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In this paper, for general multiobjective 0-1 programming problems involving positive and negative coefficients, considering fuzzy goals to represent the ambiguous nature of the decision maker's judgment for objective functions, we propose a fuzzy satisficing method through genetic algorithms which is an extension of genetic algorithms with double strings for multidimensional 0-1 knapsack problems. In the extended genetic algorithms, a new decoding algorithm for individuals represented by double strings which maps an each individual to a feasible solution is proposed through the incorporation of a reference solution and its renewal. The efficiency and effectiveness of the proposed method are investigated by several numerical examples.
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International (Volume:3 )
Date of Conference: 22-25 Aug. 1999