基于极坐标编码的改进人工鱼群算法  

Improved artificial fish swarm algorithm based on polar coordinate coding

作　　者：宋潇潇[1] 孙棣华[1] 解佳[1] 

机构地区：[1]重庆大学自动化学院,重庆400030

出　　处：《系统工程与电子技术》2010年第10期2248-2251,共4页Systems Engineering and Electronics

基　　金：国家高技术研究发展计划(863计划)(2006AA04A124);"211工程"三期建设(S-09108)资助课题

摘　　要：针对人工鱼群算法收敛速度慢、求解精度低及易陷入局部最优的问题,提出了一种改进的人工鱼群算法。为提高求解精度,算法采用极坐标编码形式增加单个母体解空间表达的多样性,在迭代求解过程中根据适应度值依概率调整极角,逐步降低观测结果的不确定性。通过对三种行为方式进行调整,去除影响搜索方向性的随机移动行为,将搜索重点集中在最优解邻域内,有效降低算法重搜索的可能性,以提高算法的收敛速度。实验结果表明,该算法在收敛性和稳定性上优于基本人工鱼群算法、自适应人工鱼群算法和生境人工鱼群算法,验证了算法的有效性。Aiming at the defects of slow rate of convergence,low accuracy and easily falling into local optimum in artificial fish swarm algorithm（AFSA）,an improved AFSA is proposed.In order to improve the accuracy,polar coordinate coding is introduced to increase the diversity in the expression solution of single matrix solution space.The polar angle is adjusted under probability by fitness in iterative process,and the uncertainty of observational results is reduced gradually.In order to increase the rate of convergence,three kinds of actions are adjusted,the random move which impacts the search direction is removedm,the search focuses on the neighborhood of the optimal solution and the possibility of repetition search is reduced.Experimental results show that the convergence and the stability of this algorithm are better than those of AFSA,adaptive artificial fish swarm algorithm（AAFSA） and niche artificial fish swarm algorithm（NAFSA）,and the effectiveness of the algorithm is validated.

关 键 词：人工鱼群算法 极坐标编码 0-1背包问题 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]