摘要
针对人工鱼群算法(AFSA)易陷入局部最优的问题,提出一种基于双混沌映射的人工鱼群算法(CAFSA)。该方法利用Tent映射的均匀分布性产生混沌初始鱼群,增加搜索的多样性;其次在人工鱼群演化陷入局部最优时,利用局部分布均匀的Logistic映射生成混沌变异算子对其产生扰动,使其跳出局部最优值,向全局最优值靠近。仿真实验表明,改进后的算法比基本人工鱼群算法的全局寻优能力更强,搜索精度更高。
Artificial fish swarm algorithm（AFSA） is easy to fall into local optimum.To resolve this problem,an improved artificial fish swarm algorithm based on coupled chaotic maps（CAFSA） is proposed.The algorithm produces primitive chaotic fish swarm using the uniform distribution of Tent map,and improves the diversity of search;When the artificial fish swarm evolves to trapping in a local optimum,the chaotic mutation operator produced by local evenly distributed Logistic map is adopted to form disturbance on the swarm to drive artificial fish jumping out of local optimum but approaching the global optimum.Simulation experimental results show that the improved algorithm has stronger global optimisation ability and higher accuracy than the basic artificial fish swarm algorithm.
出处
《计算机应用与软件》
CSCD
北大核心
2012年第9期230-233,共4页
Computer Applications and Software
基金
青海大学2011年度中青年科研基金项目(2011-QGY-1)
关键词
人工鱼群算法
混沌映射
局部最优
混沌变异
Artificial fish swarm algorithm ,Chaos mapping Local optimum ,Chaotic mutation
