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By referencing the effect of environment to the biologic evolution, an environment-gene double evolution immune clone algorithm (EGICA) is proposed based on normal immune clone algorithm. This algorithm can avoid blind search effectively and enhance the convergence speed since an environment-gene double evolution mutation operator is introduced, which can accumulate the experience of evolution process...
In this paper, a mutation with cycle probability is designed by simulating the evolutionary rule of the earth creature, and a genetic algorithm based on the cycle mutation, presents the ability in improving search efficiency and overcoming premature to some extent. To further improve performance of the algorithm, the selection is mended according to the phenomena that optimum individual always plays...
In this paper, in order to overcome the premature convergence and low stability of the particle swarm optimization (PSO) algorithm, a particle swarm optimization algorithm based on adaptive periodic mutation (APMPSO) is introduced. In the algorithm, the fitness uniformity distribution of the objective function, which can maintain the diversity of the population, is adaptively adjusted. The strategy...
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