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A possibilistic programming approach for closed-loop supply chain network design under uncertainty

FUZZY SETS AND SYSTEMS 2010年第20期161卷 2668-2683页

作者： Pishvaee, M. S. Torabi, S. A. Univ Tehran Dept Ind Engn Coll Engn Tehran Iran

The design of closed-loop supply chain networks has attracted more attention in recent years according to business and environmental factors. The significance of accounting for uncertainty and risk in such networks spurs an interest to develop appropriate decision making tools to cope with uncertain and imprecise parameters in closed-loop supply chain network design problems. This paper proposes a hi-objective possibilistic mixed integer programming model to deal with such issues. The proposed model integrates the network design decisions in both forward and reverse supply chain networks, and also incorporates the strategic network design decisions along with tactical material flow ones to avoid the sub-optimalities led from separated design in both parts. To solve the proposed possibilistic optimization model, an interactive fuzzy solution approach is developed by combining a number of efficient solution approaches from the recent literature. Numerical experiments are conducted to demonstrate the significance and applicability of the developed possibilistic model as well as the usefulness of the proposed solution approach. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Fuzzy mathematical programming Closed-loop supply chain network design possibilistic programming Fuzzy multi-objective optimization

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A STOCHASTIC possibilistic programming-MODEL FOR BANK HEDGING DECISION-PROBLEMS

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FUZZY SETS AND SYSTEMS 1993年第3期57卷 351-363页

作者： LAI, YJ HWANG, CL Department of Industrial Engineering Kansas State University Manhattan KS 66506 USA

For a practical bank hedging decision optimization problem, interest rates and price of futures contract may involve both fuzziness and randomness. For subjective nature of satisfaction, maximum desired values of loan demand, deposit supply and ratio of desired loan to deposit are often fuzzy. In this study, we consider and solve a stochastic possibilistic programming model of bank hedging decision problems with the above characters. We first use the expected value to obtain an auxiliary possibilistic linear programming problem which is further resolved by use of beta-level cut. An (crisp) auxiliary bi-objective linear programming model is then proposed and solved by our augmented maximin approach. For illustration purpose. a numerical bank hedging decision problem is solved.

关键词： BALANCE-SHEET OPTIMIZATION BANK HEDGING DECISIONS LINGUISTIC INTEREST RATES UNDER MULTIPLE STATES STOCHASTIC possibilistic programming possibilistic programming MULTIPLE OBJECTIVE LINEAR programming AUGMENTED MAXIMIN

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Notes on "possibilistic programming approach for fuzzy multidimensional analysis of preference in group decision making"

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COMPUTERS & INDUSTRIAL ENGINEERING 2014年第1期73卷 1-4页

作者： Li, Deng-Feng Fuzhou Univ Sch Econ & Management Fuzhou 350108 Fujian Peoples R China

The aim of this note is to point out and correct some errors in the definitions, notations operations and possibilistic programming model introduced by Sadi-Nezhad and Akhtari (2008) and hereby develop two correct possibilistic programming models for fuzzy multidimensional analysis of preference in the fuzzy multiattribute group decision making problems with both the fuzzy weight vector and the fuzzy positive ideal solution (PIS) unknown a priori. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： possibilistic programming Linear programming techniques for multidimensional analysis of preference (LINMAP) Multiobjective linear programming Fuzzy multiattribute group decision making Fuzzy number

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Imprecise Project Network Scheduling Using possibilistic programming Approach

Imprecise Project Network Scheduling Using Possibilistic Pro...

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2014 International Conference on Fuzzy Theory and Its Applications

作者： Liang, Tien-Fu Lin, Hsueh-Mao Cheng, Hung-Wen Chen, Yi-Fen Hsiuping Univ Sci & Technol Dept Ind Engn & Management Taichung Taiwan

ISBN: (纸本)9781479945887

This work develops a possibilistic programming approach to solve imprecise project network scheduling (PNS) problems with multiple goals. The imprecise multi-objective PNS model designed here attempts to minimize total project costs and total completion time with reference to direct costs, indirect costs, contractual penalty costs, duration of activities and the constraint of available cost budget. An industrial case is used to demonstrate the feasibility of applying the proposed approach to real-life PNS problems. Several significant managerial implications for practical application of the proposed approach are also presented. The important contribution of this work lies in presenting a possibilistic mathematical programming methodology for solving the practical multi-objective PNS problems.

关键词： Project network scheduling Fuzzy sets possibilistic programming Multi-objective linear programming

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Fuzzy Random possibilistic programming Model for Multi-objective Problem

Fuzzy Random Possibilistic Programming Model for Multi-objec...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Nureize, A. Watada, J. Univ Tun Hussein Onn Malaysia Fac Comp Sci & Informat Technol Johor Baharu 86400 Malaysia Waseda Univ Grad Sch Informat Prod & Syst Kitakyushu Fukuoka 8080135 Japan

ISBN: (纸本)9781467329453

A real-life application faces various kinds of inherent uncertainties which occurs simultaneously. To find solution, formulating real world problem into mathematical programming model is challenging. Uncertain parameters in a problem model can be characterized as vagueness, ambiguous and random of the information. Such uncertainties make the existing multi-objective model incapable of handling such situations. Thus, in this paper we present the multi-objective decision model from the perspective of possibilistic programming approach to scrutinize the uncertainties in the decision making. The proposed concept can be used to build model for multi-objective problem which is exposed with various types of uncertainties. We include an illustrative example to explain the model, and highlight its advantages.

关键词： Multi-objective evaluation fuzzy random coefficient possibilistic programming necessity measure

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A possibilistic programming Approach for the Vehicle Routing Problem with Time Windows

A Possibilistic Programming Approach for the Vehicle Routing...

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2010 IEEE World Congress on Computational Intelligence

作者： Kilic, Sezgin Turkish AF Acad Dept Ind Engn TR-34149 Istanbul Turkey

ISBN: (纸本)9781424469208

This paper considers the vehicle routing problem with time windows where the uncertainties of travel times are modeled with possibility distributions. A possibilistic programming model is designed for the problem. Furthermore, an ant colony system algorithm is developed to solve the proposed model. Necessity measure is used to gain knowledge about the feasibility of generated solutions when they are realized. Finally, numerical examples are given to show the effectiveness and usefulness of the algorithm.

关键词： ant colony system algorithm mathematical programming possibilistic programming possibility distributions possibility theory time window transportation travel time uncertainties vehicle routing problem

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Sustainable supply chain network design problem: Using the integrated BWM, TOPSIS, possibilistic programming, and ε-constrained methods

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 168卷

作者： Lahri, Vijay Shaw, Krishnendu Ishizaka, Alessio Indian Sch Mines Indian Inst Technol Dept Management Studies Dhanbad 826004 Bihar India NEOMA Business Sch 1 Rue Marechal JuinBP 215 F-76825 Mont St Aignan France

This paper proposes a two-stage multi-objective possibilistic integer linear programming sustainable supply chain network design model, minimizing the economic, environmental goals and maximizing the social sustainability goals. The proposed model determines the openings of facilities and the amount of flow of goods across the supply chain. It introduces supplier green image factors in the design of the supply chain network. The model has considered epistemic uncertainty to model the unknown capacity, cost, and demand. The proposed study has been carried out in two stages. In the first stage, BWM (Best-Worst method) and TOPSIS are applied to evaluate the green image weights of suppliers. Further, these green weights are being used in the second phase for the supply chain network design. The study has adopted combined possibilistic programming and Epsilon (epsilon) constraint method, which was reported infrequently in the literature. Epsilon (epsilon) constraint method generates distinct Pareto-optimal solutions, which provided a large combination of the trade-off between the cost, emission, and social sustainability. The results facilitate decision-makers to take the decision in an uncertain environment.

关键词： possibilistic programming epsilon-Constraint method Green image Social sustainability Best-Worst method

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A possibilistic programming approach for the location problem of multiple cross-docks and vehicle routing scheduling under uncertainty

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ENGINEERING OPTIMIZATION 2013年第10期45卷 1223-1249页

作者： Mousavi, S. Meysam Tavakkoli-Moghaddam, Reza Jolai, Fariborz Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

This article considers the design of cross-docking systems under uncertainty in a model that consists of two phases: (1) a strategic-based decision-making process for selecting the location of cross-docks to operate, and (2) an operational-based decision-making process for vehicle routing scheduling with multiple cross-docks. This logistic system contains three echelons, namely suppliers, cross-docks and retailers, in an uncertain environment. In the first phase, a new multi-period cross-dock location model is introduced to determine the minimum number of cross-docks among a set of location sites so that each retailer demand should be met. Then, in the second phase, a new vehicle routing scheduling model with multiple cross-docks is formulated in which each vehicle is able to pickup from or deliver to more than one supplier or retailer, and the pickup and delivery routes start and end at the corresponding cross-dock. This article is the first attempt to introduce an integrated model for cross-docking systems design under a fuzzy environment. To solve the presented two-phase mixed-integer programming (MIP) model, a new fuzzy mathematical programming-based possibilistic approach is used. Furthermore, experimental tests are carried out to demonstrate the effectiveness of the presented model. The computational results reveal the applicability and suitability of the developed fuzzy possibilistic two-phase model in a variety of problems in the domain of cross-docking systems.

关键词： possibilistic programming fuzzy optimization cross-docking systems vehicle routing scheduling location mixed-integer programming model

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An enhanced possibilistic programming approach for reliable closed-loop supply chain network design

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2016年第5期54卷 1358-1387页

作者： Torabi, S. A. Namdar, J. Hatefi, S. M. Jolai, F. Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Shahrekord Univ Fac Engn Shahrekord Iran

Most of current logistics network design models in the literature typically assume that facilities are always available and absolutely reliable while in practice, they are always subject to several operational and disruption risks. This paper proposes a reliable closed-loop supply chain network design model, which accounts for both partial and complete facility disruptions as well as the uncertainty in the critical input data. The proposed model is of mixed integer possibilistic linear programming type that aims to minimise simultaneously the total cost of opening new facilities and the expected cost of disruption scenarios. An enhanced possibilistic programming approach is proposed to deal with the epistemic uncertainty in input data. Furthermore, the p-robustness criterion is used to limit the cost of disruption scenarios and protect the designed network against random facility disruptions. Several numerical experiments along with sensitivity analyses on uncertain parameters are conducted to illustrate the significance and applicability of the developed model as well as the effectiveness of the proposed solution approach. Our results demonstrate that operational and disruption risks considerably affect the whole structure of the designed network and they must be taken into account when designing a reliable closed-loop logistics network.

关键词： p-robustness possibilistic programming reliable closed-loop logistics network design disruption risks

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An interactive possibilistic programming approach for a multi-objective closed-loop supply chain network under uncertainty

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2014年第3期45卷 283-299页

作者： Fallah-Tafti, Alireza Sahraeian, Rashed Tavakkoli-Moghaddam, Reza Moeinipour, Masoud Shahed Univ Fac Engn Dept Ind Engn Tehran Iran Univ Tehran Coll Engn Dept Ind Engn Tehran Iran Khajeh Nasir Toosi Univ Technol Fac Mech & Ind Engn Dept Ind Engn Tehran Iran

In this article, we first propose a closed-loop supply chain network design that integrates network design decisions in both forward and reverse supply chain networks into a unified structure as well as incorporates the tactical decisions with strategic ones (e.g., facility location and supplier selection) at each period. To do so, various conflicting objectives and constraints are simultaneously taken into account in the presence of some uncertain parameters, such as cost coefficients and customer demands. Then, we propose a novel interactive possibilistic approach based on the well-known STEP method to solve the multi-objective mixed-integer linear programming model. To validate the presented model and solution method, a numerical test is accomplished through the application of the proposed possibilistic-STEM algorithm. The computational results demonstrate suitability of the presented model and solution method.

关键词： closed-loop supply chain network design possibilistic programming STEP method multiple-criteria decision making supplier selection

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