具有自适应交换率和变异率的遗传算法

Adaptive Crossover Rate and Mutation Rate in Genetic Algorithms

简单遗传算法存在着收敛速度慢、易陷入局部极小等缺陷 .针对这些缺陷 ,本文设计出随相对遗传代数呈双曲线下降的自适应交换率 ,并提出与父串间的相对欧氏距离成反比、随相对遗传代数指数下降的自适应变异率 .实例验证表明 ,具有自适应交换率和变异率的遗传算法在收敛速度和获得全局最优解的概率两个方面都有很大的提高 .

Simple genetic algorithm gets local minimization too easily and converges slowly.To solve these problems,adaptive crossover rate that has reverse hyperbolic relation with the numbers of iteration is designed,and adaptive mutation rate that has reverse proportion to the distances of parents and reverse exponential relation to the numbers of iteration is put forward.The Practical simulation results show that the adaptive GA has greater convergence speed and larger probability of getting the best solution.