The Effect of the Migration Time on the Parallel Particle Swarm Optimization Algorithm

Abstract

The particle swarm optimization algorithm is a population-based algorithm used to solve optimization problems. In recent years, a parallel version of the PSO algorithm has proposed to solve complex application problems, and the situation has become the focus of researchers. Communication in this approach is ensured by the migration of particles between sub-population. In the parallel version of the PSO algorithm, parameters such as migration strategy, migration period, the topological structure must be determined. In this study, it was analyzed in which periods it would be more appropriate to perform migration procedures. In this context, the maximum number of iterations of 10000 is divided into three period intervals: 1000-3000, 3000-6000 and 6000-9000. Then, for cases where the number of threads is 2 and 4, the migration process is analyzed over these periods. © 2020 IEEE.