Interactive fuzzy stochastic multi-level 0–1 programming using tabu search and probability maximization

•Cooperative multi-level 0–1 programming problems involving random variable coefficients are considered.•New optimization criterion is constructed using tabu search and probability maximization.•An illustrative numerical example demonstrates the feasibility and efficiency of the proposed method. In...

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Bibliographic Details
Published in:Expert systems with applications Vol. 41; no. 6; pp. 2957 - 2963
Main Authors: Sakawa, Masatoshi, Matsui, Takeshi
Format: Journal Article
Language:English
Published: Amsterdam Elsevier Ltd 01.05.2014
Elsevier
Subjects:
0–1 Programming
Applied sciences
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Decision making
Decision theory. Utility theory
Exact sciences and technology
Fuzzy
Fuzzy logic
Fuzzy set theory
Interactive
Interactive fuzzy programming
Mathematical models
Mathematical programming
Maximization
Multi-level programming
Operational research and scientific management
Operational research. Management science
Probability maximization
Programming
Random variables
Software
Tabu search
Multi-level programming
0–1 Programming
Random variables
Tabu search
Interactive fuzzy programming
Probability maximization
Interactive programming
Probabilistic approach
Model following
Decision making
Updating
Fuzzy programming
Constrained optimization
Stochastic programming
Fuzzy logic
Zero one programming
0-1 Programming
Problem solving
Fuzzy decision
Objective function
Deterministic approach
Multilevel system
Random variable
Judgment
ISSN:0957-4174, 1873-6793
Online Access:Get full text
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Summary:•Cooperative multi-level 0–1 programming problems involving random variable coefficients are considered.•New optimization criterion is constructed using tabu search and probability maximization.•An illustrative numerical example demonstrates the feasibility and efficiency of the proposed method. In this paper, we consider interactive fuzzy programming for multi-level 0–1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0–1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. For solving the transformed deterministic problems efficiently, we also introduce novel tabu search for general 0–1 programming problems. A numerical example for a three-level 0–1 programming problem is provided to illustrate the proposed method.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2013.10.027