%0 Journal Article
%T Research on Genetic Algorithm Based on Particle Swarm Algorithm<br>基于粒子群算法的遗传算法研究
%A WANG Wen-Yi
%A QIN Guang-Jun
%A WANG Ruo-Yu
%A <br>王文义
%A 秦广军
%A 王若雨
%J 计算机科学
%D 2007
%I 
%X Premature convergence and weak local optimization are two key problems existing in the conventional genetic algorithm.To overcome the shortcomings,this paper proposes an improved genetic algorithm based on the particle swarm algorithm.The basic principle is that a new mutation operator is constructed and population is divided into parts.Three typical multimodal values functions are optimized and evaluate the efficiency of the algorithm.The experimental results show,the improved genetic algorithm can not only maintain effectively the polymorphism in the colony and avoid premature,but also greatly improve the convergent speed.
%K Genetic algorithm
%K Particle swarm algorithm
%K Mutation operator
%K Population diversity
%K Premature convergence<br>遗传算法
%K 粒子群算法
%K 变异算子
%K 种群多样性
%K 早熟收敛
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=1E8759907DE6547834E52A566745BF65&yid=A732AF04DDA03BB3&vid=339D79302DF62549&iid=5D311CA918CA9A03&sid=769BD58726D66E7D&eid=2922B27A3177030F&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=9