Research Repository

Scalarizing Functions in Decomposition-Based Multiobjective Evolutionary Algorithms

Jiang, S and Yang, S and Wang, Y and Liu, X (2018) 'Scalarizing Functions in Decomposition-Based Multiobjective Evolutionary Algorithms.' IEEE Transactions on Evolutionary Computation, 22 (2). 296 - 313. ISSN 1089-778X

07962254.pdf - Published Version

Download (2MB) | Preview


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.

Item Type: Article
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: Elements
Date Deposited: 26 Jun 2018 14:17
Last Modified: 07 Apr 2021 10:16

Actions (login required)

View Item View Item