Scalarizing Functions in Decomposition-Based Multiobjective Evolutionary Algorithms

Jiang, Shouyong and Yang, Shengxiang and Wang, Yong and Liu, Xiaobin (2018) Scalarizing Functions in Decomposition-Based Multiobjective Evolutionary Algorithms. IEEE Transactions on Evolutionary Computation, 22 (2). pp. 296-313. ISSN 1089-778X

Full content URL: http://doi.org/10.1109/TEVC.2017.2707980

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Scalarizing Functions in Decomposition-Based Multiobjective Evolutionary Algorithms
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Abstract

Decomposition-based multiobjective evolutionary algorithms (MOEAs) have received increasing research interests due to their high performance for solving multiobjective optimization problems. However, scalarizing functions (SFs), 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 SFs and analyzing their effect in decomposition-based MOEAs. Additionally, we come up with an efficient framework for decomposition-based MOEAs based on the proposed SFs and some new strategies. Extensive experimental studies have demonstrated the effectiveness of the proposed SFs and algorithm.

Keywords:Decomposition, evolutionary algorithm, multiobjective optimization, scalarizing function (SF)
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:35170
Deposited On:30 Apr 2019 15:37

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