一种基于混沌搜索的文化算法及其应用

Cultural algorithm based on chaotic search and its application

针对文化算法求解函数优化问题存在过早收敛、不稳定等缺陷,基于文化算法框架、嵌入混沌搜索优化,提出了一种混沌文化算法。该算法模型由基于混沌的群体空间和存储知识的信念空间组成,利用标准知识和形势知识分别引导混沌搜索和混沌扰动,有效克服了文化算法过早收敛、混沌搜索优化对初值敏感、搜索效率低等缺陷。实例表明,该方法具有较强的全局搜索能力,在搜索效率、精度和稳定性上有显著表现,并能有效处理高维函数优化问题。

For premature convergence and instability of cultural algorithm in solving function optimization problem,based on cultural algorithm and chaos search optimization,this paper proposed a chaos cultural algorithm（CCA）.The algorithm model consisted of a chaos-based population space and a stored knowledge belief space,using normative knowledge and situational knowledge for chaos search and chaos perturbation respectively,and effectively avoided premature convergence of cultural algorithm and overcame chaos search optimization＇s sensitivity to initial values and poor efficiency.Test results show that this algorithm is strong in global search,and has good performance in searching efficiency,precision and stability,especially in solving high-dimensional optimization problem.