A multi-objective particle swarm optimization for openshop scheduling problems

This article proposes a particle swarm optimization (PSO) technique to address open-shop scheduling problems with multiple objectives. Because PSO was originally formulated to treat continuous optimization problems, we modified the particle position representation, particle velocity, and particle movement to consider the essentially discrete nature of scheduling problems. The modified PSO was tested using two benchmark problems to evaluate its performance. The results demonstrated that the algorithm performed better when only one swarm was used for all three objectives compared to the case where the swarm was divided into three sub-swarms for each objective.