Adaptation of Genetic AlgorithmParameters Based on Fuzzy

نویسندگان

  • Francisco Herrera
  • Manuel Lozano
چکیده

The genetic algorithm behaviour is determined by the exploitation and exploration relationship kept throughout the run. Adaptive genetic algorithms have been built for inducing exploitation/exploration relationships that avoid the premature convergence problem and improve the nal results. One of the most widely studied adaptive approaches are the adaptive parameter setting techniques. In this paper, we study these techniques in depth, based on the use of fuzzy logic controllers. Furthermore, we design and discuss an adaptive real-coded genetic algorithm based on the use of fuzzy logic controllers. Although suitable results have been obtained by using this type of adaptive technique, we report some reeections on open problems that still remain.

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تاریخ انتشار 2007