基于爬山算子和适应值共享的改进遗传算法

广东工业大学学报 ›› 2011, Vol. 28 ›› Issue (1): 78-81.

基于爬山算子和适应值共享的改进遗传算法

广东工业大学应用数学学院，广东广州 510006

出版日期:2011-12-25 发布日期:2011-12-25
作者简介:涂井先（1987-），男，硕士研究生，主要研究方向为优化算法理论及其应用.

An Improved Genetic Algorithm Based on Mountain-climbing Operators and Fitness Sharing

Faculty of Applied Mathematics,Guangdong University of Technology,Guangzhou 510006,China

Online:2011-12-25 Published:2011-12-25

摘要/Abstract

摘要： 提出了一种基于爬山算子和适应值共享的改进遗传算法，将局部搜索算法与遗传算法有效结合,增强了遗传算法的搜索能力.爬山算子以黄金分割法为基础，依次对个体每一维进行优化.数值实验证明,改进后的新算法优于当前一些较好的遗传算法.新算法既有较快的收敛速度，又能以较大概率搜索到优化问题的全局最优解.

关键词: 遗传算法；适应值共享；爬山算子；黄金分割法

Abstract: An improved genetic algorithm,based on mountainclimbing operators and fitness sharing,is proposed.It combines the genetic algorithm with the local searching algorithm effectively,which enhances the searching ability of the genetic algorithm.The mountainclimbing operator,based on the method of golden section,optimizes each dimension of the individual in turn .The results show that the improved algorithm is better than some current algorithms.The new algorithm not only has a rather high convergence speed,but also locates the global optimum with a rather large probability.

Key words: genetic algorithm; fitness sharing; mountain-climbing operator; the method of golden section

涂井先, 刘伟. 基于爬山算子和适应值共享的改进遗传算法[J]. 广东工业大学学报, 2011, 28(1): 78-81.

TU Jing-Xian, LIU Wei. An Improved Genetic Algorithm Based on Mountain-climbing Operators and Fitness Sharing[J]. Journal of Guangdong University of Technology, 2011, 28(1): 78-81.

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