control theory we address the problem of how to balance the allocation of resources for detection and epidemic control in order to preserve both host species in the ecosystem. Contrary to simple expectations our results show that an intermediate level of detection is optimal. Low levels of detection, characteristic of low effort expended on searching and detection of diseased trees, and high detection levels, exemplified by the deployment of large amounts of resources to identify diseased trees, fail to bring the epidemic under control. Importantly, we show that a slight change in the balance between the resources allocated to detection and those allocated to control may lead to drastic inefficiencies in control strategies. The results hold when quarantine is introduced to reduce the ingress of infected material into the region of interest. PMID:20856850

Towards an understanding of the molecular regulation of carbon allocation in diatoms: the interaction of energy and carbon allocation.

PubMed

Wagner, Heiko; Jakob, Torsten; Fanesi, Andrea; Wilhelm, Christian

2017-09-05

In microalgae, the photosynthesis-driven CO 2 assimilation delivers cell building blocks that are used in different biosynthetic pathways. Little is known about how the cell regulates the subsequent carbon allocation to, for example, cell growth or for storage. However, knowledge about these regulatory mechanisms is of high biotechnological and ecological importance. In diatoms, the situation becomes even more complex because, as a consequence of their secondary endosymbiotic origin, the compartmentation of the pathways for the primary metabolic routes is different from green algae. Therefore, the mechanisms to manipulate the carbon allocation pattern cannot be adopted from the green lineage. This review describes the general pathways of cellular energy distribution from light absorption towards the final allocation of carbon into macromolecules and summarizes the current knowledge of diatom-specific allocation patterns. We further describe the (limited) knowledge of regulatory mechanisms of carbon partitioning between lipids, carbohydrates and proteins in diatoms. We present solutions to overcome the problems that hinder the identification of regulatory elements of carbon metabolism.This article is part of the themed issue 'The peculiar carbon metabolism in diatoms'. © 2017 The Author(s).

Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning

PubMed Central

Zhang, Yue; Song, Bin; Zhang, Ying; Du, Xiaojiang; Guizani, Mohsen

2016-01-01

Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management. PMID:27916841

Prospective Analysis of Behavioral Economic Predictors of Stable Moderation Drinking Among Problem Drinkers Attempting Natural Recovery

PubMed Central

Tucker, Jalie A.; Cheong, JeeWon; Chandler, Susan D.; Lambert, Brice H.; Pietrzak, Brittney; Kwok, Heather; Davies, Susan L.

2016-01-01

Background As interventions have expanded beyond clinical treatment to include brief interventions for persons with less severe alcohol problems, predicting who can achieve stable moderation drinking has gained importance. Recent behavioral economic (BE) research on natural recovery has shown that active problem drinkers who allocate their monetary expenditures on alcohol and saving for the future over longer time horizons tend to have better subsequent recovery outcomes, including maintenance of stable moderation drinking. The present study compared the predictive utility of this money-based “Alcohol-Savings Discretionary Expenditure” (ASDE) index with multiple BE analogue measures of behavioral impulsivity and self-control, which have seldom been investigated together, to predict outcomes of natural recovery attempts. Methods Community-dwelling problem drinkers, enrolled shortly after stopping abusive drinking without treatment, were followed prospectively for up to a year (N = 175 [75.4% male], M age = 50.65 years). They completed baseline assessments of pre-resolution drinking practices and problems; analogue behavioral choice tasks (Delay Discounting, Melioration-Maximization, and Alcohol Purchase Tasks); and a Timeline Followback interview including expenditures on alcohol compared to voluntary savings (ASDE index) during the pre-resolution year. Results Multinomial logistic regression models showed that, among the BE measures, only the ASDE index predicted stable moderation drinking compared to stable abstinence or unstable resolutions involving relapse. As hypothesized, stable moderation was associated with more balanced pre-resolution allocations to drinking and savings (OR = 1.77, 95% CI = 1.02 ∼ 3.08, p < .05), suggesting it is associated with longer term behavior regulation processes than abstinence. Conclusions The ASDE's unique predictive utility may rest on its comprehensive representation of contextual elements to support this patterning of behavioral allocation. Stable low risk drinking, but not abstinence, requires such regulatory processes. PMID:27775161

Flow of Funds Modeling for Localized Financial Markets: An Application of Spatial Price and Allocation Activity Analysis Models.

DTIC Science & Technology

1981-01-01

on modeling the managerial aspects of the firm. The second has been the application to economic theory led by ...individual portfolio optimization problems which were embedded in a larger global optimization problem. In the global problem, portfolios were linked by market ...demand quantities or be given by linear demand relationships. As in~ the source markets , the model

Efficient Computing Budget Allocation for Finding Simplest Good Designs

PubMed Central

Jia, Qing-Shan; Zhou, Enlu; Chen, Chun-Hung

2012-01-01

In many applications some designs are easier to implement, require less training data and shorter training time, and consume less storage than the others. Such designs are called simple designs, and are usually preferred over complex ones when they all have good performance. Despite the abundant existing studies on how to find good designs in simulation-based optimization (SBO), there exist few studies on finding simplest good designs. We consider this important problem in this paper, and make the following contributions. First, we provide lower bounds for the probabilities of correctly selecting the m simplest designs with top performance, and selecting the best m such simplest good designs, respectively. Second, we develop two efficient computing budget allocation methods to find m simplest good designs and to find the best m such designs, respectively; and show their asymptotic optimalities. Third, we compare the performance of the two methods with equal allocations over 6 academic examples and a smoke detection problem in wireless sensor networks. We hope that this work brings insight to finding the simplest good designs in general. PMID:23687404

A market-based optimization approach to sensor and resource management

NASA Astrophysics Data System (ADS)

Schrage, Dan; Farnham, Christopher; Gonsalves, Paul G.

2006-05-01

Dynamic resource allocation for sensor management is a problem that demands solutions beyond traditional approaches to optimization. Market-based optimization applies solutions from economic theory, particularly game theory, to the resource allocation problem by creating an artificial market for sensor information and computational resources. Intelligent agents are the buyers and sellers in this market, and they represent all the elements of the sensor network, from sensors to sensor platforms to computational resources. These agents interact based on a negotiation mechanism that determines their bidding strategies. This negotiation mechanism and the agents' bidding strategies are based on game theory, and they are designed so that the aggregate result of the multi-agent negotiation process is a market in competitive equilibrium, which guarantees an optimal allocation of resources throughout the sensor network. This paper makes two contributions to the field of market-based optimization: First, we develop a market protocol to handle heterogeneous goods in a dynamic setting. Second, we develop arbitrage agents to improve the efficiency in the market in light of its dynamic nature.

SLA-based optimisation of virtualised resource for multi-tier web applications in cloud data centres

NASA Astrophysics Data System (ADS)

Bi, Jing; Yuan, Haitao; Tie, Ming; Tan, Wei

2015-10-01

Dynamic virtualised resource allocation is the key to quality of service assurance for multi-tier web application services in cloud data centre. In this paper, we develop a self-management architecture of cloud data centres with virtualisation mechanism for multi-tier web application services. Based on this architecture, we establish a flexible hybrid queueing model to determine the amount of virtual machines for each tier of virtualised application service environments. Besides, we propose a non-linear constrained optimisation problem with restrictions defined in service level agreement. Furthermore, we develop a heuristic mixed optimisation algorithm to maximise the profit of cloud infrastructure providers, and to meet performance requirements from different clients as well. Finally, we compare the effectiveness of our dynamic allocation strategy with two other allocation strategies. The simulation results show that the proposed resource allocation method is efficient in improving the overall performance and reducing the resource energy cost.

Research on Multirobot Pursuit Task Allocation Algorithm Based on Emotional Cooperation Factor

PubMed Central

Fang, Baofu; Chen, Lu; Wang, Hao; Dai, Shuanglu; Zhong, Qiubo

2014-01-01

Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots' individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm. PMID:25152925

Research on multirobot pursuit task allocation algorithm based on emotional cooperation factor.

PubMed

Fang, Baofu; Chen, Lu; Wang, Hao; Dai, Shuanglu; Zhong, Qiubo

2014-01-01

Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots' individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm.

From honeybees to Internet servers: biomimicry for distributed management of Internet hosting centers.

PubMed

Nakrani, Sunil; Tovey, Craig

2007-12-01

An Internet hosting center hosts services on its server ensemble. The center must allocate servers dynamically amongst services to maximize revenue earned from hosting fees. The finite server ensemble, unpredictable request arrival behavior and server reallocation cost make server allocation optimization difficult. Server allocation closely resembles honeybee forager allocation amongst flower patches to optimize nectar influx. The resemblance inspires a honeybee biomimetic algorithm. This paper describes details of the honeybee self-organizing model in terms of information flow and feedback, analyzes the homology between the two problems and derives the resulting biomimetic algorithm for hosting centers. The algorithm is assessed for effectiveness and adaptiveness by comparative testing against benchmark and conventional algorithms. Computational results indicate that the new algorithm is highly adaptive to widely varying external environments and quite competitive against benchmark assessment algorithms. Other swarm intelligence applications are briefly surveyed, and some general speculations are offered regarding their various degrees of success.

Allocating and Reallocating Financial Resources in an Environment of Fiscal Stress. Topical Paper No. 24. Selected Proceedings of the Annual Conference on Higher Education (9th, Center for the Study of Higher Education, University of Arizona, Tucson, May 1984).

ERIC Educational Resources Information Center

Wilson, Robert A., Ed.

Resource allocation and reallocation strategies for colleges who have financial problems are considered in three articles based on presentations to a national conference at the University of Arizona. In "Reallocation Strategies," James A. Hyatt discusses factors that shape institutional responses to reallocation and elements that should…

Reconceptualizing perceptual load as a rate problem: The role of time in the allocation of selective attention.

PubMed

Li, Zhi; Xin, Keyun; Li, Wei; Li, Yanzhe

2018-04-30

In the literature about allocation of selective attention, a widely studied question is when will attention be allocated to information that is clearly irrelevant to the task at hand. The present study, by using convergent evidence, demonstrated that there is a trade-off between quantity of information present in a display and the time allowed to process it. Specifically, whether or not there is interference from irrelevant distractors depends not only on the amount of information present, but also on the amount of time allowed to process that information. When processing time is calibrated to the amount of information present, irrelevant distractors can be selectively ignored successfully. These results suggest that the perceptual load in the load theory of selective attention (i.e., Lavie, 2005) should be thought about as a dynamic rate problem rather than a static capacity limitation. The authors thus propose that rather than conceiving of perceptual load as a quantity of information, they should consider it as a quantity of information per unit of time. In other words, it is the relationship between the quantity of information in the task and the time for processing the information that determines the allocation of selective attention. Thus, the present findings extended load theory, allowing it to explain findings that were previously considered as counter evidence of load theory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Plant reproductive allocation predicts herbivore dynamics across spatial and temporal scales.

PubMed

Miller, Tom E X; Tyre, Andrew J; Louda, Svata M

2006-11-01

Life-history theory suggests that iteroparous plants should be flexible in their allocation of resources toward growth and reproduction. Such plasticity could have consequences for herbivores that prefer or specialize on vegetative versus reproductive structures. To test this prediction, we studied the response of the cactus bug (Narnia pallidicornis) to meristem allocation by tree cholla cactus (Opuntia imbricata). We evaluated the explanatory power of demographic models that incorporated variation in cactus relative reproductive effort (RRE; the proportion of meristems allocated toward reproduction). Field data provided strong support for a single model that defined herbivore fecundity as a time-varying, increasing function of host RRE. High-RRE plants were predicted to support larger insect populations, and this effect was strongest late in the season. Independent field data provided strong support for these qualitative predictions and suggested that plant allocation effects extend across temporal and spatial scales. Specifically, late-season insect abundance was positively associated with interannual changes in cactus RRE over 3 years. Spatial variation in insect abundance was correlated with variation in RRE among five cactus populations across New Mexico. We conclude that plant allocation can be a critical component of resource quality for insect herbivores and, thus, an important mechanism underlying variation in herbivore abundance across time and space.

Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments

PubMed Central

Zapater, Marina; Sanchez, Cesar; Ayala, Jose L.; Moya, Jose M.; Risco-Martín, José L.

2012-01-01

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time. PMID:23112621

Managing Complexity

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

Chassin, David P.; Posse, Christian; Malard, Joel M.

2004-08-01

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today’s most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically-based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This paper explores the state of the art in the use physical analogs for understanding the behavior of some econophysical systems and to deriving stable and robust controlmore » strategies for them. In particular we review and discussion applications of some analytic methods based on the thermodynamic metaphor according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood.« less

[Monitoring evaluation system for high-specialty hospitals].

PubMed

Fajardo Dolci, Germán; Aguirre Gas, Héctor G; Robledo Galván, Héctor

2011-01-01

Hospital evaluation is a fundamental process to identify medical units' objective compliance, to analyze efficiency of resource use and allocation, institutional values and mission alignment, patient safety and quality standards, contributions to research and medical education, and the degree of coordination among medical units and the health system as a whole. We propose an evaluation system for highly specialized regional hospitals through the monitoring of performance indicators. The following are established as base thematic elements in the construction of indicators: safe facilities and equipment, financial situation, human resources management, policy management, organizational climate, clinical activity, quality and patient safety, continuity of care, patients' and providers' rights and obligations, teaching, research, social responsibility, coordination mechanisms. Monitoring refers to the planned and systematic evaluation of valid and reliable indicators, aimed at identifying problems and opportunity areas. Moreover, evaluation is a powerful tool to strengthen decision-making and accountability in medical units.