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
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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. |
DOI | 10.1109/CEC.2014.6900548 |
URL | 查看来源 |
语种 | 英语English |
Scopus入藏号 | 2-s2.0-84908587583 |
引用统计 | |
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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