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Lookup NU author(s): Dr Shouyong Jiang
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.
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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