Hybrid Particle Swarm Optimization for Permutation Flow Shop Scheduling

Scheduling problem is a kind of well-known combination optimization problem, and many scheduling problems are NP problems. Particle swarm optimization is used to solve the permutation flow shop-scheduling problem. The particle representation based on particle position sequence is presented, which can ensure that the feasible scheduling solutions are made and is applicable to computational model of particle swam optimization. The local search method based on particle position crossing-over is introduced. The computational results prove that hybrid particle swarm optimization can effectively solve the permutation flow shop-scheduling problem, and outperforms genetic algorithm and NEH heuristic method