一种基于距离行为模型的改进微粒群算法  

Improved particle swarm optimizer with behavior of distance models

作　　者：王辉[1] 钱锋[1] 

机构地区：[1]华东理工大学化学工程联合国家重点实验室,上海200237

出　　处：《计算机工程与应用》2007年第30期30-32,共3页Computer Engineering and Applications

基　　金：国家重点基础研究发展规划(973)(the National Grand Fundamental Research 973 Program of China under Grant No.2002CB3122000);国家高技术研究发展计划(863)(the National High-Tech Research and Development Plan of China under Grant No.20060104Z1081);上海市自然科学基金(the Natural Science Foundation of Shanghai of China under Grant No.05ZR14038);国家杰出青年科学基金(the National Science Fund of China for Distinguished Young Scholar under Grant No.60625302);上海市科委重大基础研究基金(No.05DJ14002)。

摘　　要：提出一种基于距离行为模型的改进微粒群算法,根据微粒所处区域来调整其飞行的速度。在吸引区域微粒加速飞向群体最优位置,在排斥区域按正常速度飞行。为了研究算法的性能,对几种典型高维非线性函数进行了测试。研究结果表明,与基本微粒群算法相比,改进后的微粒群算法提高了算法的收敛速度和收敛精度,改善了算法的性能。Proposes an improved PSO（Particle Swarm Optimizer） called BDPSO（Behavior of Distance PSO） that particles do different behavior due to different regions of the swarm.In the attraction region particles speed up fly to the best position of the swarm and in the repulsion region they fly at normal speed.Some benchmark problems are tested for the performance of BDPSO and results show that BDPSO performances better than PSO both on convergence rate and accurate solutions.

关 键 词：微粒群算法 吸引 排斥 距离行为微粒群算法 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]