A comparative study of local search within a surrogate-assisted multi-objective memetic algorithm framework for expensive problems
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- 作者：Pramudita Satria Palara ; pramsp@ftmd.itb.ac.id" class="auth_mail" title="E-mail the corresponding author ; Takeshi Tsuchiyaa ; tsuchiya@mail.ecc.u-tokyo.ac.jp" class="auth_mail" title="E-mail the corresponding author ; Geoffrey Thomas Parksb ; gtp10@cam.ac.uk" class="auth_mail" title="E-mail the corresponding author
- 关键词：Memetic algorithm ; Multi-objective ; Local surrogate ; Local search ; Expensive problems
- 刊名：Applied Soft Computing
- 出版年：2016
- 出版时间：June 2016
- 年：2016
- 卷：43
- 期：Complete
- 页码：1-19
- 全文大小：2773 K
文摘
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We studied the effect of local search on multi-objective memetic algorithm.
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The base algorithm is single surrogate-based multi-objective memetic algorithm.
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We investigated four types of local search.
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Local search based on achievement-type function were more robust than the others.
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The achievement-type function found better solutions on real-world problem.