An interactive fuzzy satisficing method for general multiobjective 0-1 programming problems through genetic algorithms with double strings based on a reference solution

Authors:
Masatoshi Sakawa;Kosuke Kato
Affiliations:
Department of Industrial and Systems Engineering, Faculty of Engineering, Hiroshima University, Higashi-Hiroshima, Japan;Department of Industrial and Systems Engineering, Faculty of Engineering, Hiroshima University, Higashi-Hiroshima, Japan
Venue:
Fuzzy Sets and Systems - Theme: Decision and optimization
Year:
2002

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Abstract

In this paper, focusing on general multiobjective 0-1 programming problems involving positive and negative coefficients, we propose an interactive fuzzy satisficing method by extending our previous genetic algorithms with double strings for multiobjective multidimensional 0-1 knapsack problems. In the extended genetic algorithms, a new decoding algorithm for individuals represented by double strings which maps each individual to a feasible solution is proposed through the introduction of backtracking and individual modification. After examining the feasibility and efficiency of the extended genetic algorithms with double strings using a lot of 0-1 programming problems involving positive and negative coefficients, an illustrative numerical example demonstrated the feasibility and efficiency of the proposed interactive fuzzy satisficing method.