【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。更多还原

【Abstract】 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.更多还原