Artificial Bee Colony Algorithm Based on Improvement of Chaotic Local Search

Zhao Shu-yang; Liu Wei; Cai Yao-he

doi:10.3969/j.issn.1007-7162.2013.04.009

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Artificial Bee Colony Algorithm Based on Improvement of Chaotic Local Search

更新时间：2026-05-27

- Artificial Bee Colony Algorithm Based on Improvement of Chaotic Local Search
- Vol. 30, Issue 4, Pages: 55-60(2013)
- 作者机构：
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- DOI：10.3969/j.issn.1007-7162.2013.04.009
  CLC：
- Online First：30 December 2013，
  
  Published：2013
- 稿件说明：
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赵舒阳, 刘伟, 蔡耀河. 一种改进的混沌局部搜索的人工蜂群算法[J]. 广东工业大学学报, 2013, 30(4): 55-60.

Zhao Shu-yang, Liu Wei, Cai Yao-he. Artificial Bee Colony Algorithm Based on Improvement of Chaotic Local Search[J]. 2013, 30(4): 55-60.
赵舒阳, 刘伟, 蔡耀河. 一种改进的混沌局部搜索的人工蜂群算法[J]. 广东工业大学学报, 2013, 30(4): 55-60. DOI： 10.3969/j.issn.1007-7162.2013.04.009.

Zhao Shu-yang, Liu Wei, Cai Yao-he. Artificial Bee Colony Algorithm Based on Improvement of Chaotic Local Search[J]. 2013, 30(4): 55-60. DOI： 10.3969/j.issn.1007-7162.2013.04.009.

摘要

人工蜂群算法具有鲁棒性强、收敛速度快且全局寻优性能优异等优点，但其局部搜索能力不足.为了克服此缺陷，提出了一种改进的混沌局部搜索的人工蜂群算法.新算法在每一代的所有个体的平均值附近利用混沌函数进行局部搜索，然后在搜索到的解和原食物源之间采用贪婪选择的原则确定下一代种群.基于6个标准测试函数的仿真结果表明，本算法能有效地加快收敛速度，提高最优解的精度，其性能优于已有的人工蜂群算法.

Abstract

The artificial bee colony algorithm has good robust，high convergence speed and outstanding performance in global optimization

but its ability of local search is not good enough. In order to improve its ability of local search

an improved chaotic artificial bee colony algorithm was proposed. In the new algorithm

local search is executed nearby the mean of all individuals

selecting the better individual between the solution searched by chaos function and previous population. Experimental simulation shows that the improved algorithm not only accelerates the convergence rate

but also improves its accuracy

whose performance is better than that of the existing artificial bee colony algorithm.

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