混沌优化与遗传算法的智能集成  

Intelligent Integrate of Genetic Algorithm and Chaotic Optimization

作　　者：章敬东[1] 刘小辉[1] 邓飞其[1] 刘永清[1] 

机构地区：[1]广州市华南理工大学自动化科学与工程学院,广州510641

出　　处：《计算机工程与应用》2003年第16期17-20,共4页Computer Engineering and Applications

基　　金：国家自然科学基金资助(编号:69934030);广东省计委高技术项目基金资助(编号:犤2001309犦)

摘　　要：作为智能算法,遗传算法的确是解决非线性复杂优化问题的有利工具,但它在搜索过程中易陷入局部最优、收敛速度慢的缺陷又确实限制了它的寻优效能。混沌的遍历性、随机性和内在规律性使得混沌优化能够互补地与遗传算法进行集成。基于此,该文经过遗传算法和混沌优化方法的理论机制分析,将二者进行智能集成,给出混沌遗传优化算法CGA。经过仿真迭代运算,发现该算法能够保证求得全局最优解,并且寻优速度有很大提高。As an Intelligent Algorithm,Genetic Algorithm does be an favorite tool that can solve nonlinear complex op-timization problems ,however that it's easy to get into part extremum solution and sometimes its convergence rate is too low and depresses it.Based on this,this paper does intelligent integrate of Genetic Algorithm and Chaotic Optimization methods and supplies a integrated Chaos-Genetic Algorithm(CGA)by analyzing and researching Genetic Algorithm and Chaotic Optimization methods on theory mechanism.By simulating iteration operation,it discovers that CGA can surely and rapidly get global optimum solution and greatly improve convergence rate.

关 键 词：智能集成 混沌遗传算法 遗传算法 混沌优化 非线性 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]