[1]黎延海,拓守恒.一种求解多模态复杂问题的混合和声差分算法[J].智能系统学报,2018,13(02):281-289.[doi:10.11992/tis.201612030]
 LI Yanhai,TUO Shouheng.Hybrid algorithm based on harmony search and differential evolution for solving multi-modal complex problems[J].CAAI Transactions on Intelligent Systems,2018,13(02):281-289.[doi:10.11992/tis.201612030]
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一种求解多模态复杂问题的混合和声差分算法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第13卷
期数:
2018年02期
页码:
281-289
栏目:
出版日期:
2018-04-15

文章信息/Info

Title:
Hybrid algorithm based on harmony search and differential evolution for solving multi-modal complex problems
作者:
黎延海 拓守恒
陕西理工大学 数学与计算机科学学院, 陕西 汉中 723001
Author(s):
LI Yanhai TUO Shouheng
School of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong 723001, China
关键词:
和声搜索差分进化混合机制更新成功率变异策略多模态优化问题
Keywords:
harmony searchdifferential evolutionhybrid mechanismsuccess ratemutation strategymultimodal optimization problem
分类号:
TP391
DOI:
10.11992/tis.201612030
摘要:
针对多模态复杂优化问题,提出了一种基于和声搜索和差分进化的混合优化算法:HHSDE算法。在不同的进化阶段,HHSDE算法依据累积加权更新成功率来自适应地选择和声算法或差分算法作为更新下一代种群的方式,并改进了差分算法的变异策略来平衡差分算法的全局与局部搜索能力。通过对10个多模态Benchmark函数进行测试,利用Wilcoxon秩和检验对不同算法的计算结果进行比较,结果表明HHSDE算法具有收敛速度快,求解精度高,稳定性好等优势。
Abstract:
This paper presents a hybrid algorithm (HHSDE) based on harmony search and differential evolution for solving multi-modal complex optimization. In different evolution stages, HHSDE algorithm self-adaptively selects harmony search (HS) or differential evolution (DE) algorithm as the means of updating the next generation of population on basis of the cumulative success rate of weighted update, in addition, it changes the mutation strategy of differential evolution (DE) algorithm for balancing the global and local search ability of the differential evolution (DE) algorithm. To investigate the performance of HHSDE, ten multi-modal Benchmark functions were tested. The experimental results, compared with other algorithms by Wilcoxon rank sum test, indicate that HHSDE algorithm has the advantages such as fast convergence speed, high solution precision and excellent stability.

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备注/Memo

备注/Memo:
收稿日期:2016-12-26。
基金项目:国家自然科学基金项目(11401357);陕西省教育厅科研项目(14JK1130);陕西理工大学校级科研项目(SLGKY2017-05).
作者简介:黎延海,男,1981年生,讲师,硕士,主要研究方向为智能优化算法及应用;拓守恒,男,1978年生,副教授,博士研究生,CCF会员,主要研究方向为智能优化算法、生物信息分析与处理,发表学术论文多篇。
通讯作者:黎延海.E-mail:Chenxi81991@sina.com.
更新日期/Last Update: 1900-01-01