Interactive fuzzy programming for multiobjective fuzzy random linear programming problems through possibility-based probability maximization

This paper presents interactive fuzzy programming for multiobjective fuzzy random linear programming problems through possibility-based probability maximization. In our proposed approach, it is assumed that the decision maker has fuzzy goals for not only original objective functions but also the cor...

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Veröffentlicht in:Operational research Jg. 14; H. 1; S. 51 - 69
Hauptverfasser: Yano, Hitoshi, Sakawa, Masatoshi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2014
Springer Nature B.V
Schlagworte:
Business and Management
Computational Intelligence
Decision making
Farms
Fuzzy
Fuzzy logic
Fuzzy set theory
Interactive
Linear programming
Management Science
Mathematical analysis
Mathematical models
Maximization
Operations Research
Operations Research/Decision Theory
Original Paper
Pareto optimum
Programming
Random variables
Simplex method
Studies
Working hours
Fuzzy random variable
Fuzzy decision
Probability maximization
Satisfactory solution
Interactive decision making
ISSN:1109-2858, 1866-1505
Online-Zugang:Volltext
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Zusammenfassung:This paper presents interactive fuzzy programming for multiobjective fuzzy random linear programming problems through possibility-based probability maximization. In our proposed approach, it is assumed that the decision maker has fuzzy goals for not only original objective functions but also the corresponding distribution functions in a probability maximization model, and such fuzzy goals are quantified by eliciting the corresponding membership functions. Using the fuzzy decision, such two kinds of membership functions are integrated. The satisfactory solution is derived from among an extended Pareto optimal solution set through the interaction with the decision maker. An illustrative numerical example is provided to demonstrate the efficiency of the proposed method.
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ISSN:1109-2858
1866-1505
DOI:10.1007/s12351-013-0135-4