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Volume 7
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Article

On the Efficacy of Ensemble of Constraint Handling Techniques in Self-Adaptive Differential Evolution

by
Hassan Javed
1,†,
Muhammad Asif Jan
1,*,†,
Nasser Tairan
2,†,
Wali Khan Mashwani
1,†,
Rashida Adeeb Khanum
3,†,
Muhammad Sulaiman
4,†,
Hidayat Ullah Khan
5,† and
Habib Shah
2,†
1
Institute of Numerical Sciences, Kohat University of Science & Technology, Kohat 26000, Pakistan
2
College of Computer Science, King Khalid University, Abha 61321, Saudi Arabia
3
Jinnah College for Women, University of Peshawar, Peshawar 25000, Pakistan
4
Department of Mathematics, Abdul Wali Khan University, Mardan 23200, Pakistan
5
Department of Economics, Abbottabad University of Science & Technology, Abbottabad 22010, Pakistan
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Mathematics 2019, 7(7), 635; https://doi.org/10.3390/math7070635
Received: 9 June 2019 / Revised: 8 July 2019 / Accepted: 10 July 2019 / Published: 17 July 2019
(This article belongs to the Special Issue Evolutionary Algorithms in Intelligent Systems)
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Abstract

Self-adaptive variants of evolutionary algorithms (EAs) tune their parameters on the go by learning from the search history. Adaptive differential evolution with optional external archive (JADE) and self-adaptive differential evolution (SaDE) are two well-known self-adaptive versions of differential evolution (DE). They are both unconstrained search and optimization algorithms. However, if some constraint handling techniques (CHTs) are incorporated in their frameworks, then they can be used to solve constrained optimization problems (COPs). In an early work, an ensemble of constraint handling techniques (ECHT) is probabilistically hybridized with the basic version of DE. The ECHT consists of four different CHTs: superiority of feasible solutions, self-adaptive penalty, ε -constraint handling technique and stochastic ranking. This paper employs ECHT in the selection schemes, where offspring competes with their parents for survival to the next generation, of JADE and SaDE. As a result, JADE-ECHT and SaDE-ECHT are developed, which are the constrained variants of JADE and SaDE. Both algorithms are tested on 24 COPs and the experimental results are collected and compared according to algorithms’ evaluation criteria of CEC’06. Their comparison, in terms of feasibility rate (FR) and success rate (SR), shows that SaDE-ECHT surpasses JADE-ECHT in terms of FR, while JADE-ECHT outperforms SaDE-ECHT in terms of SR. View Full-Text
Keywords: evolutionary algorithms; formal methods in evolutionary algorithms; self-adaptive differential evolutionary algorithms; constrained optimization; ensemble of constraint handling techniques; hybrid algorithms evolutionary algorithms; formal methods in evolutionary algorithms; self-adaptive differential evolutionary algorithms; constrained optimization; ensemble of constraint handling techniques; hybrid algorithms
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MDPI and ACS Style

Javed, H.; Jan, M.A.; Tairan, N.; Mashwani, W.K.; Khanum, R.A.; Sulaiman, M.; Khan, H.U.; Shah, H. On the Efficacy of Ensemble of Constraint Handling Techniques in Self-Adaptive Differential Evolution. Mathematics 2019, 7, 635. https://doi.org/10.3390/math7070635

AMA Style

Javed H, Jan MA, Tairan N, Mashwani WK, Khanum RA, Sulaiman M, Khan HU, Shah H. On the Efficacy of Ensemble of Constraint Handling Techniques in Self-Adaptive Differential Evolution. Mathematics. 2019; 7(7):635. https://doi.org/10.3390/math7070635

Chicago/Turabian Style

Javed, Hassan, Muhammad A. Jan, Nasser Tairan, Wali K. Mashwani, Rashida A. Khanum, Muhammad Sulaiman, Hidayat U. Khan, and Habib Shah. 2019. "On the Efficacy of Ensemble of Constraint Handling Techniques in Self-Adaptive Differential Evolution" Mathematics 7, no. 7: 635. https://doi.org/10.3390/math7070635

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