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

作　　者：何建佳[1] 徐福缘[1] 何胜学[1] 黄鹤[1] 

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《计算机应用研究》2010年第7期2472-2475,共4页Application Research of Computers

基　　金：国家自然科学基金资助项目(70672110);国家"863"计划资助项目(2007AA04Z101);上海市(第三期)重点学科项目(S30504);上海市研究生创新基金资助项目(JWCXSL1001)

摘　　要：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.

关 键 词：进化计算 文化算法 混沌文化算法 混沌搜索 知识引导 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]