Interactive multiobjective fuzzy random programming through the level set-based probability model

This paper considers a multiobjective linear programming problem involving fuzzy random variable coefficients. A new fuzzy random programming model is proposed by extending the ideas of level set-based optimality and a stochastic programming model. The original problem involving fuzzy random variabl...

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Bibliographic Details
Published in:Information sciences Vol. 181; no. 9; pp. 1641 - 1650
Main Authors: Katagiri, Hideki, Sakawa, Masatoshi
Format: Journal Article
Language:English
Published: Elsevier Inc 01.05.2011
Subjects:
Algorithms
Fuzzy
Fuzzy logic
Fuzzy random variable
Fuzzy set theory
Interactive
Interactive algorithm
Level set-based model
Mathematical models
Multiobjective linear programming
Optimization
Pareto optimality
Probability maximization
Programming
Pareto optimality
Level set-based model
Fuzzy random variable
Multiobjective linear programming
Probability maximization
Interactive algorithm
ISSN:0020-0255, 1872-6291
Online Access:Get full text
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Summary:This paper considers a multiobjective linear programming problem involving fuzzy random variable coefficients. A new fuzzy random programming model is proposed by extending the ideas of level set-based optimality and a stochastic programming model. The original problem involving fuzzy random variables is transformed into a deterministic equivalent problem through the proposed model. An interactive algorithm is provided to obtain a satisficing solution for a decision maker from among a set of newly defined Pareto optimal solutions. It is shown that an optimal solution of the problem to be solved iteratively in the interactive algorithm is analytically obtained by a combination of the bisection method and the simplex method.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2011.01.003