关键词: 遗传算法 早熟 自适应算子

Abstract:

This paper analyses tersely the reasons resulting in prematurity arising in the practice of genetic algorithms （GA） and puts forth an improved algor  ithm IGA. IGA adopts the strategy of adaptive cross rate and mutation rate to solve the prematurity problem. The simulation results show that IGA has th e characteristics of high convergence and can effectively avoid prematurity to improve global optimization.

Key words: （genetic algorithms;prematurity, adaptive operators）