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An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems using chance constrained conditions
Author(s) -
Sakawa Masatoshi,
Kato Kosuke
Publication year - 2002
Publication title -
journal of multi‐criteria decision analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 47
eISSN - 1099-1360
pISSN - 1057-9214
DOI - 10.1002/mcda.322
Subject(s) - satisficing , mathematical optimization , goal programming , stochastic programming , ambiguity , fuzzy logic , randomness , linear programming , computer science , mathematics , artificial intelligence , statistics , programming language
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.