[1]彭晓华,刘利强.混沌搜索策略的改进人工蜂群算法[J].智能系统学报编辑部,2015,10(6):927-933.[doi:10.11992/tis.201507032]
 PENG Xiaohua,LIU Liqiang.Improved artificial bee colony algorithm based on chaos searching strategy[J].CAAI Transactions on Intelligent Systems,2015,10(6):927-933.[doi:10.11992/tis.201507032]
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混沌搜索策略的改进人工蜂群算法(/HTML)
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《智能系统学报》编辑部[ISSN:1673-4785/CN:23-1538/TP]

卷:
第10卷
期数:
2015年6期
页码:
927-933
栏目:
出版日期:
2015-12-25

文章信息/Info

Title:
Improved artificial bee colony algorithm based on chaos searching strategy
作者:
彭晓华1 刘利强2
1. 辽宁工程技术大学基础教学部, 辽宁葫芦岛 125105;
2. 辽宁工程技术大学电气与控制工程学院, 辽宁葫芦岛 125105
Author(s):
PENG Xiaohua1 LIU Liqiang2
1. Ministry of basic education, Liaoning University of engineering and Technology, Huludao 125105, China;
2. College of electrical and control engineering, Liaoning University of engineering and Technology, Huludao 125105, China
关键词:
人工蜂群算法混沌搜索策略载波映射局部蜜源搜索蜂群多样性混沌-决策变量收敛性能仿真实验
Keywords:
artificial bee colony algorithmchaotic search strategycarrier mappinglocal search nectarthe swarm diversitychaos-decision variableconvergence performancesimulation experiment
分类号:
TP301.6
DOI:
10.11992/tis.201507032
摘要:
针对人工蜂群算法的蜂群缺乏多样性、全局和局部搜索能力差及收敛速度较慢,提出一种基于混沌搜索策略的改进人工蜂群算法。该算法通过载波映射,由混沌-决策变量的变换,产生新的邻域点,为采蜜蜂和被招募的观察蜂提供了更广阔的搜索空间和更优质的位置蜜源,增强蜂群多样性;同时,引进侦查蜂局部蜜源搜索较好地解决了算法易陷入局部极小的问题,改善了人工蜂群算法的收敛性能。最后由6个标准测试函数的仿真验证,得到基于混沌搜索策略的人工蜂群算法性能明显优于标准人工蜂群算法。
Abstract:
The current artificial bee colony algorithm results in the swarm lacking diversity, and the global and local search abilities and convergence speed are slow. We propose an improved artificial bee colony algorithm based on a chaotic search strategy. We map the algorithm with the carrier using a chaos decision variable transformation, generating new neighborhood points, and recruiting bees within a broader search space and from better source locations, while enhancing swarm diversity. In addition, the investigation of a local honey bee search better solved the algorithm problem of the local minimum and improved the convergence property of the artificial bee colony algorithm. The most recent six simulation validations of the standard test functions using the proposed artificial bee colony algorithm, based on the chaotic search strategy, are significantly better than the performance results of the current artificial bee colony algorithm.

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备注/Memo

备注/Memo:
收稿日期:2015-04-30;改回日期:。
基金项目:国家自然科学基金资助项目(51274118);辽宁省教育厅基金资助项目(L2012119).
作者简介:彭晓华,女,1963年生,教授,博士,主要研究方向为煤层瓦斯渗流理论研究、智能控制理论方法与应用研究。参加国家自然基金项目2项,主持和参加省教育厅科学研究基金项目各一项,主持或参加其他科研项目10余项。通过省市和学校鉴定的科研课题多项,获科研成果10余项。发表学术论文20余篇。刘利强,男,1988年生,硕士研究生,主要研究方向为智能检测与故障诊断。
通讯作者:刘利强.E-mail:2965131477@qq.com.
更新日期/Last Update: 1900-01-01