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Assessing solution quality and computational performance in the hydro unit commitment problem considering different mathematical programming approaches

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ELECTRIC POWER SYSTEMS RESEARCH 2016年 136卷 212-222页

作者： Finardi, E. C. Takigawa, F. Y. K. Brito, B. H. Univ Fed Santa Catarina Elect Syst Planning Res Lab BR-88040900 Florianopolis SC Brazil Fed Inst Santa Catarina BR-88020300 Florianopolis SC Brazil Fed Inst Tocantins BR-77020450 Palmas Brazil

This paper presents a comparative analysis of different mathematical programming approaches for optimizing the hydro unit commitment (HUC) problem with cascaded plants, multiple generating units, and a head-dependent hydropower model. Regarding the HUC problem related to this paper, the objective is to minimize the cascade outflow while satisfying all constraints, including a power target for each plant, in a day-ahead planning horizon. The decision variables are the on/off status of the units and the respective generation levels. Rigorously, the HUC is a mixed-integer nonlinear programming (MINLP) problem, and several strategies can be used to compute near-optimal solutions. In this paper, we are interested in accessing the solution quality, as well as the computational performance when the HUC problem is solved using the following mathematical programming approaches: (i) the Lagrangian relaxation that represents a decomposition technique that exploits the HUC modeling structure, (ii) a MINLP solver that can handle the size and the non-concavity of the problem, and (iii) a mixed-integer linear programming (MILP) approach obtained by means of the hydropower model linearization. To perform the proposed analysis, numerical results are presented related to a real hydro system with eight cascaded reservoirs and 29 generating units. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Hydro unit commitment Lagrangian relaxation mixed-integer nonlinear programming mixed-integer linear programming Hydropower model

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Simultaneous Model Selection and Parameter Estimation for Lithium-Ion Batteries: A Sequential MINLP Solution Approach

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AICHE JOURNAL 2016年第1期62卷 78-89页

作者： Shen, Jia-Ni He, Yi-Jun Ma, Zi-Feng Shanghai Jiao Tong Univ Dept Chem Engn Shanghai Electrochem Energy Devices Res Ctr Shanghai 200240 Peoples R China

Equivalent circuit model (ECM) is a practical and commonly used tool not only in state of charge (SOC) estimation but also in state of health (SOH) monitoring for lithium-ion batteries (LIBs). The functional forms of circuit parameters with respect to SOC in ECM are usually empirical determined, which cannot guarantee to obtain a compact and simple model. A systematical solution framework for simultaneous functional form selection and parameter estimation is proposed. A bi-objective mixed-integer nonlinear programming (MINLP) model is first constructed. Two solution approaches, namely the explicit and implicit methods, are then developed to balance model accuracy and model complexity. The former explicitly treats the model complexity as a constraint and the latter implicitly embeds the model complexity into the objective as a penalty. Both approaches require sequential solution of the transformed MINLP model and an ideal and nadir ideal solutions-based criterion is utilized to terminate the solution procedure for determining the optimal functional forms, in which ideal solution and nadir ideal solution represent the best and worst of each objective, respectively. Both explicit and implicit approaches are thoroughly evaluated and compared through experimental pulse current discharge test and hybrid pulse power characterization test of a commercial LIB. The fitting and prediction results illustrate that the proposed methods can effectively construct an optimal ECM with minimum complexity and prescribed precision requirement. It is thus indicated that the proposed MINLP-based solution framework, which could automatically guide the optimal ECM construction procedure, can be greatly helpful to both SOC estimation and SOH monitoring for LIBs. (C) 2015 American Institute of Chemical Engineers

关键词： lithium-ion batteries state of charge equivalent circuit model functional forms selection parameter estimation mixed-integer nonlinear programming

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Formulation of a nonlinear water distribution problem with water rationing: an optimisation approach

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SUSTAINABLE WATER RESOURCES MANAGEMENT 2016年第4期2卷 379-385页

作者： Chagwiza, Godfrey Natl Univ Sci & Technol Dept Appl Math POB AC939 Ascot Bulawayo Zimbabwe

A mixed-integer nonlinear programming water distribution problem that incorporates water rationing is presented. The city of Bulawayo water distribution problem is implemented and solved using max-min ant system, genetic, tabu search, and simulated annealing algorithms with 100 runs performed for each algorithm. The results show that the city of Bulawayo can save $3158 a day. The max-min ant system produced the best optimal costs compared with the other algorithms. The least run time is obtained by implementing the tabu search algorithm. Water lost through hoarding during water-rationing periods contributes significantly to the total operational costs. Statistical analysis of the results obtained by different algorithms shows that the optimal costs obtained by tabu search, and simulated annealing algorithms are insignificantly different. Future research may be directed toward incorporating priority among water users and formulating a hybrid algorithm that uses both the max-min ant system and tabu search algorithms to solve such problems.

关键词： mixed-integer nonlinear programming Water rationing Optimisation

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Integrated Production, Inventory, and Location-Allocation Decisions in Designing Supply Chain Networks

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INTERNATIONAL JOURNAL OF INFORMATION SYSTEMS AND SUPPLY CHAIN MANAGEMENT 2016年第4期9卷 22-42页

作者： Alavi, Sepideh Azad, Nader Heydar, Mojtaba Davoudpour, Hamid Univ Wisconsin Milwaukee WI 53201 USA St Marys Univ Sobey Sch Business Halifax NS Canada Univ Newcastle Callaghan NSW Australia Amirkabir Univ Technol Tehran Iran

This paper studies the design and development of an inventory model for manufacturers with constant production rates considering location and allocation decisions in a three-level supply chain. In this supply chain, the demands of customers and the lead times are assumed to be uncertain. Therefore, each distribution center retains some amount of safety stock to provide suitable service level for customers. The proposed non-linear model aims to minimize location and inventory costs of distribution centers, manufacturers and transportation costs subject to relevant constraints. To solve the model, an efficient imperialist competitive algorithm and a Tabu search algorithm, each using variable neighborhood search, are proposed. The model outputs are decisions such as which distribution centers and manufacturers are opened, the allocation of customers to distribution centers, and distribution centers to manufacturers. Results are also the ordering quantity of each opened distribution center and the production rate of each opened manufacturer. The computational results for several instances of the problem are represented to show the efficiency of proposed algorithm.

关键词： Continuous Inventory Review Imperialist Competitive Algorithm Location-Inventory Models Manufacturer mixed-integer nonlinear programming Order Quantity Production Three-Level Supply Chain

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Valid inequalities for the topology optimization problem in gas network design

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OR SPECTRUM 2016年第3期38卷 597-631页

作者： Humpola, Jesco Fuegenschuh, Armin Koch, Thorsten Zuse Inst Berlin Takustr 7 D-14195 Berlin Germany Helmut Schmidt Univ Univ Fed Armed Forces Hamburg Holstenhofweg 85 D-22043 Hamburg Germany Tech Univ Berlin Str 17 Juni 136 D-10623 Berlin Germany

One quarter of Europe's energy demand is provided by natural gas distributed through a vast pipeline network covering the whole of Europe. At a cost of 1 million Euro per km extending the European pipeline network is already a multi-billion Euro business. Therefore, automatic planning tools that support the decision process are desired. Unfortunately, current mathematical methods are not capable of solving the arising network design problems due to their size and complexity. In this article, we will show how to apply optimization methods that can converge to a proven global optimal solution. By introducing a new class of valid inequalities that improve the relaxation of our mixed-integer nonlinear programming model, we are able to speed up the necessary computations substantially.

关键词： Network design mixed-integer nonlinear programming Cutting planes

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Optimizing the Costs and GT based reliabilities of Large-scale Performance Assessments 1

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80th Annual Meeting of the Psychometric-Society

作者： Suh, Yon Soo Hwang, Dasom Quan, Meiling Lee, Guemin Yonsei Univ Dept Educ Seoul South Korea

ISBN: (数字)9783319387598

ISBN: (纸本)9783319387598;9783319387574

In generalizability theory (GT), higher levels of reliability can be obtained by increasing facet sample sizes but at the expense of increasing expenditure and resources. The challenging task is identifying optimal sample sizes that balance such psychometric and practical considerations. As such, the objective of our research was to demonstrate the use of mixed integer nonlinear programming, an optimization procedure, in attaining the most cost-efficient measurement design subject to both psychometric and practical constraints. The optimization procedure was applied to the context of large-scale performance assessments where costs and reliability are important but conflicting issues. The results suggest that the optimization method can be a useful tool in determining the optimal sampling factors to achieving a desired reliability coefficient among multiple feasible solutions. Moreover, they demonstrate how practitioners not only face a trade-off between costs and desired reliability where costs increase exponentially in order to heighten reliability but also demonstrate the need for test developers to consider possible additional practical constraints along with budget and reliability such as restrictions on the number of students, tasks, raters or any other facet of interest.

关键词： Generalizability theory Large-scale performance assessment mixed-integer nonlinear programming Optimal sample sizes Reliability

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A nonlinear model for a capacitated stochastic transportation network using multiple linear regression

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INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT 2016年第4期11卷 252-261页

作者： Shiripour, Saber Mahdavi, Iraj Mahdavi-Amiri, Nezam Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran Sharif Univ Technol Fac Math Sci Tehran Iran

Here, a capacitated location-multi-allocation-routing problem with intelligent stochastic travel times is considered. In our study, the concept of intelligent stochastic travel times incurs two issues: (1) consideration of some random factors in computing the travel times and (2) impact of the traveling population on these random factors simultaneously. Here, a deterministic factor of road length and two random factors of the time spent in traffic and the number of accidents are considered. It is assumed that the time spent in traffic is distributed based on an exponential distribution function and the other factor is distributed based on a Poisson distribution function. Also, the capacities of server nodes and arcs for accepting the population are assumed to be limited. Using multiple linear regression, we formulate the problem as a mixed-integer nonlinear programming model. The objective is to find appropriate locations as server locations among the candidate locations, allocate the existing population in each demand node to server locations and determine the movement path of each member to reach its corresponding server with respect to the simultaneous change of the stochastic travel times so that the expected total transportation time is minimized. Also, to investigate the validation and behavior of the proposed probabilistic model, a network example is provided and computational results are analyzed.

关键词： Intelligent stochastic travel times multiple linear regression multi-allocation mixed-integer nonlinear programming

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Joint Resource Segmentation and Transmission Rate Adaptation in Cloud RAN with Caching as a Service 17

Joint Resource Segmentation and Transmission Rate Adaptation...

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17th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Tang, Jianhua Quek, Tony Q. S. Tay, Wee Peng Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing Peoples R China Singapore Univ Technol & Design Singapore Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

ISBN: (纸本)9781509017492

By introducing Caching as a Service (CaaS) in Cloud radio access network (C-RAN), the joint resource segmentation and transmission rate adaptation problem is investigated in this paper. Specifically, in the baseband unit (BBU) pool of C-RAN, we optimally segment computation and storage resources to different types of virtual machines (VMs), and in the remote radio heads (RRHs), we adjust the beamformers to obtain the cache-based adaptive rate (CBAR). We aim to minimize the system cost, which includes server cost, VM cost and wireless transmission cost. The joint optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem, which contains.. l(0)-norm terms in the objective function and nonconvex constraints. We propose a three-step solution approach, i.e., a general smooth function approximation step, a weighted minimum mean square error (WMMSE) reformulation step and an integer recovery step. Simulation results show that our proposed integer recovery algorithms recover the integer variable values effectively.

关键词： C-RAN Caching as a Service resource segmentation joint transmission mixed-integer nonlinear programming

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Generalized Benders Decomposition to Reoptimize Water Production and Distribution Operations in a Real Water Supply Network

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2016年第2期142卷 4015059-1-4015059-11页

作者： Verleye, Derek Aghezzaf, El-Houssaine Univ Ghent Dept Ind Syst Engn & Prod Design Fac Engn & Architecture Technol Pk 903 B-9052 Zwijnaarde Belgium

Water supply networks are designed to effectively and efficiently supply water to some originally targeted agglomerations. However, the dynamics over time of water-demand patterns and electricity cost schemes may render these designs inefficient and expensive to operate. This paper considers the challenging problem of optimizing water production and distribution operations in one of the largest water supply networks operating in Flanders (Belgium) while accounting for the water-demand and electricity cost dynamics. Optimizing operations in a real water supply network is a difficult task as it involves many constraints. In addition to the complex hydraulic nonlinear equality constraints stemming from friction losses and pump curves, specific constraints for accurate modeling of storage buffers must be taken into account. These constraints require additional binary variables to model free inflow or possible reinjection of water to the network. The resulting optimization problem is thus a nonconvex mixed-integer and nonlinear mathematical problem that is computationally expensive to solve. A particularly appealing method for solving such optimization problems is Generalized Benders Decomposition (GBD). This paper extends this method to the water supply network optimization problem mentioned previously. It is experimentally shown that the approach is successful through careful selection of the complicating variables and values for the penalty term. Results of the experiments carried out on two network instances show that the carefully fine-tuned model allows convergence to near-optimal solutions. Compared to state-of-the-art solvers, the proposed approach proved to be competitive on the tested networks in terms of solution quality and computational time. (C) 2015 American Society of Civil Engineers.

关键词： Large water supply networks mixed-integer nonlinear programming Benders decomposition

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Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: NSGA-II and NRGA

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INFORMATION SCIENCES 2015年第0期292卷 57-74页

作者： Pasandideh, Seyed Hamid Reza Niaki, Seyed Taghi Akhavan Asadi, Kobra Kharazmi Univ Fac Engn Dept Ind Engn Tehran Iran Sharif Univ Technol Dept Ind Engn Tehran Iran

Bi-objective optimization of a multi-product multi-period three-echelon supply-chain-network problem is aimed in this paper. The network consists of manufacturing plants, distribution centers (DCs), and customer nodes. To bring the problem closer to reality, the majority of the parameters in this network including fixed and variable costs, customer demand, available production time, set-up and production times, all are considered stochastic. The goal is to determine the quantities of the products produced by the manufacturing plants in different periods, the number and locations of the warehouses, the quantities of products transported between the supply chain entities, the inventory of products in warehouses and plants, and the shortage of products in periods such that both the expected and the variance of the total cost are minimized. The problem is first formulated into the framework of a single-objective stochastic mixed integer linear programming model. Then, it is reformulated into a bi-objective deterministic mixed-integer nonlinear programming model. To solve the complicated problem, a non-dominated sorting genetic algorithm (NSGA-II) is utilized next. As there is no benchmark available in the literature, another GA-based algorithm called non-dominated ranking genetic algorithm (NRGA) is used to validate the results obtained. In both algorithms, a modified priority-based encoding is proposed. Some numerical illustrations are provided at the end to not only show the applicability of the proposed methodology, but also to select the best method using a t-test along with the simple additive weighting (SAW) method. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Supply chain management Uncertainty mixed-integer nonlinear programming NRGA & NSGA-II SAW

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