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Scalarizing Functions in Decomposition-based Multiobjective Evolutionary Algorithms

Lookup NU author(s): Dr Shouyong Jiang

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This is the final published version of an article that has been published in its final definitive form by IEEE, 2018.

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Abstract

OAPA Decomposition-based multiobjective evolutionary algorithms have received increasing research interests due to their high performance for solving multiobjective optimization problems. However, scalarizing functions, which play a crucial role in balancing diversity and convergence in these kinds of algorithms, have not been fully investigated. This paper is mainly devoted to presenting two new scalarizing functions and analyzing their effect in decomposition-based multiobjective evolutionary algorithms. Additionally, we come up with an efficient framework for decomposition-based multiobjective evolutionary algorithms based on the proposed scalarizing functions and some new strategies. Extensive experimental studies have demonstrated the effectiveness of the proposed scalarizing functions and algorithm.

Publication metadata

Author(s): Jiang S, Yang S, Wang Y, Liu X

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Evolutionary Computation

Year: 2018

Volume: 22

Issue: 2

Pages: 296-313

Print publication date: 01/04/2018

Online publication date: 29/06/2017

Acceptance date: 05/05/2017

Date deposited: 27/07/2017

ISSN (print): 1089-778X

ISSN (electronic): 1941-0026

Publisher: IEEE

URL: https://doi.org/10.1109/TEVC.2017.2707980

DOI: 10.1109/TEVC.2017.2707980

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