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Manufacturing network configuration in supply chains with product recovery

OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2009年第4期37卷 757-769页

作者： Francas, David Minner, Stefan Univ Mannheim Dept Logist D-6800 Mannheim 1 Germany Univ Vienna Fac Business Econ & Stat A-1010 Vienna Austria

Efficient implementation of product recovery requires appropriate network structures. In this paper, we study the network design problem of a firm that manufactures new products and remanufactures returned products in its facilities. We examine the capacity decisions and expected performance of two alternative manufacturing network configurations when demand and return flows are both uncertain. Concerning the market structure, we further distinguish between the case where newly manufactured and remanufactured products are sold on the same market and the case where recovered products have to be sold on a secondary market. We consider network structures where manufacturing and remanufacturing are both conducted in common plants as well as structures that pool all remanufactoring activities in a separate plant. The underlying decision problems are formulated as two-stage stochastic programs with recourse. Based on numerical studies with normally distributed demands and returns, we show that particularly network size, investment costs of (re-)manufacturing capacity, and market structure have a strong impact oil the choice of a network configuration. Concerning the general role of manufacturing configuration in a system with product recovery, our results indicate that the investigated structures can lead to very different expected profits. We also examine the sensitivity of network performance to changes in return volumes, return variability and correlation between return and demand. Based on these results, we find that integrated plants are more beneficial in the common market setting. This relative advantage tends to diminish when demand is segmented, thus investing in more specialized, dedicated resources should be considered. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Product recovery network configuration Manufacturing and remanufacturing capacity Manufacturing flexibility stochastic linear programming

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Planning the supply of rewards with cooperative promotion considerations in coalition loyalty programmes management

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2015年第7期66卷 1140-1154页

作者： Cao, Yuheng Nsakanda, Aaron L. Diaby, Moustapha Carleton Univ Ottawa ON K1S 5B6 Canada Univ Connecticut Storrs CT USA

Coalition loyalty programmes (CLPs) are owned and operated as for-profit enterprises. We consider the ordering decisions of rewards that arise in this context, under a general setting in which not only is the demand for rewards uncertain, but also the CLP firm offers bonus points, a very common cooperative promotion mechanism used in loyalty programmes. The rewards are acquired either at a wholesale 'discounted' cost or at a wholesale 'non-discounted' cost by the CLP firm from its multiple commercial partners and supplied to customers seeking to redeem their accumulated 'reward points', subject to commercial partners' capacities for offering rewards, the firm's overall budget for purchasing rewards, and its control policy on points liability. We formulate the problem as a stochastic linear programme with recourse and solve it using a sampling-based heuristic solution procedure previously discussed in the literature. We report on the managerial applicability of our model in dealing with the redemption budget spending resulting from changes in demand variability, changes in the redemption budget, and the control of liability levels within a reasonable range.

关键词： loyalty reward programmes aggregate planning stochastic linear programming optimization supply chain management

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An efficient interactive framework for improving resilience of power-water distribution systems with multiple privately-owned microgrids

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2020年 116卷 105550-000页

作者： Najafi, Javad Peiravi, Ali Anvari-Moghaddam, Amjad Guerrero, Josep. M. Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Razavi Khorasan Iran Aalborg Univ Dept Energy Technol Aalborg Denmark

Resilience improvement of power distribution networks against natural disasters is an important problem. Water network similar to other important infrastructures depends on power networks. In this paper, resilience improvement is defined as increasing the users' accessibility to water and power after natural disasters. Microgrids with appropriate operation can provide energy to restore disconnected loads in distribution networks. In the proposed interactive framework, a stochastic energy management program for microgrids is designed that not only determines the amount of energy can be delivered to distribution systems, but also considers the reliability of local loads during emergency conditions. Each microgrid provides a list of bid-quantity energy blocks to the distribution system operator (DSO) during the emergency period. Then, the DSO chooses the best plan to restore disconnected loads considering inaccessibility values to power and water and also the damage of power and water distribution networks. Demand response actions in microgrids are also considered as effective tools for the energy management program, and their impact on the distribution system resilience is investigated. The proposed model is tested on the modified IEEE 33-bus distribution system with multiple microgrids, and the effectiveness of the proposed method is validated accordingly.

关键词： Microgrids Natural disasters Resilience stochastic linear programming Water network

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Resilience improvement planning of power-water distribution systems with multiple microgrids against hurricanes using clean strategies

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JOURNAL OF CLEANER PRODUCTION 2019年 223卷 109-126页

作者： Najafi, Javad Peiravi, Ali Anvari-Moghaddam, Amjad Guerrero, Josep M. Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Razavi Khorasan Iran Aalborg Univ Dept Energy Technol Aalborg Denmark

This paper proposes a comprehensive planning framework including a main problem and two sub-problems to enhance the resilience of power distribution network (PDN) and water distribution network (WDN) with multiple microgrids against hurricanes. The main problem which is formulated in stochastic programming aims to minimize the investment cost of resilience improvement strategies and the expected inaccessibility values of loads to power and water under hurricanes. Line hardening in PDN, upgrading the energy storage size in microgrids and water tanks in WDN are considered as three clean candidate strategies. In analyzing each scenario of the main problem, the microgrids which are connected to the PDN are modeled as emergency sources through the first stochastic sub -problem that can restore disconnected loads and water pumps. Water pumps as critical loads are equipped with emergency generators with limited fuel capacity. If there are some water pumps which cannot be restored in each scenario of the main problem, their emergency generators will be scheduled with the second subproblem of the model. The proposed model is tested on the modified IEEE 33-bus PDN with multiple microgrids and a designed WDN, and the effectiveness of the proposed method is validated accordingly. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Microgrids Resilience improvement planning stochastic linear programming Power network Water network

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Generalized adaptive partition-based method for two-stage stochastic linear programs : Geometric oracle and analysis

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OPERATIONS RESEARCH LETTERS 2022年第4期50卷 452-457页

作者： Forcier, Mail Leclere, Vincent Ecole Ponts CERMICS Marne France

Adaptive Partition-based Methods (APM) are numerical methods that solve, in particular, two-stage stochastic linear problems (2SLP). We say that a partition of the uncertainty space is adapted to the current first stage control x over titlde if we can aggregate scenarios while conserving the true value of the expected recourse cost at x over titlde. The core idea of APM is to iteratively construct an adapted partition to all past tentative first stage controls. Relying on the normal fan of the dual admissible set, we give a necessary and sufficient condition for a partition to be adapted even for non-finite distribution, and provide a geometric method to obtain an adapted partition. Further, by showing the connection between APM and the L-shaped algorithm, we prove convergence and complexity bounds of the APM methods. The paper presents the fixed recourse case and ends with elements to forgo this assumption. (C) 2022 Elsevier B.V. All rights reserved.

关键词： stochastic linear programming Exact method Adaptive partition methods

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Note on "A new equivalent transformation for interval inequality constraints of interval linear programming"

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FUZZY OPTIMIZATION AND DECISION MAKING 2019年第2期18卷 259-262页

作者： Li, Dechao Shi, Jiaheng Huang, Hongying Zhejiang Ocean Univ Sch Math Phys & Informat Sci Zhoushan 316000 Peoples R China Key Lab Oceanog Big Data Min & Applicat Zhejiang Zhoushan 316022 Peoples R China

This note provides a counterexample to demonstrate some flaws in a recent paper by Chen et al. It pinpoints the logic error in the proof of Theorem 5.2 and discusses some remedial works.

关键词： Interval linear programming Modeling the interval uncertainty Uniform distribution stochastic linear programming

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Risk Averse Scheduling by a PEV Aggregator Under Uncertainty

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IEEE TRANSACTIONS ON POWER SYSTEMS 2015年第2期30卷 882-891页

作者： Momber, Ilan Siddiqui, Afzal Gomez San Roman, Tomas Soder, Lennart Comillas Univ Inst Res Technol IIT Madrid 28015 Spain KTH Royal Inst Technol Dept Elect Power Syst EPS Sch Elect Engn S-10044 Stockholm Sweden UCL Dept Stat Sci London WC1E 6BT England Stockholm Univ Dept Comp & Syst Sci DSV SE-16440 Kista Sweden KTH Royal Inst Technol Dept Elect Power Syst EPS S-10044 Stockholm Sweden

Research on electric power systems has considered the impact of foreseeable plug-in electric vehicle (PEV) penetration on its regulation, planning, and operation. Indeed, detailed treatment of PEV charging is necessary for efficient allocation of resources. It is envisaged that a coordinator of charging schedules, i.e., a PEV aggregator, could exercise some form of load control according to electricity market prices and network charges. In this context, it is important to consider the effects of uncertainty of key input parameters to optimization algorithms for PEV charging schedules. However, the modeling of the PEV aggregator's exposure to profit volatility has received less attention in detail. Hence, this paper develops a methodology to maximize PEV aggregator profits taking decisions in day-ahead and balancing markets while considering risk aversion. Under uncertain market prices and fleet mobility, the proposed two-stage linear stochastic program finds optimal PEV charging schedules at the vehicle level. A case study highlights the effects of including the conditional value-at-risk (CVaR) term in the objective function and calculates two metrics referred to as the expected value of aggregation and flexibility.

关键词： Conditional value-at-risk (CVaR) optimal PEV charging schedule plug-in electric vehicle (PEV) aggregator risk aversion stochastic linear programming

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Volumetric Barrier Cutting Plane Algorithms for stochastic linear Semi-Infinite Optimization

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IEEE ACCESS 2020年 8卷 4995-5008页

作者： Alzalg, Baha Gafour, Asma Alzaleq, Lewa Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA Univ Jordan Dept Math Amman 11942 Jordan Washington State Univ Dept Math & Stat Pullman WA 99164 USA

In this paper, we study the two-stage stochastic linear semi-infinite programming with recourse to handle uncertainty in data defining (deterministic) linear semi-infinite programming. We develop and analyze volumetric barrier cutting plane interior point methods for solving this class of optimization problems, and present a complexity analysis of the proposed algorithms. We establish our convergence analysis by showing that the volumetric barrier associated with the recourse function of stochastic linear semi-infinite programs is a strongly self-concordant barrier and forms a self-concordant family on the first-stage solutions. The dominant terms in the complexity expressions obtained in this paper are given in terms of the problem dimension and the number of realizations. The novelty of our algorithms lies in their ability to kill the effect of the radii of the largest Euclidean balls contained in the feasibility sets on the dominant complexity terms.

关键词： Semi-infinite programming stochastic linear programming interior-point methods volumetric barrier cutting plane

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stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market

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ENERGY 2017年 124卷 310-320页

作者： Gomes, I. L. R. Pousinho, H. M. I. Melicio, R. Mendes, V. M. F. Univ Lisbon Inst Super Tecn IDMEC Lisbon Portugal Univ Evora Escola Ciencias & Tecnol Dept Fis Evora Portugal Inst Super Engn Lisboa Dept Elect Engn & Automat Lisbon Portugal

This paper presents an optimal bid submission in a day-ahead electricity market for the problem of joint operation of wind with photovoltaic power systems having an energy storage device. Uncertainty not only due to the electricity market price, but also due to wind and photovoltaic powers is one of the main characteristics of this submission. The problem is formulated as a two-stage stochastic programming problem. The optimal bids and the energy flow in the batteries are the first-stage variables and the energy deviation is the second stage variable of the problem. Energy storage is a way to harness renewable energy conversion, allowing the store and discharge of energy at conveniently market prices. A case study with data from the Iberian day-ahead electricity market is presented and a comparison between joint and disjoint operations is discussed. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Joint operation Day-ahead market Energy storage PV power stochastic linear programming Wind power

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PRIMAL-DUAL AGGREGATION AND DISAGGREGATION FOR stochastic linear-PROGRAMS

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MATHEMATICS OF OPERATIONS RESEARCH 1994年第4期19卷 893-908页

作者： WRIGHT, SE Department of Mathematics & Statistics Miami University Oxford Ohio 45056

A multistage stochastic linear program can be approximated by replacing the underlying information structure by a coarser structure. Given the ordinary Lagrangian for the original problem, this amounts to restricting both the primal and dual variables to be adapted to the coarser information structure. The resulting primal problem has the same form as the original, but with aggregated constraints and decisions. Mutual upper and lower bounds on the optimal values of the original and aggregated problems are obtained via partially aggregated problems formed by restricting only the primal variables or only the dual variables to the coarser structure. The introduction of the partially aggregated problems leads to a general disaggregation framework for developing heuristic approaches to solving the original problem.

关键词： MULTISTAGE stochastic programming stochastic linear programming AGGREGATION LAGRANGIAN DUALITY

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