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Random lead times in replenishment planning for single-level assembly systems: The value of information

IFAC-PapersOnLine 2017年第1期50卷 1205-1210页

作者： BORODIN V. HNAIEN F. DOLGUI A. École des Mines de Saint-Étienne CMP Georges Charpak CNRS UMR 6158 LIMOSGardanne F-13541 France Laboratory of Industrial Systems Optimization Charles Delaunay Institute University of Technology of Troyes UMR CNRS 8261 12 rue Marie Curie - CS 42060Troyes 10004 France IMT Atlantique LS2N UMR CNRS 6004 La Chantrerie 4 rue Alfred Kastler - B.P. 20722 cedex 3 Nantes F-44307 France

Lead times and their variability have a key role to play in multi-component assembly systems, directly impacting their performance. They are rarely known exactly in advance, being generated by various sources of uncertainty. This paper focuses on the stochastic solution of the replenishment planning problem of a single-level assembly system, in the framework of which: (i) procurement decisions must be made before the fixed demands are realized, and (ii) backlogs are authorized. By approaching this problem in the context of stochastic programming, we discuss the value of (stochastic) information for, subsequently, characterizing and better apprehending the grade of stochasticity and its effect on the corresponding solutions. © 2017

关键词： assembly system random lead time replenishment planning problem two-stage stochastic programming value of information

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Capacities-based distant-water fishery cold chain network design considering yield uncertainty and demand dynamics 5

Capacities-based distant-water fishery cold chain network de...

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2017 International Conference on Progress in Informatics and Computing(PIC)

作者： Xiangqun Song Qianli Ma Wenyuan Wang Yun Peng State Key Laboratory of Coastal and Offshore Engineering Dalian University of Technology

ISBN: (纸本)9781538619797;9781538619780

In distant-water fishing industry, production, supply and distribution activities are realized in a dynamic environment including uncertainties of resources in fishing grounds and demands from global markets. Moreover, the capacity of the port cold storage is of great importance to the cold chain network as most of catch is handled and temporarily stored at seaports. Here, a multi-product, three-echelon and multiperiod network model is applied to a distant-water fishery cold chain design problem based on capacities. This network-design includes optimal cold storage facility locations and optimal flow amounts. And a two-stage stochastic programming method is used to handle the uncertainties.

关键词： cold storage capacity network optimization distant-water fishery uncertainty two-stage stochastic programming

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

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Journal of Industrial Engineering International 2017年第4期13卷 445-453页

作者： Yahyaei, Mohsen Bashiri, Mahdi Department of Industrial Engineering Iran University of Science and Technology Tehran Iran Department of Industrial Engineering Faculty of Engineering Shahed University Tehran Iran

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. © 2017, The Author(s).

关键词： Multiple cuts Benders decomposition Reliable hub location problem Sample average approximation two-stage stochastic programming

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Short-Term Scheduling of Microgrids in the Presence of Demand Response

Short-Term Scheduling of Microgrids in the Presence of Deman...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

作者： Talari, Saber Shafie-khah, Miadreza Haghifam, Mahmoud R. Yazdaninejad, Mohsen Catalao, Joao P. S. C MAST UBI Porto Portugal Tarbiat Modares Univ Tehran Iran Univ Semnan Semnan Iran INESC TEC Porto Portugal C MAST UBI FEUP Porto Portugal INESC ID IST UL Lisbon Portugal

ISBN: (纸本)9781538619537

In this paper, operation management of microgrids is performed. To do so, some contingencies including outage of distributed generators (DG), energy storage (ES) and the upstream network are considered. Since the microgrids have suitable capabilities in terms of control and communication, demand response reserve can be applied to improve the operation management. Using Monte Carlo simulation method and Markov chain, several scenarios are generated to show the possible contingencies in various hours. Then, a scenario reduction method is used for reducing the number of scenarios. Finally, a two-stage stochastic model is applied to solve a day-ahead scheduling problem in mixed-integer linear programming by GAMS. Consequently, the effect of demand response in the reduction of operation cost is demonstrated.

关键词： Demand response microgrid security-constrained unit commitment two-stage stochastic programming

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Sizing of energy storage systems considering uncertainty on demand and generation

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IFAC-PapersOnLine 2017年第1期50卷 8861-8866页

作者： Bucciarelli M. Giannitrapani A. Paoletti S. Vicino A. Zarrilli D. Dipartimento di Ingegneria dell'Informazione e Scienze Matematiche Università di Siena via Roma 56 Siena 53100 Italy

Over recent years there has been a general consensus about the necessary changes towards modernizing the existing power grid to meet environmental and socio-economic objectives. The adoption of low carbon technologies is a milestone in this process. On the other hand, the massive and uncoordinated connection of distributed generators (e.g. solar or wind) is making the operation of electrical distribution networks more challenging, e.g. causing energy balancing problems or voltage violations. Energy storage systems represent a possible means to cope with these issues. In this paper, we consider the problem of sizing the energy storage systems installed in a low voltage network with the aim of preventing voltage violations along the feeders. Since the problem is solved at the planning stage, when future realizations of demand and generation are unknown, we adopt a two-stage stochastic formulation where daily demand and generation profiles are modelled as random processes. The cost function to be minimized takes into account installation and operation costs related to storage use. By taking a scenario-based approach, the two-stage problem is approximated via a multi-scenario optimal power flow. To reduce the computational burden of the latter problem, a heuristic strategy consisting of solving separately a sizing problem for each scenario, and then combining the solutions of the single problems through a worst-case criterion, is proposed. The multi-scenario approach and the heuristic strategy are compared in terms of both computation time and quality of the solution using real data from an Italian low voltage network with photovoltaic generation. © 2017

关键词： distribution network Energy storage sizing scenario-based approach two-stage stochastic programming voltage control

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Progressive Hedging and Sample Average Approximation for the two-stage stochastic Traveling Salesman Problem 6

Progressive Hedging and Sample Average Approximation for the...

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6th International Conference on Operations Research and Enterprise Systems (ICORES)

作者： Adasme, Pablo Leung, Janny Soto, Ismael Univ Santiago Chile Dept Ingn Elect Ave Ecuador 3519 Santiago Chile Chinese Univ Hong Kong Shaw Coll 2001 Longxiang Blvd Shenzhen Peoples R China

ISBN: (纸本)9789897582189

In this paper, we propose an adapted version of the progressive hedging algorithm (PHA) (Rockafellar and Wets, 1991;Lokketangen and Woodruff, 1996;Watson and Woodruff, 2011) for the two-stage stochastic traveling salesman problem (STSP) introduced in (Adasme et al., 2016). Thus, we compute feasible solutions for small, medium and large size instances of the problem. Additionally, we compare the PHA method with the sample average approximation (SAA) method for all the randomly generated instances and compute statistical lower and upper bounds. For this purpose, we use the compact polynomial formulation extended from (Miller et al., 1960) in (Adasme et al., 2016) as it is the one that allows us to solve large size instances of the problem in short CPU time with CPLEX. Our preliminary numerical results show that the results obtained with the PHA algorithm are tight when compared to the optimal solutions of small and medium size instances. Moreover, we obtain significantly better feasible solutions than CPLEX for large size instances with up to 100 nodes and 10 scenarios in significantly low CPU time. Finally, the bounds obtained with SAA method provide an average reference interval for the stochastic problem.

关键词： two-stage stochastic programming Traveling Salesman Problem Progressive Hedging Algorithm Sample Average Approximation Method

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Assessment of Ancillary Service Demand Response and Time of Use in a Market-Based Power System Through a stochastic Security Constrained Unit Commitment 8th

Assessment of Ancillary Service Demand Response and Time of ...

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8th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS)

作者： Talari, Saber Shafie-Khah, Miadreza Hajibandeh, Neda Catalao, Joao P. S. Univ Beira Interior C MAST P-6201001 Covilha Portugal Univ Porto INESC TEC P-4200465 Porto Portugal Univ Porto Fac Engn P-4200465 Porto Portugal Univ Lisbon Inst Super Tecn INESC ID P-1049001 Lisbon Portugal

ISBN: (纸本)9783319560779

In this paper, the impacts of an incentive-based Demand Response, i.e., Ancillary Service DR (ASDR), and a price-based DR, i.e., Time of Use (ToU), are revealed in a restructured power system which has some wind farms. This network is designed based on the pre-emptive market which is a day-ahead market with a balancing market prognosis. It is a proper mechanism to deal with the stochastic nature of non-dispatchable and outage of all units of the network. With Monte Carlo Simulation (MCS) method, several scenarios are generated in order to tackle the variability and uncertainties of the wind farms generation. The impacts of merging ASDR and ToU are investigated through running a two-stage stochastic security constrained unit commitment (SCUC), separately.

关键词： Ancillary service demand response Security constrained unit commitment Time of Use two-stage stochastic programming

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Optimal Bidding Strategy for a Smart Microgrid in Day-Ahead Electricity Market with Demand Response Programs Considering Uncertainties

Optimal Bidding Strategy for a Smart Microgrid in Day-Ahead ...

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Smart Grid Conference

作者： Salehpour, Mohammad Javad Tafreshi, Seyed Masoud Moghaddas Univ Guilan Fac Elect Engn Rasht Iran

ISBN: (纸本)9781538642795

This paper computes the optimal bids that the smart microgrid energy management system (SMEMS) submits to the day-ahead electricity market. This smart microgrid consists of dispatchable generation resources, renewable generation resources, storage system and the loads that can be participate in the demand response (DR) programs. In this study we intend to maximize the expected profit earned by trading in day-ahead electricity market as well as optimal scheduling of smart microgrid for energy dispatching on the operating day. The bidding problem can be difficult due to different uncertainties in generations, loads and market prices forecasts amounts. To deal with these uncertainties, two-stage stochastic programming is employed. Various stochastic scenarios are generated by Monte Carlo simulation and then a scenario reduction algorithm based on kantorovich distance is performed. Nonlinear terms of the objective function are recast into linear forms. Numerical results have confirmed the profitability of the proposed smart microgrid.

关键词： Smart microgrid Bidding problem Demand response (DR) programs two-stage stochastic programming Uncertainty

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Random lead times in replenishment planning for single-level assembly systems: The value of information

Random lead times in replenishment planning for single-level...

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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Borodin, Valeria Hnaien, Faicel Dolgui, Alexandre Ecole Mines St Etienne CMP Georges Charpak CNRS UMR LIMOS 6158 F-13541 Gardanne France Univ Technol Troyes UMR CNRS 8261 Charles Delaunay Inst Lab Ind Syst Optimizat 12 Rue Marie CurieCS 42060 F-10004 Troyes France IMT Atlantique LS2N UMR CNRS 6004 4 Rue Alfred KastlerBP 20722 F-44307 Nantes 3 France

关键词： assembly system random lead time replenishment planning problem two-stage stochastic programming value of information

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CLOSED-LOOP SUPPLY CHAIN NEtwoRK DESIGN UNDER DEMAND, RETURN AND QUALITY UNCERTAINTY

CLOSED-LOOP SUPPLY CHAIN NETWORK DESIGN UNDER DEMAND, RETURN...

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作者： KADIR BICE MIDDLE EAST TECHNICAL UNIVERSITY

学位级别：硕士

In this study, we focus on a closed-loop supply chain (CLSC) network design problem in the presence of uncertainty in demand quantities, return rates, and quality of the returned products. We formulate the problem as a two-stage stochastic mixed-integer program that maximizes the total expected profit. The first-stage decisions in our model are facility location and capacity decisions, and the second-stage decisions are production quantities and the forward/backward flows on the network. We solve the problem by using the L-shaped method in iterative and branch-and-cut frameworks. In order to improve the computational efficiency, we consider various strategies such as adding mean-value cuts to the restricted master problem and generating multiple cuts instead of a single cut at each iteration or at each integer feasible solution. We use our numerical results to estimate the value of the stochastic solution and the expected value of perfect information in different problem settings.

关键词： Closed-loop supply chains network design under uncertainty two-stage stochastic programming L-shaped method branch-and-cut

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