遗传算法的改进

Improvement of Genetic Algorithms

简单遗传算法存在着收敛速度慢、员陷入局部极小等缺陷。针对这2点，对遗传算法的各个环节作了改进：对初始方案集的产生做了改进，提出了更加适合自然规律的竞争选择法，设计出与迭代次数成反比、与父串间的距离成正比的自适应变异率。实例验证表明，改进的遗传算法的收敛速度和获得全局最优解的概率都有很大的提高。

Simple genetic algorithms gets local minimization too easily and converges slowly.To solve these problems, the improvement to the generation of initial population, theindication in the compete selection and the design of adaptive mutation rate that has inverseproportion to the numbers of iteration and direct proportion to the distance of parents are putforward. The practical simulation results show that the improved genetic algorithms hasgreater converge speed and larger probability of getting the best solution.