M-machine Reentrant Permutation Flowshop Scheduling to Minimize Makespan Using Particle Swarm Optimization Algorithm

In recent years, the reentrant permutation flowshop scheduling problem has attracted the attention of both researchers and industry. A common assumption in the classical permutation flowshop scheduling model is that each job is processed on each machine at most once. However, reentrant flowshop scheduling allows a job to revisit a particular machine several times. Considering the complexity of the m-machine reentrant permutation flowshop scheduling problem, this paper proposes a particle swarm optimization algorithm to tackle the problem with makespan criterion. We conduct simulation experiments to test the effectiveness of the proposed algorithm and compare it with existing heuristics. Computational results and comparisons demonstrate that the proposed algorithm outperforms the existing heuristics in terms of objective solutions andcomputing times. Hence, enterprises can introduce the proposed method to generate profits by fully utilizing its advantages and lower overhead manufacturing costs.

کلیدواژه ها:

Scheduling ، Reentrant permutation flowshop ، Makespan ، Particle Swarm Optimization