Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization

Author:

Shu Tianye1ORCID,Shang Ke1ORCID,Ishibuchi Hisao1ORCID,Nan Yang1ORCID

Affiliation:

1. Department of Computer Science and Engineering, Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen, China

Funder

Shenzhen Science and Technology Program

Guangdong Provincial Key Laboratory

The Stable Support Plan Program of Shenzhen Natural Science Fund

National Natural Science Foundation of China

the Program for Guangdong Introducing Innovative and Enterpreneurial Teams

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Last-X-Generation Archiving Strategy for Multi-Objective Evolutionary Algorithms;2024 IEEE Congress on Evolutionary Computation (CEC);2024-06-30

2. LTR-HSS: A Learning-to-Rank Based Framework for Hypervolume Subset Selection;Lecture Notes in Computer Science;2024

3. How to Find a Large Solution Set to Cover the Entire Pareto Front in Evolutionary Multi-Objective Optimization;2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2023-10-01

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