Solving multi-objective flowshop scheduling problem by Taguchi-based particle swarm optimization

摘要

A Taguchi-based particle swarm optimization (TBPSO) algorithm is proposed for solving multi-objective flowshop scheduling problems (FSPs). The proposed TBPSO integrates particle swarm optimization and Taguchi-based crossover. The proposed TBPSO is the use of a PSO to explore the optimal feasible region and the use of the Taguchi-based crossover to exploit the better solution. As a result, the TBPSO exhibits a significant improvement in Pareto best solutions of the FSP. By combining the advantages of exploration and exploitation, the TBPSO provides better results compared to the existing methods reported in the literature when solving multi-objective FSPs.