复杂函数优化的混沌遗传算法

Optimizing Complex Functions by Chaos Genetic Algorithm

将混沌融入遗传算法提出了混沌遗传算法 ,该方法利用混沌运动的随机性、遍历性、对初始条件的敏感性等特性进行群体的混沌初始化和最优个体的混沌变尺度载波寻优 .典型复杂函数优化的仿真结果表明该方法较遗传算法具有更快的收敛速度和更小的计算量 ,是复杂函数优化的有效手段 .

By introducing chaos state to genetic algorithm,this paper proposed a novel optimization algorithm named chaos genetic algorithm.Its major measures are chaos initialization and chaos carrier wave of best fitness in population both based on the ergodicity,stochastic property and regularity of chaos.Simulation results of typical complex function optimization show that chaos genetic algorithm improves the convergence and reduces the computing time greatly.