摘要
本文利用混沌运动的遍历性 ,提出了一种求解优化问题的混沌遗传算法 ( ChaosGenetic Algorithm,简称 CGA) ,该算法的基本思想是把混沌变量加载于遗传算法的变量群体中 ,利用混沌变量对子代群体进行微小扰动并随着搜索过程的进行逐渐调整扰动幅度。研究结果表明 ,该方法效果显著 ,明显提高了优化计算效率。
By the full use of the ergodic property of chaos movement, a Chaos Genetic Algorithm(CGA) is proposed in this paper. The basic principle of CGA is that the small disturbance is added to child generation group by using the chaos variable and the disturbance extent is adjusted little by little as the search is going on. The computation results indicate that the CGA has good performance and significantly improves the computational efficiency in optimization.
出处
《系统工程》
CSCD
北大核心
2001年第1期70-74,共5页
Systems Engineering
