Adaptive Selection of Crossover and Mutation Probability of Genetic Algorithm and Its Mechanism
Changzheng Chen
Abstract
Changzheng Chen
Abstract
Considering the deficiency of selection of crossover and mutation probability in traditional genetic algorithm, an improved algorithm of crossover and mutation probability is proposed, and the mechanism of new algorithm is thoroughly analyzed, the new algorithm reflects adaptive stratagem. New algorithm is tested with a complex mathematics function, the experimental results show that improved method is efficient. The new improved algorithm remedies the premature and local convergence problem of the old algorithm.
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Considering the deficiency of selection of crossover and mutation probability in traditional genetic algorithm, an improved algorithm of crossover and mutation probability is proposed, and the mechanism of new algorithm is thoroughly analyzed, the new algorithm reflects adaptive stratagem. New algorithm is tested with a complex mathematics function, the experimental results show that improved method is efficient. The new improved algorithm remedies the premature and local convergence problem of the old algorithm.
Key concepts: Crossover, Mutation, Selection (genetic algorithm), Genetic algorithm, Algorithm, Convergence (economics), Mechanism (biology), Premature convergence