An interactive fuzzy satisficing method based on fractile criterion optimization for multiobjective stochastic integer programming problems

In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic integer programming problems are transformed into deterministic one...

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Vydáno v:Expert systems with applications Ročník 37; číslo 8; s. 6012 - 6017
Hlavní autoři: Kato, Kosuke, Sakawa, Masatoshi, Katagiri, Hideki, Perkgoz, Cahit
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.08.2010
Témata:
Criteria
Decision making
Efficient solution
Fractile criterion optimization
Fuzzy
Fuzzy logic
Fuzzy programming
Fuzzy set theory
Integer programming
Mathematical models
Multiobjective programming
Stochastic programming
Stochasticity
Integer programming
Fractile criterion optimization
Fuzzy programming
Efficient solution
Multiobjective programming
Stochastic programming
ISSN:0957-4174, 1873-6793
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Abstract In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic integer programming problems are transformed into deterministic ones based on the fractile criterion optimization model. As a fusion of stochastic programming and fuzzy one, we introduce fuzzy goals representing the ambiguity of the decision maker’s judgments into them and define M- θ -efficiency, a new concept of efficient solution, as a fusion of stochastic approaches and fuzzy ones. Then, we construct an interactive fuzzy satisficing method using genetic algorithms to derive a satisficing solution for the decision maker which is guaranteed to be M- θ -efficient by updating the reference membership levels. Finally, the efficiency of the proposed method is demonstrated through numerical experiments.
AbstractList In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic integer programming problems are transformed into deterministic ones based on the fractile criterion optimization model. As a fusion of stochastic programming and fuzzy one, we introduce fuzzy goals representing the ambiguity of the decision maker’s judgments into them and define M- θ -efficiency, a new concept of efficient solution, as a fusion of stochastic approaches and fuzzy ones. Then, we construct an interactive fuzzy satisficing method using genetic algorithms to derive a satisficing solution for the decision maker which is guaranteed to be M- θ -efficient by updating the reference membership levels. Finally, the efficiency of the proposed method is demonstrated through numerical experiments.
In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic integer programming problems are transformed into deterministic ones based on the fractile criterion optimization model. As a fusion of stochastic programming and fuzzy one, we introduce fuzzy goals representing the ambiguity of the decision maker's judgments into them and define M-[theta]-efficiency, a new concept of efficient solution, as a fusion of stochastic approaches and fuzzy ones. Then, we construct an interactive fuzzy satisficing method using genetic algorithms to derive a satisficing solution for the decision maker which is guaranteed to be M-[theta]-efficient by updating the reference membership levels. Finally, the efficiency of the proposed method is demonstrated through numerical experiments.
Author Sakawa, Masatoshi
Kato, Kosuke
Perkgoz, Cahit
Katagiri, Hideki
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Issue 8
Keywords Integer programming
Fractile criterion optimization
Fuzzy programming
Efficient solution
Multiobjective programming
Stochastic programming
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SubjectTerms Criteria
Decision making
Efficient solution
Fractile criterion optimization
Fuzzy
Fuzzy logic
Fuzzy programming
Fuzzy set theory
Integer programming
Mathematical models
Multiobjective programming
Stochastic programming
Stochasticity
Title An interactive fuzzy satisficing method based on fractile criterion optimization for multiobjective stochastic integer programming problems
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