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Computing efficient solutions to fuzzy multiple objective linear programming problems

fuzzy SETS AND SYSTEMS 2006年第10期157卷 1328-1332页

作者： Li, XQ Zhang, B Li, H Cent S Univ Sch Math Sci & Comp Technol Changsha 410083 Peoples R China

In this paper, we improve the fuzzy compromise approach of Guu and Wu by automatically computing proper membership thresholds instead of choosing them. Indeed, in practice, choosing membership thresholds arbitrarily may result in an infeasible optimization problem. Although we can adjust minimum satisfaction degree to get fuzzy efficient solution, it sometimes makes the process of interaction more complicated. In order to overcome this drawback, a theoretically and practically more efficient two-phase max-min fuzzy compromise approach is proposed in this paper. Moreover, the efficiency of the two-phase approach is verified by an example. (C) 2005 Elsevier B.V. All rights reserved.

关键词： fuzzy multiple objective linear programming max-min operator approach fuzzy compromise approach two-phase approach

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An α-fuzzy goal approximate algorithm for solving fuzzy multiple objective linear programming problems

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SOFT COMPUTING 2007年第3期11卷 259-267页

作者： Lu, Jie Ruan, Da Wu, Fengjie Zhang, Guangquan Univ Technol Sydney Fac Informat Technol Broadway NSW 2007 Australia CEN SCK Belgian Nucl Res Ctr B-2400 Mol Belgium

multiple conflicting objectives in many decision making problems can be well described by multiple objective linear programming (MOLP) models. This paper deals with the vague and imprecise information in a multiple objective problem by fuzzy numbers to represent parameters of an MOLP model. This so-called fuzzy MOLP (or FMOLP) model will reflect some uncertainty in the problem solution process since most decision makers often have imprecise goals for their decision objectives. This study proposes an approximate algorithm based on a fuzzy goal optimization under the satisfactory degree alpha to handle both fuzzy and imprecise issues. The concept of a general fuzzy number is used in the proposed algorithm for an FMOLP problem with fuzzy parameters. As a result, this algorithm will allow decision makers to provide fuzzy goals in any form of membership functions.

关键词： optimization multiple objective linear programming fuzzy multiple objective linear programming approximate algorithm

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A compromise model for solving fuzzy multiple objective linear programming problems

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Journal of the Chinese Institute of Industrial Engineers 2001年第5期18卷 87-93页

作者： Wu, Yan-Kuen Guu, Sy-Ming Department of Industrial Management Van-Nun Institute of Technology 320 1 Van-Nung Road Chung-Li Tao-Yuan Taiwan Department of Information Management Yuan-Ze University United States

Two-phase approach had been proposed to generate an efficient solution for the multiple objective linear programming problems [MOLP]. In this research, we shall show a revised two-phase approach to the case of the fuzzy multiple objectives linear programming problems [FMOLP]. This revised model can improve the optimal decision obtained from min operator. Moreover, a compromise model embedded two-phase approach and average operator will be proposed to yield a fuzzy-efficient solution between non-compensatory and fully compensatory. More precisely, one compromise index to the membership function can be adjusted by decision-maker to reveal the way of change on degree of satisfaction for each objective and fuzzy constraint. One numerical example is employed to illustrate our assertions. © 2001 Taylor & Francis Group, LLC.

关键词： fuzzy multiple objective linear programming Two-phase approach

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A new approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters

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APPLIED MATHEMATICS AND COMPUTATION 2006年第1期174卷 524-544页

作者： Wu, FJ Lu, J Zhang, GQ Univ Technol Sydney Fac Informat Technol Broadway NSW 2007 Australia

Many business decision problems involve multiple objectives and can thus be described by multiple objective linear programming (MOLP) models. When a MOLP problem is being formulated, the parameters of objective functions and constraints are normally assigned by experts. In most real situations, the possible values of these parameters are imprecisely or ambiguously known to the experts. Therefore, it would be more appropriate for these parameters to be represented as fuzzy numerical data that can be represented by fuzzy numbers. In this paper, a new approximate algorithm is developed for solving fuzzy multiple objective linear programming (FMOLP) problems involving fuzzy parameters in any form of membership functions in both objective functions and constraints. A detailed description and analysis of the algorithm are supplied. In addition, an example is given to illustrate the approximate algorithm. (c) 2005 Elsevier Inc. All rights reserved.

关键词： optimization decision support technology fuzzy multiple objective linear programming approximate algorithm

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A decision support system for multiple objective linear programming with fuzzy parameters

A decision support system for multiple objective linear prog...

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IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE 2004)

作者： Wu, FJ Lu, J Zhang, GQ Univ Technol Sydney Fac Informat Technol Broadway NSW 2007 Australia

ISBN: (纸本)0769520731

A new approximate algorithm has been developed by Wu et al. for solving fuzzy multiple objective linear programming (FMOLP) problems with fuzzy parameters in any form of membership function in both objective functions and constraints. Based on the approximate algorithm, a fuzzy multiple objective decision support system (FMODSS) is developed. This paper focuses on the description of use for FMODSS in detail, and an example is presented for demonstrating how to solve a FMOLP problem by the FMODSS.

关键词： decision support system multiple objective linear programming fuzzy multiple objective linear programming

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A fuzzy multiple objective decision support model for energy-economy planning

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2003年第2期145卷 304-316页

作者： Borges, AR Antunes, CH Coimbra Polytech Inst ISEC P-3030601 Coimbra Portugal INESC P-3000033 Coimbra Portugal Univ Coimbra Dept Elect Engn P-3030030 Coimbra Portugal

In this paper an interactive approach to deal with fuzzy multiple objective linear programming problems is presented, which is based on the analysis of the decomposition of the parametric (weight) diagram into indifference regions corresponding to basic efficient solutions. This approach is illustrated to tackle uncertainty and imprecision associated with the coefficients of an input-output energy-economy planning model, aimed at providing decision support to decision makers in the study of the interactions between the energy system and the economy on a national level. (C) 2002 Published by Elsevier Science B.V.

关键词： fuzzy multiple objective linear programming decision support systems interactive methods energy system input-output analysis

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Suitable Aggregation Models Based on Risk Preferences for Supplier Selection and Order Allocation Problem

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2018年第1期22卷 5-16页

作者： Suprasongsin, Sirin Yenradee, Pisal Van-Nam Huynh Charoensiriwath, Chayakrit Japan Adv Inst Sci & Technol Sch Knowledge Sci 1-1 Asahidai Nomi Ishikawa 9231292 Japan Thammasat Univ Sirindhorn Int Inst Technol Sch Mfg Syst & Mech Engn 99 Moo 18Km 41 Paholyothin Highway Khlong Luang Pathum Thani 12120 Thailand Natl Elect & Comp Technol Ctr 112 Phahonyothin Rd Khlong Nueng 12120 Pathum Thani Thailand

In this paper, we propose (a) fuzzy multiple objective linear programming models for the Supplier Selection and Order Allocation (SSOA) problem under fuzzy demand and volume/quantity discount environments, and (b) an analysis of how to select the suitable aggregation operator based on the risk preferences of decision makers. The aggregation operators under consideration are additive, maximin, and augmented operators while the risk preferences are classified as risk-averse, risk-taking, and risk-neutral ones. The suitabilities of aggregation operators and risk preferences of decision makers are analyzed by a statistical technique, considering the average and the lowest satisfaction levels of the supplier selection criteria, based on numerical examples. Analysis results reveal that decision makers with different risk preferences will prefer only some aggregation operators and models. Moreover, a particular aggregation operator and modelmay generate a dominated solution for some situations. Thus, it should be applied with caution.

关键词： fuzzy multiple objective linear programming aggregation operators risk preferences of decision makers supplier selection and order allocation

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fuzzy Multi-objective Forest Biomass-to-biofuel Facility Location Problem with Social Consideration 10

Fuzzy Multi-objective Forest Biomass-to-biofuel Facility Loc...

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10th International Conference on Applied Energy (ICAE)

作者： Lin, Chun-Cheng Liu, Wan-Yu Huang, Guan-Lin Natl Chiao Tung Univ Dept Ind Engn Hsinchu 300 Taiwan Natl Chung Thing Univ Dept Forestry Taichung 402 Taiwan

This study proposes a novel multiple-objective forest biomass-to-biofuel facility location problem with social consideration and uncertainties, which determines locations of forest biomass-to-biofuel facilities so as to satisfy the energy demand, while the scale of facilities is limited. Aside from the two objectives (i e, minimizing cost and pollution) that were often discussed in previous problems, the problem in this study additionally considers an objective from the social aspect, i.e., maximizing the job opportunity by opening facilities. Furthermore, many uncertain factors may affect the number of days of operating biomass energy facilities as well as biomass production;the demand of biomass energy is uncertain with the unstable price of fossil fuels;and the number of job offers is uncertain. Therefore, we adopt fuzzy theory to add environmental uncertainties in the problem. To solve this problem, we employ the geographic information system to obtain candidate locations of facilities and biomass, and then use fuzzy multiple objective linear programming to solve the problem. From experimental results, the conflict between objectives can be observed. (C) 2019 The Authors. Published by Elsevier Ltd.

关键词： Facility location problem fuzzy theory fuzzy multiple objective linear programming

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fuzzy Multi-objective Forest Biomass-to-biofuel Facility Location Problem with Social Consideration

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Energy Procedia 2019年 158卷 4067-4072页

作者： Chun-Cheng Lin Wan-Yu Liu Guan-Lin Huang Department of Industrial Engineering National Chiao Tung University Hsinchu 300 Taiwan Department of Forestry National Chung Hsing University Taichung 402 Taiwan

This study proposes a novel multiple-objective forest biomass-to-biofuel facility location problem with social consideration and uncertainties, which determines locations of forest biomass-to-biofuel facilities so as to satisfy the energy demand, while the scale of facilities is limited. Aside from the two objectives (i.e., minimizing cost and pollution) that were often discussed in previous problems, the problem in this study additionally considers an objective from the social aspect, i.e., maximizing the job opportunity by opening facilities. Furthermore, many uncertain factors may affect the number of days of operating biomass energy facilities as well as biomass production; the demand of biomass energy is uncertain with the unstable price of fossil fuels; and the number of job offers is uncertain. Therefore, we adopt fuzzy theory to add environmental uncertainties in the problem. To solve this problem, we employ the geographic information system to obtain candidate locations of facilities and biomass, and then use fuzzy multiple objective linear programming to solve the problem. From experimental results, the conflict between objectives can be observed.

关键词： Facility location problem fuzzy theory fuzzy multiple objective linear programming

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