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- W2382321315 abstract "Being a stochastic search technique, there are some shortcomings in standard genetic algorithm such as poor local search ability and premature convergence. An effective method of adapting mutation probabilities on each genome of binary-encoding genetic algorithm is proposed to overcome these shortcomings. At the beginning stage of evolution, larger values of mutation probability are assigned to those genomes in higher bit positions, so that larger feasible region is explored. When the region in which the global optimum exists is found, mutation probabilities of genomes in higher bit positions are decreased to prevent better solutions from disruption. Accordingly, mutation probabilities of genomes in lower bit positions are increased to improve the local search ability. Experiments results on five multimodal functions demonstrate that proposed genetic algorithm possesses better optimization ability and gets stuck at a local optimum fewer times than standard genetic algorithm does." @default.
- W2382321315 created "2016-06-24" @default.
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- W2382321315 date "2005-01-01" @default.
- W2382321315 modified "2023-09-24" @default.
- W2382321315 title "Binary-encoding Genetic Algorithms with Modified Mutation Operation" @default.
- W2382321315 hasPublicationYear "2005" @default.
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