科研成果详情

题名Online objective reduction for many-objective optimization problems
作者
发表日期2014-09-16
会议录名称Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
页码1165-1171
摘要For many-objective optimization problems, i.e. the number of objectives is greater than three, the performance of most of the existing Evolutionary Multi-objective Optimization algorithms will deteriorate to a certain degree. It is therefore desirable to reduce many objectives to fewer essential objectives, if applicable. Currently, most of the existing objective reduction methods are based on objective selection, whose computational process is, however, laborious. In this paper, we will propose an online objective reduction method based on objective extraction for the many-objective optimization problems. It formulates the essential objective as a linear combination of the original objectives with the combination weights determined based on the correlations of each pair of the essential objectives. Subsequently, we will integrate it into NSGA-II. Numerical studies have show the efficacy of the proposed approach.
DOI10.1109/CEC.2014.6900548
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语种英语English
Scopus入藏号2-s2.0-84908587583
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被引频次[WOS]:0   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/6490
专题北师香港浸会大学
作者单位
1.Department of Computer Science,Hong Kong Baptist University,Hong Kong,Hong Kong
2.United International College,BNU-HKBU,Zhuhai,China
第一作者单位北师香港浸会大学
推荐引用方式
GB/T 7714
Cheung,Yiu Ming,Gu,Fangqing. Online objective reduction for many-objective optimization problems[C], 2014: 1165-1171.
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