论文信息 - A Comparison among Wolf Pack Search and Four other Optimization Algorithms

A Comparison among Wolf Pack Search and Four other Optimization Algorithms

The main objective of this paper is applying a comparison between the Wolf Pack Search (WPS) as a newly introduced intelligent algorithm with several other known algorithms including Particle Swarm Optimization (PSO), Shuffl ed Frog Leaping (SFL), Binary and Continues Genetic algorit hms. All algorithms are applied on two benchmark cost functi o s. The aim is to identify the best algorithm in terms of more spe ed and accuracy in finding the solution, where speed is measured in te rms of function evaluations. The simulation results show that the S FL algorithm with less function evaluations becomes first if the simu lation time is important, while if accuracy is the significant iss ue, WPS and PSO would have a better performance. Keywords—Wolf Pack Search, Particle Swarm Optimization, Continues Genetic Algorithm, Binary Genetic Algorit hm, Shuffled Frog Leaping, Optimization.

Maryam Kouzehgar | Shahla Shoghian | M. Kouzehgar | Shahla Shoghian

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