The World of Computer Science and Information Technology Journal

7

Authors: Farid Bourennani

Nowadays, we have access to unprecedented high-performance computing (HPC) resources that can be utilized to solve complex and computationally expensive optimization problem. However, one of the problems with existing metaheuristics algorithms is that they do not scale well. For example, particle swarm optimization (PSO) which is one of the most known metaheuristics performs poorly in terms of accuracy and convergence speed with large dimensional problems. In this paper, we propose a broadcast and distributed PSO using message passing interface (MPI) that showed to be faster and more accurate than the commonly utilized distributed master-slave version of PSO for the studied large-scale optimization problems.