一种新的混沌差分进化算法

Novel Chaos Differential Evolution Algorithm

提出一种新的混沌差分进化(CDE)算法,在每一代中通过差分进化(DE)算法找到最佳个体,在最佳个体附近用混沌方法进行局部搜索,通过引入调节因子加强其搜索能力。6个基本测试函数的优化结果表明,当误差函数精度为10-14时,与DE相比,CDE的寻优能力更强、收敛速度较快。

This paper proposes a new Chaos Differential Evolution（CDE） algorithm. It uses Differential Evolution（DE） algorithm to find the best individual each generation, then chaos based local search is executed nearby the best individual. A scaling factor is introduced to enhance the searching ability of CDE. Experimental results on six benchmark functions show the error function value is 10^-14, both the ability of finding optimal solution and convergence speed using CDE are better than using DE.