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A Two-Phase Constraint-Handling Technique for Constrained Optimization

delete2023-10-01
delete6
PRE
AI
W
Weifeng Gao *
黄玲玲 (Lingling Huang)
H
Hong Li
J
Jin Xie
DOI:10.1109/TSMC.2023.3281550delete
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Abstract

Abstract

En 中文
A two-phase constraint-handling technique is integrated into the evolutionary algorithms to solve constrained optimization problems (called TPDE) in this article. In phase one, denoted as the exploration phase, an exterior penalty function method with the dynamic penalty coefficients is developed to compare any two candidate solutions, which aims to push the population into the feasible region. To reduce the computational burden, in phase two, denoted as the exploitation phase, an interior penalty function method with the dynamic penalty coefficients is developed, which enhances the search ability by using the information of constraints in feasible solutions. During the optimization process, differential evolution is adopted as the search algorithm to produce the offspring population. Experiment results on four benchmark test suites, namely, IEEE CEC 2006, IEEE CEC 2010, IEEE CEC 2017, and IEEE CEC 2020, indicate that TPDE is competitive with other popular algorithms.
Keywords:
Constrained optimization
differential evolution (DE)
exterior penalty
interior penalty

Journal

IEEE Transactions on Cybernetics cover
IEEE Transactions on Cybernetics
IF:
10.5
Papers:
1.1W
Citations:
5.0W

Organization

X
Xidian University
Scholars:
2.4W
Papers: 1.9W
Citations: 9.7K