标题:An Improved Backtracking Search Algorithm for Constrained Optimization Problems
作者:Zhao, Wenting; Wang, Lijin; Yin, Yilong; Wang, Bingqing; Wei, Yi; Yin, Yushan
通讯作者:Yin, Yilong
作者机构:[Zhao, Wenting; Wang, Lijin; Yin, Yilong; Wang, Bingqing; Wei, Yi; Yin, Yushan] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China.
会议名称:7th International Conference on Knowledge Science, Engineering and Management (KSEM)
会议日期:OCT 16-18, 2014
来源:KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT, KSEM 2014
出版年:2014
卷:8793
页码:222-233
关键词:constrained optimization; backtracking search algorithm; differential; evolution algorithm; breeder GA mutation operator; mutation
摘要:Backtracking search algorithm is a novel population-based stochastic technique. This paper proposes an improved backtracking search algorithm for constrained optimization problems. The proposed algorithm is combined with differential evolution algorithm and the breeder genetic algorithm mutation operator. The differential evolution algorithm is used to accelerate convergence at later iteration process, and the breeder genetic algorithm mutation operator is employed for the algorithm to improve the population diversity. Using the superiority of feasible point scheme and the parameter free penalty scheme to handle constrains, the improved algorithm is tested on 13 well-known benchmark problems. The results show the improved backtracking search algorithm is effective and competitive for constrained optimization problems.
收录类别:CPCI-S;EI;SCOPUS
WOS核心被引频次:5
Scopus被引频次:7
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84909583741&partnerID=40&md5=eccd1d60065880d33ceada6c011874eb
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