Solving the job shop scheduling problem via a modified PSO

The job shop scheduling problem plays an important role not only in the manufacturing systems, but also in the industrial process for enhancing the resource utilization. This paper describes a modified particle swarm optimization (MPSO) with the passive congregation and the restriction factor for solving the job shop scheduling problem, by minimizing the objective function of the makespan. The several examples of the different sizes are used to verify the performance of the MPSO algorithm. Finally, this algorithm is compared with the tabu search algorithm (TS), the combination of the shifting bottleneck method and the tabu search algorithm (TSSB algorithm), the combination of the tabu search algorithm with the simulated annealing (TSSA algorithm), and the guided tabu search/path relinking algorithm (GTSPR). The results show that the proposed MPSO algorithm works better than the all algorithms for solving the job shop scheduling problem.