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Balancing Convergence and Diversity by Using Two Different Reproduction Operators in MOEA/D: Some Preliminary Work

Wang, Z and Zhang, Q and Li, H (2016) Balancing Convergence and Diversity by Using Two Different Reproduction Operators in MOEA/D: Some Preliminary Work. In: UNSPECIFIED, ? - ?.

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Abstract

© 2015 IEEE. This paper studies how to use two reproduction operators with different characteristics for balancing the convergence and the diversity in MOEA/D. We consider two operators. One is a differential evolution and polynomial mutation, and the other is a neighbor learning and inversion mutation. We show that these two operators have different search abilities. Then we propose a scheme to use these two operators in our recently proposed MOEA/D-GR framework. We test the proposed algorithm on some benchmark problems to demonstrate its effectiveness.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 27 Feb 2016 11:10
Last Modified: 30 Jan 2019 16:20
URI: http://repository.essex.ac.uk/id/eprint/16133

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