Adaptive Genetic Algorithm Simulating Human Reproduction Mode and Its Application in Multi-Peak Function Optimization

摘要

Considering the limitation such as premature convergence and low global convergence speed of standard genetic algorithm, human reproduction mode is used for reference and an improved genetic algorithm named adaptive genetic algorithm simulating human reproduction mode (HRAGA) is proposed in this paper. The genetic operators of this algorithm include selection operator, help operator, adaptive crossover operator and adaptive mutation operator. The genetic individuals are separated into male individuals and female individuals, the age feature and consanguinity feature are fused into individuals. Two individuals with opposite sex can reproduce the next generation if they are distant consanguinity individuals and their age is allowable. The crossover operator and mutation operator are adjusted nonlinearly and adaptively. Experiments were taken on multi-peak function optimization. The validity and excellent performance of this algorithm was proved by the experimental results. Its global convergence speed and optimal solutions are all better than those of simple genetic algorithm.