[1]拓守恒,雍龙泉,邓方安.动态调整策略改进的和声搜索算法[J].智能系统学报,2015,10(02):307-315.[doi:10.3969/j.issn.1673-4785.201402019]
 TUO Shouheng,YONG Longquan,DENG Fangan.Dynamic adjustment strategy for improving the harmony search algorithm[J].CAAI Transactions on Intelligent Systems,2015,10(02):307-315.[doi:10.3969/j.issn.1673-4785.201402019]
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动态调整策略改进的和声搜索算法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第10卷
期数:
2015年02期
页码:
307-315
栏目:
出版日期:
2015-04-25

文章信息/Info

Title:
Dynamic adjustment strategy for improving the harmony search algorithm
作者:
拓守恒 雍龙泉 邓方安
陕西理工学院 数计学院, 陕西 汉中 723001
Author(s):
TUO Shouheng YONG Longquan DENG Fang’an
School of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong 723001, China
关键词:
自适应调整策略高维优化问题和声搜索算法
Keywords:
adaptive adjustment strategyhigh-dimensional optimization problemsharmony search algorithm
分类号:
TP391
DOI:
10.3969/j.issn.1673-4785.201402019
文献标志码:
A
摘要:
为了得到高维复杂问题的全局高精度最优解,提出一种动态调整策略,并用该策略改进和声搜索算法。算法选取和声记忆库中最差和声向量作为优化调整目标,随着迭代的进行,逐步降低决策变量的调整概率,该方法能够使得算法在全局探索能力和局部高精度开发能力之间实现平衡,有效提高了新和声更新最差和声的成功率。通过6个高维Benchmark测试函数的仿真结果表明,提出的动态调整策略能够有效提高和声搜索算法求解高维复杂优化问题的能力。
Abstract:
A dynamic adjustment strategy is used to improve the harmony search algorithm for solving high-dimensional multimodal global optimization problems. It chooses the worst harmony vector from the harmony memory (HM) as an optimization objective vector. With the process of iteration, the adjustment probability of decision variables is reduced step by step. It can achieve the balance effectively between the global exploration powers and local exploitation competence, and can increase the success rate of evolution. Finally, the experimental results of 16 high-dimension benchmark functions demonstrated that the proposed method can enhance the performance and robustness of the harmony search algorithm obviously in solving large scale multimodal optimization problems.

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备注/Memo

备注/Memo:
收稿日期:2014-2-21;改回日期:。
基金项目:国家自然科学基金资助项目(11401357),陕西省教育厅科研资助项目(14JK1141);汉中市科技局科研资助项目(2013hzzx-39);陕西理工学院科研资助项目(SLGKY 13-27).
作者简介: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;雍龙泉,男,1980年生,副教授,博士,主要研究方向为优化理论与算法设计、智能优化算法等;邓方安,男,1963生,教授,博士,主要研究方向为代数系统、粗糙集理论和优化理论。
通讯作者:拓守恒.tuo_sh@126.com.
更新日期/Last Update: 2015-06-15