Parallelizing particle swarm optimization

This paper focuses on a parallel version of particle swarm optimization (PSO) algorithm which can significantly reduces execution time for solving complex large-scale optimization problems. This paper gives an overview of PSO algorithm, and then proposes a design and an implementation of parallel PSO. The proposed algorithm eliminates redundant synchronizations and optimizes message transfer to overlap communication with computation. The experimental results showed that 13.2 times speedup was obtained by the proposed parallel PSO algorithm with 14 processors.