Pareto-optimal solutions in fuzzy multi-objective linear programming

被引：75

作者：

Jimenez, Mariano ^{[1
]}

Bilbao, Amelia ^{[2
]}

机构：

[1] Univ Basque Country, Dpto Econ Aplicada 1, San Sebastian, Spain

[2] Univ Oviedo, Dpto Econ Cuantitat, E-33006 Oviedo, Spain

来源：

FUZZY SETS AND SYSTEMS | 2009年 / 160卷 / 18期

关键词：

Multi-objective programming; Goal programming; Fuzzy mathematical programming; Fuzzy-efficient solution; Pareto-optimal solution; Two-phase method; MEMBERSHIP FUNCTIONS; 2-PHASE APPROACH;

D O I：

10.1016/j.fss.2008.12.005

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The problem of solving multi-objective linear-programming problems, by assuming that the decision maker has fuzzy goals for each of the objective functions, is addressed. Several methods have been proposed in the literature in order to obtain fuzzy-efficient solutions to fuzzy multi-objective programming problems. In this paper we show that, in the case that one of our goals is fully achieved, a fuzzy-efficient solution may not be Pareto-optimal and therefore we propose a general procedure to obtain a non-dominated solution, which is also fuzzy-efficient. Two numerical examples illustrate our procedure. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：2714 / 2721

页数：8

共 50 条

[21] Evaluating the ε-domination based multi-objective evolutionary algorithm for a quick computation of pareto-optimal solutions
Deb, K
Mohan, M
Mishra, S
EVOLUTIONARY COMPUTATION, 2005, 13 (04) : 501 - 525
[22] Pareto-optimal solutions based multi-objective particle swarm optimization control for batch processes
Jia, Li
Cheng, Dashuai
Chiu, Min-Sen
NEURAL COMPUTING & APPLICATIONS, 2012, 21 (06): : 1107 - 1116
[23] Additive Approximations of Pareto-Optimal Sets by Evolutionary Multi-Objective Algorithms
Horoba, Christian
Neumann, Frank
FOGA'09: PROCEEDINGS OF THE 10TH ACM SIGRVO CONFERENCE ON FOUNDATIONS OF GENETIC ALGORITHMS, 2009, : 79 - 86
[24] Multi-objective design optimization of an integrated regenerative transcritical cycle considering sensitivity in Pareto-optimal solutions
Bryan, Jacob A.
Zhang, Yili
Wang, Hailei
Richards, Geordie
ENERGY CONVERSION AND MANAGEMENT-X, 2023, 18
[25] Covering pareto-optimal fronts by subswarms in multi-objective particle swarm optimization
Mostaghim, S
Teich, J
CEC2004: PROCEEDINGS OF THE 2004 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2, 2004, : 1404 - 1411
[26] Pareto-Optimal Aircraft Technology Study for Environmental Benefits with Multi-Objective Optimization
Jimenez, Hernando
Mavris, Dimitri
JOURNAL OF AIRCRAFT, 2017, 54 (05): : 1860 - 1876
[27] Estimating Objective Weights of Pareto-Optimal Policies for Multi-Objective Sequential Decision-Making
Ikenaga, Akiko
Arai, Sachiyo
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2024, 28 (02) : 393 - 402
[28] Optimal load curtailment using multi-objective fuzzy linear programming method
Liu, Sige
Fan, Mingtian
Zhou, Xiaoxin
Cheng, Haozhong
EUROPEAN TRANSACTIONS ON ELECTRICAL POWER, 2010, 20 (08): : 1025 - 1039
[29] Flexibility of design variables to Pareto-optimal solutions in Multi Objective Optimization problems
Hiroyasu, Tomoyuki
Chino, Shinpei
Miki, Mitsunori
2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 4462 - +
[30] Sampling of Pareto-Optimal Trajectories using Progressive Objective Evaluation in Multi-Objective Motion Planning
Lee, Jeongseok
Yi, Daqing
Srinivasa, Siddhartha S.
2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2018, : 5358 - 5365

← 1 2 3 4 5 →