An interactive fuzzy satisficing method for multiobjective integer programming problems through genetic algorithms

被引：0

作者：

Sakawa, M ^{[1
]}

Shibano, T ^{[1
]}

Kato, K ^{[1
]}

机构：

[1] Hiroshima Univ, Dept Ind & Syst Engn, Hiroshima 730, Japan

来源：

1998 SECOND INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED INTELLIGENT ELECTRONIC SYSTEMS, KES'98 PROCEEDINGS, VOL 1 | 1998年

关键词：

multiobjective integer programming problem; fuzzy goals; genetic algorithms; ringed double strings; interactive methods;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper deals with multiobjective integer programming problems by considering fuzzy goals of the decision maker for objective functions. After determining the fuzzy goals of the decision maker, if the decision maker specifies the reference membership values, the corresponding Pareto optimal solution can be obtained by solving the augmented minimax problem which becomes an integer programming problem. For solving the problem, decoding algorithms for 0-1 programming problems are revised and ringed double strings are also introduced. Then an interactive fuzzy satisficing method is presented together with an illustrative numerical example.

引用

页码：94 / 100

页数：7

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