A novel multimodal multiobjective memetic algorithm with a local detection mechanism and a clustering-based selection strategy-Reference-Cited by-同舟云学术

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A novel multimodal multiobjective memetic algorithm with a local detection mechanism and a clustering-based selection strategy

Published:2022-01-21 Issue:1 Volume:15 Page:31-43
ISSN:1865-9284
Container-title:Memetic Computing
language:en
Short-container-title:Memetic Comp.

Author:

Luo Naili,Ye Yulong,Lin Wu^ORCID,Lin Qiuzhen^ORCID,Leung Victor C. M.^ORCID

Funder

National Natural Science Foundation of China

the Joint Funds of the NSFC under Key Program

the Shenzhen Scientific Research and Development Funding Program

the Guangdong “Pearl River Talent Recruitment Program”

Shenzhen Science and Technology Innovation Commission

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12293-022-00353-0.pdf

Reference33 articles.

1. Yue C, Qu B, Yu K, Liang J, Li X (2019) A novel scalable test problem suite for multimodal multiobjective optimization. Swarm Evol Comput 48(2018):62–71. https://doi.org/10.1016/j.swevo.2019.03.011

2. Ishibuchi H, Peng Y, and Shang K (2019) A scalable multimodal multiobjective test problem. In: 2019 IEEE Congress on Evolutionary Computation (CEC) 2019 (pp 310-317) https://doi.org/10.1109/CEC.2019.8789971

3. Liang JJ et al. (2019) Problem definitions and evaluation criteria for the CEC 2019 special session on multimodal multiobjective optimization J. Sch Electr Eng Zhengzhou Univ Zhengzhou China, https://doi.org/10.13140/RG.2.2.31746.02247.

4. Grimme C, Kerschke P, and Trautmann H (2019) Multimodality in multi-objective optimization – More boon than bane? Lect Notes Comput Sci (Including Subser Lect Notes Artif Intell Lect Notes Bioinformatics), vol. 11411 LNCS, pp 126–138, https://doi.org/10.1007/978-3-030-12598-1_11.

5. Yue C, Qu B, Liang J (2018) A multiobjective particle swarm optimizer using ring topology for solving multimodal multiobjective problems. IEEE Trans Evol Comput 22(5):805–817. https://doi.org/10.1109/TEVC.2017.2754271

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