Evolutionary game algorithm for continuous parameter optimization
Information Processing Letters
ExGA II: an improved exonic genetic algorithm for the multiple knapsack problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
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In this paper, we propose a novel algorithm for optimizing multipleknapsack problem based on game theory. The proposed algorithm mapsthe search space and objective function of multiple knapsackproblem tothe strategy profile space and utility function ofnon-cooperative game respectively, and achieves the optimizationobjective through a three-phase equilibrium process of rationalgame agents. In the article, we present the definition and detaileddescription of the proposed algorithm, and give the proof on itsglobal convergence property. The efficiency of the proposedalgorithm has been verified by the simulation test and thecomparison with genetic algorithms.