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Convergence acceleration operator for multiobjective optimization

Adra, S.F., Dodd, T.J., Griffin, I.A. and Fleming, P.J. (2009) Convergence acceleration operator for multiobjective optimization. IEEE Transactions on Evolutionary Computation, 13 (4). pp. 825-847. ISSN 1089-778X


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A convergence acceleration operator (CAO) is described which enhances the search capability and the speed of convergence of the host multiobjective optimization algorithm. The operator acts directly in the objective space to suggest improvements to solutions obtained by a multiobjective evolutionary algorithm (MOEA). The suggested improved objective vectors are then mapped into the decision variable space and tested. This method improves upon prior work in a number of important respects, such as mapping technique and solution improvement. Further, the paper discusses implications for many-objective problems and studies the impact of the use of the CAO as the number of objectives increases. The CAO is incorporated with two leading MOEAs, the non-dominated sorting genetic algorithm and the strength Pareto evolutionary algorithm and tested. Results show that the hybridized algorithms consistently improve the speed of convergence of the original algorithm while maintaining the desired distribution of solutions. It is shown that the operator is a transferable component that can be hybridized with any MOEA.

Item Type: Article
Copyright, Publisher and Additional Information: © Copyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Evolutionary multiobjective optimization; neural networks
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Miss Anthea Tucker
Date Deposited: 05 Oct 2009 11:19
Last Modified: 18 Jun 2014 08:06
Published Version: http://dx.doi.org/10.1109/TEVC.2008.2011743
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number: 10.1109/TEVC.2008.2011743
URI: http://eprints.whiterose.ac.uk/id/eprint/9817

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