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An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems using chance constrained conditions

✍ Scribed by Masatoshi Sakawa; Kosuke Kato

Publisher: John Wiley and Sons
Year: 2002
Tongue: English
Weight: 178 KB
Volume: 11
Category: Article
ISSN: 1057-9214
DOI: 10.1002/mcda.322

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✦ Synopsis

Abstract

Two major approaches to deal with randomness or ambiguity involved in mathematical programming problems have been developed. They are stochastic programming approaches and fuzzy programming approaches. In this paper, we focus on multiobjective linear programming problems with random variable coefficients in objective functions and/or constraints. Using chance constrained programming techniques, the stochastic programming problems are transformed into deterministic ones. As a fusion of stochastic approaches and fuzzy ones, after determining the fuzzy goals of the decision maker, interactive fuzzy satisficing methods to derive a satisficing solution for the decision maker by updating the reference membership levels is presented. Copyright © 2003 John Wiley & Sons, Ltd.

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