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基于遗传粒子群算法的高维复杂函数优化方法
引用本文:于万霞,张维存,郑宏兴.基于遗传粒子群算法的高维复杂函数优化方法[J].计算机工程与应用,2007,43(36):31-33.
作者姓名:于万霞  张维存  郑宏兴
作者单位:[1]天津工程师范学院电子工程系,天津300222 [2]河北工业大学管理学院,天津300130
摘    要:针对高维复杂函数优化的特点,提出了一种遗传算法与粒子群算法相结合的主-从结构算法。算法中,主级为全局搜索的遗传算法;从级为局部邻域搜索的粒子群算法。通过主-从协调机制和从级转换函数设计,使算法不依赖复杂的编码方式和进化算子进行全局精确搜索。通过仿真和比较实验,验证了算法对高维复杂函数优化的有效性。

关 键 词:遗传算法  粒子群算法  算法结构  转换函数  优化
文章编号:1002-8331(2007)36-0031-03
修稿时间:2007年8月1日

Genetic and particle swarm algorithm-based optimization solution for high-dimension complex functions
YU Wan-xia,ZHANG Wei-cun,ZHENG Hong-xing.Genetic and particle swarm algorithm-based optimization solution for high-dimension complex functions[J].Computer Engineering and Applications,2007,43(36):31-33.
Authors:YU Wan-xia  ZHANG Wei-cun  ZHENG Hong-xing
Affiliation:1.Department of Electronic Engineering,Tianjin University of Technology and Education,Tianjin 300222,China 2.School of Management,Hebei University of Technology,Tianjin 300130,China
Abstract:A hybrid of genetic and particle swarm algorithm is proposed to solve the higen-dimension complex functions optimization.The algorithm is formulated in a form of hierarchical structure.The global search is performed at the master level by genetic algorithm,while the local search is carried out at the slave level by particle swarm optimization.Through the harmonizing mechanism between master and slave level,and special translation function designed for the slave level,the algorithm can execute global exact search without relying on complex coding and complex evolving operators.The simulation and results from comparison with other algorithms demonstrate the effectiveness of the proposed algorithm for high-dimension complex functions optimization.
Keywords:genetic algorithm  particle swarm optimization  algorithm structure  translation function  optimization
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