Balancing Objective Optimization and Constraint Satisfaction in Constrained Evolutionary Multi-Objective Optimization

Tian, Ye, Zhang, Yajie, Su, Yansen, Zhang, Xingyi, Tan, Kay Chen and Jin, Yaochu (2020) Balancing Objective Optimization and Constraint Satisfaction in Constrained Evolutionary Multi-Objective Optimization IEEE Transactions on Cybernetics.

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Abstract

Both objective optimization and constraint satisfaction are crucial for solving constrained multi-objective optimization problems, but existing evolutionary algorithms encounter difficulties in striking a good balance between them when tackling complex feasible regions. To address this issue, this paper proposes a two-stage evolutionary algorithm, which adjusts the fitness evaluation strategies during the evolutionary process to adaptively balance objective optimization and constraint satisfaction. The proposed algorithm can switch between the two stages according to the status of the current population, enabling the population to cross the infeasible region and reach the feasible regions in one stage, and to spread along the feasible boundaries in the other stage. Experimental studies on four benchmark suites and three real-world applications demonstrate the superiority of the proposed algorithm over the state-of-the-art algorithms, especially on problems with complex feasible regions.

Item Type:	Article
Divisions :	Faculty of Engineering and Physical Sciences
Authors :	Name Email ORCID Tian, Ye Zhang, Yajie Su, Yansen Zhang, Xingyi Tan, Kay Chen Jin, Yaochu Yaochu.Jin@surrey.ac.uk
Date :	30 August 2020
Copyright Disclaimer :	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords :	Constrained multi-objective optimization problems; Evolutionary algorithm; Objective optimization; Constraint satisfaction
Depositing User :	Diane Maxfield
Date Deposited :	11 Sep 2020 12:11
Last Modified :	11 Sep 2020 12:11
URI:	http://epubs.surrey.ac.uk/id/eprint/858562

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