Effects of The Different Migration Periods on Parallel Multi-Swarm PSO
Şaban Gülcü, Halife Kodaz · 2016
In recent years, there has been an increasing interest in parallel computing.In parallel computing, multiple computing resources are used simultaneously in solving a problem.There are multiple processors that will work concurrently and the program is divided into different tasks to be simultaneously solved.Recently, a considerable literature has grown up around the theme of metaheuristic algorithms.Particle swarm optimization (PSO) algorithm is a popular metaheuristic algorithm.The parallel comprehensive learning particle swarm optimization (PCLPSO) algorithm based on PSO has multiple swarms based on the master-slave paradigm and works cooperatively and concurrently.The migration period is an important parameter in PCLPSO and affects the efficiency of the algorithm.We used the well-known benchmark functions in the experiments and analysed the performance of PCLPSO using different migration periods.