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A replacement strategy for balancing convergence and diversity in MOEA/D

Wang, Zhenkun and Zhang, Qingfu and Gong, Maoguo and Zhou, Aimin (2014) A replacement strategy for balancing convergence and diversity in MOEA/D. In: 2014 IEEE Congress on Evolutionary Computation (CEC), 2014-07-06 - 2014-07-11.

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Abstract

This paper studies the replacement schemes in MOEA/D and proposes a new replacement named global replacement. It can improve the performance of MOEA/D. Moreover, trade-offs between convergence and diversity can be easily controlled in this replacement strategy. It also shows that different problems need different trade-offs between convergence and diversity. We test the MOEA/D with this global replacement on three sets of benchmark problems to demonstrate its effectiveness.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 07 Aug 2015 09:30
Last Modified: 23 Sep 2022 18:48
URI: http://repository.essex.ac.uk/id/eprint/14477

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