Adaptive and Assortative Mating Scheme for Evolutionary Multi-Objective Algorithms

نویسندگان

  • Khoi Le
  • Dario Landa Silva
چکیده

We are interested in the role of restricted mating schemes in the context of evolutionary multi-objective algorithms. In this paper, we propose an adaptive assortative mating scheme that uses similarity in the decision space (genotypic assortative mating) and adapts the mating pressure as the search progresses. We show that this mechanism improves the performance of the simple evolutionary algorithm for multi-objective optimisation (SEAMO2) on the multiple knapsack problem.

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تاریخ انتشار 2007