Learning to search promising regions by space partitioning for evolutionary methods-Reference-Cited by-同舟云学术

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Learning to search promising regions by space partitioning for evolutionary methods

Published:2024-12 Issue: Volume:91 Page:101726
ISSN:2210-6502
Container-title:Swarm and Evolutionary Computation
language:en
Short-container-title:Swarm and Evolutionary Computation

Author:

Xia Hai^ORCID,Li Changhe^ORCID,Tan Qingshan^ORCID,Zeng Sanyou,Yang Shengxiang

Publisher

Elsevier BV

Reference63 articles.

1. Exploration and exploitation in evolutionary algorithms: A survey;Črepinšek;ACM Comput. Surv.,2013

2. On evolutionary exploration and exploitation;Eiben;Fund. Inform.,1998

3. J. Lehman, K.O. Stanley, Evolving a diversity of virtual creatures through novelty search and local competition, in: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, 2011, pp. 211–218.

4. Diversity-guided evolutionary algorithms;Ursem,2002

5. Seeking multiple solutions: An updated survey on niching methods and their applications;Li;IEEE Trans. Evol. Comput.,2017

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