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混合变异算子的人工鱼群算法
引用本文:曲良东,何登旭.混合变异算子的人工鱼群算法[J].计算机工程与应用,2008,44(35):50-52.
作者姓名:曲良东  何登旭
作者单位:广西民族大学,数学与计算机科学学院,南宁,530006
基金项目:国家民委科学基金  
摘    要:在分析基本人工鱼群算法存在不足的基础上,提出了基于高斯变异算子与差分进化变异算子相结合的人工鱼群算法,该算法克服了人工鱼漫无目的随机游动或在非全局极值点的大量聚集,显著提高了求解质量和运行效率.通过仿真实验测试验证,表明该算法是可行的和有效的。

关 键 词:人工鱼群算法  高斯变异算子  差分进化变异算子
收稿时间:2007-12-20
修稿时间:2008-2-27  

Artificial fish-school algorithm based on hybrid mutation operators
QU Liang-dong,HE Deng-xu.Artificial fish-school algorithm based on hybrid mutation operators[J].Computer Engineering and Applications,2008,44(35):50-52.
Authors:QU Liang-dong  HE Deng-xu
Affiliation:College of Mathematics and Computer Science,Guangxi University for Nationlities,Nanning 530006,China
Abstract:After analyzing the disadvantages of Artificial Fish-School Algorithm (AFSA),this paper presents a hybrid artificial fish-school algorithm based on Gauss mutation and differential evolution mutation.By adding mutation operators to AFSA in evolution process,the ability of AFSA to break away from artificial fish stochastic moving without a definite purpose or heavy getting together round the local optimum solution is greatly improve.The proposed algorithm can greatly improve the ability of seeking the global excellent result and convergence property and accuracy.Several computer simulation results show that the proposed algorithm is significantly superior to original AFSA.
Keywords:Artificial Fish-School Algorithm(AFSA)  Gauss mutation operator  differential evolution mutation operator
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