Improved Genetic Algorithms using Inverse-Elitism

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  • 逆エリート戦略を用いた改良遺伝的アルゴリズム
  • ギャク エリート センリャク オ モチイタ カイリョウ イデンテキ アルゴリズ

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Abstract

Improved Genetic Algorithms (GAs) have been proposed in this paper. We have directed our attention to “selection” and “crossover” in GAs. Novel strategies in selection and crossover are used in the proposed method. Various selecting strategies have been used in the conventional GAs such as Elitism, Tournament, Ranking, Roulette wheel, and Expected value model. These are not always effective, since these refer to only the fitness of each chromosome.<br>We have developed the following techniques to improve the conventional GAs: “inverse-elitism” as a selecting strategy and variable crossover range as a crossover strategy. In the “inverse-elitism”, an inverse-elite whose gene values are reversed from those in the corresponding elite is produced. This strategy greatly contributes to diversification of chromosomes. As for the variable crossover range, we combine the following crossover techniques effectively: one is that range in crossover is varied from wide to narrow gradually to carry out global search in the beginning and local search in the ending; another is that range in crossover is varied from narrow to wide.<br>We confirmed validity and superior performance of the proposed method by computer simulations.

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