Multi-objective volleyball premier league algorithm

Moghdani, Reza, Salimifard, Khodakaram, Demir, Emrah ORCID: https://orcid.org/0000-0002-4726-2556 and Benyettou, Abdelkader 2020. Multi-objective volleyball premier league algorithm. Knowledge-Based Systems 196 , 105781. 10.1016/j.knosys.2020.105781

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Abstract

This paper proposes a novel optimization algorithm called the Multi-Objective Volleyball Premier League (MOVPL) algorithm for solving global optimization problems with multiple objective functions. The algorithm is inspired by the teams competing in a volleyball premier league. The strong point of this study lies in extending the multi-objective version of the Volleyball Premier League algorithm (VPL), which is recently used in such scientific researches, with incorporating the well-known approaches including archive set and leader selection strategy to obtain optimal solutions for a given problem with multiple contradicted objectives. To analyze the performance of the algorithm, ten multi-objective benchmark problems with complex objectives are solved and compared with two well-known multiobjective algorithms, namely Multi-Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D). Computational experiments highlight that the MOVPL outperforms the two state-of-the-art algorithms on multi-objective benchmark problems. In addition, the MOVPL algorithm has provided promising results on well-known engineering design optimization problems.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Publisher:	Elsevier
ISSN:	0950-7051
Date of First Compliant Deposit:	23 March 2020
Date of Acceptance:	17 March 2020
Last Modified:	24 Nov 2024 08:00
URI:	https://orca.cardiff.ac.uk/id/eprint/130541

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