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Modeling an Inventory Routing Problem for perishable products with environmental considerations and demand uncertainty

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2015年 164卷 118-133页

作者： Soysal, Mehmet Bloemhof-Ruwaard, Jacqueline M. Haijema, Rene van der Vorst, Jack G. A. J. Wageningen Univ Operat Res & Logist NL-6706 KN Wageningen Netherlands

The transition to sustainable food supply chain management has brought new key logistical aims such as reducing food waste and environmental impacts of operations in the supply chain besides the traditional cost minimization objective. Traditional assumptions of constant distribution costs between nodes, unlimited product shelf life and deterministic demand used in the Inventory Routing Problem (IRP) literature restrict the usage of the proposed models in current food logistics systems. From this point of view, our interest in this study is to enhance the traditional models for the IRP to make them more useful for the decision makers in food logistics management. Therefore, we present a multi-period IRP model that includes truck load dependent (and thus route dependent) distribution costs for a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand. A case study on the fresh tomato distribution operations of a supermarket chain shows the applicability of the model to a real-life problem. Several variations of the model, each differing with respect to the considered aspects, are employed to present the benefits of including perishability and explicit fuel consumption concerns in the model. The results suggest that the proposed integrated model can achieve significant savings in total cost while satisfying the service level requirements and thus offers better support to decision makers. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Inventory routing Greenhouse gas emissions Energy consumption Perishability chance-constrained programming

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The Price Decision And Return Policy For E-business In A Fuzzy Environment 27

The Price Decision And Return Policy For E-business In A Fuz...

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27th Chinese Control and Decision Conference (CCDC)

作者： Ai, Ying Huang, Min Lu, Licai Shenyang Jianzhu Univ Sch Sci Shenyang 110168 Liaoning Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China

ISBN: (纸本)9781479970162

The price decision and return policy for e-business is studied in a fuzzy environment. The demand and cost are uncertain, which are described as fuzzy variable. A maximize expectation profit model with risk neutral e-tailer and a chance-constrained programming model with risk averse e-tailer are proposed. Through a numerical example some insights to management are obtained.

关键词： return policy pricing e-business chance-constrained programming fuzzy variable

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chance-constrained programming : a Tool for Solving Linear Eddy Current Inverse Problem

Chance-Constrained Programming : a Tool for Solving Linear E...

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13th International Workshop on Electromagnetic Nondestructive Evaluation (ENDE)

作者： Zorgati, Riadh Duchene, Bernard Univ Paris 11 Dept Rech Electromagnetisme Lab Signaux & Syst CNRSSupelec 3 Rue Joliot Curie F-91192 Gif Sur Yvette France EDF R&D Paris France

ISBN: (纸本)9781607504429;9781607500230

This paper deals with the application of chance-constrained programming to eddy current inverse problems, linearized in the Born approximation framework. It suggests two probabilistic formulations of this linear inverse problem: the first one uses joint chance constraints and the second one is based upon individual chance constraints;the latter allows a layer-by-layer reconstruction suitable for taking attenuation into account. The paper illustrates how structural properties of chance constraints are a powerful tool for dealing with the ill-posed nature of the problem. Two situations are considered: i) the first one concerns a flaw made of a simple conductivity contrast and an underlying random process belonging to the class of elliptically symmetric distributions;in that case, a deterministic equivalence of the problem can be found provided that a suitable level of probability is chosen, ii) the second situation concerns a notch;a tractable approximate algorithm based upon the Hoeffding inequality is suggested for solving the inverse problem in that case.

关键词： Eddy Current Linear Inverse Problem chance-constrained programming

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Using integer programming for balancing return and risk in problems with individual chance constraints

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COMPUTERS & OPERATIONS RESEARCH 2014年第Sep.期49卷 59-70页

作者： Shen, Siqian Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA

In this paper, we study probabilistically constrained problems involving individual chance constraints, random univariate right-hand sides, and risk tolerances defined as decision variables which affect part of the objective function. Built on the concept of efficient points, we formulate the problems as mixed-integer programs by using binary variables to determine an optimal risk tolerance for each chance constraint. We develop two benchmark approaches, both of which solve chance-constrained programs with fixed risk values in a bisection algorithm or by enumeration. We specify our approaches for a minimum cost flow problem and a network capacity design problem, both of which involve chance constraints for bounding the risk of demand shortages. We test instances with diverse size and complexity of the two network problems, and demonstrate the computational efficacy as well as give managerial insights. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： chance-constrained programming Risk management Mixed-integer programming Minimum cost flow Network capacity design

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An Evaluation of Post Conservation Reserve Program Alternatives In The Texas High Plains

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Journal of Agricultural and Applied Economics 2015年第2期27卷 556-564页

作者： Phillip N. Johnson Eduardo Segarra Department of Agricultural Economics Texas Tech University Lubbock Texas

Four policy alternatives for CRP lands upon expiration of the current contracts in Hale County, Texas are evaluated using chance-constrained programming. It was found that if CRP contracts are extended at the current average rental rate, 40 percent of the current enrollment would be expected to return to crop production, while 66 percent would return to crop production if the program were eliminated. The results also indicate that the marginal value of CRP payments to producers is lower than the marginal value of deficiency payments.

关键词： Conservation Reserve Program soil erosion chance-constrained programming

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Uncertainty Management in Remanufacturing Decisions: A Consideration of Uncertainties in Market Demand, Quantity, and Quality of Returns

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ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING 2015年第2期1卷 021007页

作者： Mashhadi, A. Raihanian Esmaeilian, Behzad Behdad, Sara SUNY Buffalo Mech & Aerosp Engn Dept Buffalo NY 14260 USA Northeastern Univ Mech & Ind Engn Dept Boston MA 02115 USA SUNY Buffalo Mech & Aerosp Engn Dept Ind & Syst Engn Dept Buffalo NY 14260 USA

As market demand for remanufactured products increases and environmental legislation puts further enforcement on original equipment manufacturers (OEMs), remanufacturing is becoming an important business. However, profitability of salvaging operations is still a challenge in remanufacturing industry. Several factors influence the cost effectiveness of remanufacturing operations, including uncertainties in the quantity of return flows and market demand as well as variability in the quality of received items. The objective of this paper is to develop a stochastic optimization model based on chance-constrained programming to deal with these sources of uncertainties in take-back and inventory planning systems. The main purpose of the model is to determine the best upgrade level for a received product with certain quality level with the aim of maximizing profit. An example of personal computer is provided to show the application of the method.

关键词： remanufacturing market end-of-use product recovery upgrade planning chance-constrained programming

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SRCCP: A stochastic robust chance-constrained programming model for municipal solid waste management under uncertainty

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RESOURCES CONSERVATION AND RECYCLING 2009年第6期53卷 352-363页

作者： Xu, Y. Huang, G. H. Qin, X. S. Cao, M. F. Univ Regina Fac Engn Environm Syst Engn Program Regina SK S4S 0A2 Canada N China Elect Power Univ Sino Canada Ctr Energy & Environm Res Beijing 102206 Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn Singapore 639798 Singapore

A hybrid stochastic robust chance-constraint programming (SRCCP) model was developed in this study for supporting municipal solid waste management under uncertainty. The method improves upon the existing robust-optimization (RO) and chance-constraint programming (CCP) approaches by allowing analysis on trade-offs among expected value of the objective function, variation in the value of the objective function and the risk of violating constraints that contain uncertain parameters. SRCCP could be used to examine the balance between solution robustness and model robustness. and was especially useful for analyzing the reliability of satisfying (or risk of violating) system constraints under complex uncertainties. A long-term municipal solid waste management problem was used to demonstrate the applicability of SRCCP, with violations for capacity constraints being assumed under various significance levels. The study results demonstrated that a higher system cost may guarantee that waste-management requirements and environmental criteria be met, and a lower cost may lead to a higher risk of violating the related regulations. The proposed SRCCP model could be used by waste managers for identifying desired waste-management policies under various environmental, economic, and system-reliability constraints and complex uncertainties. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Robust optimization chance-constrained programming Environment Compromise programming Solid waste management Uncertainty

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Application of chance-constrained programming for stochastic group shop scheduling problem

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2009年第3-4期42卷 321-334页

作者： Ahmadizar, Fardin Ghazanfari, Mehdi Ghomi, Seyyed Mohammad Taghi Fatemi Iran Univ Sci & Technol Dept Ind Engn Tehran *** Iran Amirkabir Univ Technol Dept Ind Engn Tehran Iran

In this paper, we study a group shop scheduling (GSS) problem subject to uncertain release dates and processing times. The GSS problem is: a general formulation including the other shop scheduling problems such as the flow shop, the job shop, and the open shop scheduling problems. The objective is to find a job schedule which minimizes the total weighted completion time. We solve this problem based on the chance-constrained programming. First, the problem is fomulated in a form of stochastic programming and then prepared in a form of deterministic mixed binary integer linear programming such that it can be solved by a linear programming solver. To solve the problem efficiently, we develop an efficient hybrid method. Exploiting a heuristic algorithm in order to satisfy the constraints, an ant colony optimization algorithm is applied to construct high-quality solutions to the problem. The proposed approach is tested on instances where the random variables are normally, uniformly, or exponentially distributed.

关键词： Group shops scheduling Uncertain release dates and processing times Total weighted completion time chance-constrained programming Ant colony algorithm Heuristic algorithm

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Two-stage fuzzy chance-constrained programming: application to water resources management under dual uncertainties

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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2009年第3期23卷 349-359页

作者： Guo, P. Huang, G. H. Univ Waterloo Dept Civil & Environm Engn Waterloo ON N2L 3G1 Canada Univ Regina Environm Syst Engn Program Regina SK S4S 0A2 Canada

In this study, a two-stage fuzzy chance-constrained programming (TFCCP) approach is developed for water resources management under dual uncertainties. The concept of distribution with fuzzy probability (DFP) is presented as an extended form for expressing uncertainties. It is expressed as dual uncertainties with both stochastic and fuzzy characteristics. As an improvement upon the conventional inexact linear programming for handling uncertainties in the objective function and constraints, TFCCP has advantages in uncertainty reflection and policy analysis, especially when the input parameters are provided as fuzzy sets, probability distributions and DFPs. TFCCP integrates the two-stage stochastic programming (TSP) and fuzzy chance-constrained programming within a general optimization framework. TFCCP incorporates the pre-regulated water resources management policies directly into its optimization process to analyze various policy scenarios;each scenario has different economic penalty when the promised amounts are not delivered. TFCCP is applied to a water resources management system with three users. Solutions from TFCCP provide desired water allocation patterns, which maximize both the system's benefits and feasibility. The results indicate that reasonable solutions were generated for objective function values and decision variables, thus a number of decision alternatives can be generated under different levels of stream flows, alpha-cut levels and fuzzy dominance indices.

关键词： chance-constrained programming Decision making Fuzzy Uncertainty Water resources

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An inexact double-sided chance-constrained model for air quality management in Nanshan District, Shengzhen, China

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ENGINEERING OPTIMIZATION 2014年第12期46卷 1694-1708页

作者： Shao, Liguo Xu, Ye Huang, Guohe China Ctr Informat Ind Dev Beijing Peoples R China North China Elect Power Univ MOE Key Lab Reg Energy & Environm Syst Optimizat Sinocanada Resources & Environm Res Acad Beijing Peoples R China

In this study, an inexact double-sided fuzzy-random-chance-constrained programming (IDSFRCCP) model was developed for supporting air quality management of the Nanshan District of Shenzhen, China, under uncertainty. IDSFRCCP is an integrated model incorporating interval linear programming and double-sided fuzzy-random-chance-constrained programming models. It can express uncertain information as both fuzzy random variables and discrete intervals. The proposed model was solved based on the stochastic and fuzzy chance-constrained programming techniques and an interactive two-step algorithm. The air quality management system of Nanshan District, including one pollutant, six emission sources, six treatment technologies and four receptor sites, was used to demonstrate the applicability of the proposed method. The results indicated that the IDSFRCCP was capable of helping decision makers to analyse trade-offs between system cost and risk of constraint violation. The mid-range solutions tending to lower bounds with moderate alpha(h) and q(i) values were recommended as decision alternatives owing to their robust characteristics.

关键词： chance-constrained programming interval linear programming air quality management uncertainty

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