Multi-Objective Volleyball Premier League algorithm
作者： Reza Moghdani , Khodakaram Salimifard , Emrah Demir , Abdelkader Benyettou
DOI: 10.1016/J.KNOSYS.2020.105781
关键词: Computer science 、 Evolutionary algorithm 、 Engineering design process 、 Algorithm 、 Optimization problem 、 Set (abstract data type) 、 Benchmark (computing) 、 League 、 Point (geometry) 、 Particle swarm optimization
摘要: Abstract This paper proposes a novel optimization algorithm called the Multi-Objective Volleyball Premier League (MOVPL) for solving global problems with multiple objective functions. The is inspired by teams competing in volleyball premier league. strong point of this study lies extending multi-objective version (VPL), which recently used such scientific researches, incorporating well-known approaches including archive set and leader selection strategy to obtain optimal solutions given problem contradicted objectives. To analyze performance algorithm, ten benchmark complex objectives are solved compared two algorithms, namely Particle Swarm Optimization (MOPSO) Evolutionary Algorithm Based on Decomposition (MOEA/D). Computational experiments highlight that MOVPL outperforms state-of-the-art algorithms problems. In addition, has provided promising results engineering design
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