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An external archive guided multiobjective evolutionary approach based on decomposition for continuous optimization

Li, Y and Cai, X and Fan, Z and Zhang, Q (2014) An external archive guided multiobjective evolutionary approach based on decomposition for continuous optimization. In: UNSPECIFIED, ? - ?.

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Abstract

© 2014 IEEE. In this paper, we propose a decomposition based multiobjective evolutionary algorithm that extracts information from an external archive to guide the evolutionary search for continuous optimization problem. The proposed algorithm used a mechanism to identify the promising regions(subproblems) through learning information from the external archive to guide evolutionary search process. In order to demonstrate the performance of the algorithm, we conduct experiments to compare it with other decomposition based approaches. The results validate that our proposed algorithm is very competitive.

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 > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 07 Aug 2015 09:28
Last Modified: 17 Oct 2019 21:15
URI: http://repository.essex.ac.uk/id/eprint/14476

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