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

TU  Jing-Xian; LIU  Wei

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

更新时间：2026-05-27

- An Improved Genetic Algorithm Based on Mountain-climbing Operators and Fitness Sharing
- Vol. 28, Issue 1, Pages: 78-81(2011)
- 作者机构：
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- Online First：25 December 2011，
  
  Published：2011
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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]. 2011, 28(1): 78-81.
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. DOI：

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

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.

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.

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references

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于歆杰,王赞基.对适应值共享遗传算法的分类及评价[J].模式识别与人工智能,2001,14(1):42-47.

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