Solving fuzzy optimization problems by evolutionary algorithms

被引：16

作者：

Jiménez, F

Cadenas, JM ^{[1
]}

Verdegay, JL

Sánchez, G

机构：

[1] Univ Murcia, Dept Ingn Informac & Commun, Murcia 30071, Spain

[2] Univ Granada, Dept Ciencias Computac & Inteligencia Artificial, Granada 18071, Spain

来源：

INFORMATION SCIENCES | 2003年 / 152卷

关键词：

fuzzy mathematical programming; evolutionary algorithms;

D O I：

10.1016/S0020-0255(03)00074-4

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper mathematical programming problems with fuzzy constraints are dealt with. Fuzzy solutions are obtained by means of a parametric approach in conjunction with evolutionary techniques. Some relevant characteristics of the evolutionary algorithm are for instance a real-coded representation of solutions and the preselection scheme as niche formation and elitist technique. Three test problems with fuzzy constraints and different structures are used in order to check and compare the proposed technique. The results obtained are very good in comparison with those from another methods. (C) 2003 Elsevier Science Inc. All rights reserved.

引用

页码：303 / 311

页数：9

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