An interactive fuzzy satisficing method based on variance minimization under expectation constraints for multiobjective stochastic linear programming problems

被引:5
|
作者
Kato, Kosuke [1 ]
Sakawa, Masatoshi [2 ]
机构
[1] Hiroshima Inst Technol, Fac Appl Informat Sci, Hiroshima 7315193, Japan
[2] Hiroshima Univ, Grad Sch Engn, Higashihiroshima 7398527, Japan
关键词
Multiobjective linear programming; Stochastic programming; Interactive fuzzy satisficing method; Expectation optimization; Variance minimization; UNCERTAINTY;
D O I
10.1007/s00500-010-0540-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we focus on multiobjective linear programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic linear programming problems are transformed into deterministic ones based on the variance minimization model under expectation constraints. After introducing fuzzy goals to reflect the ambiguity of the decision maker's judgements for objective functions, we propose an interactive fuzzy satisficing method to derive a satisficing solution for them as a fusion of the stochastic programming and the fuzzy one. The application of the proposed method to an illustrative numerical example shows its usefulness.
引用
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页码:131 / 138
页数:8
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