Simulation-based optimization for solving a hybrid flow shop scheduling problem

This paper describes the solution of a hybrid flow shop (HFS) scheduling problem of a printed circuit board assembly. The production comprises four surface-mount device placement machines on the first stage and five automated optical inspection machines on the second stage. The objective is to minimize the makespan and the total tardiness. The paper compares three approaches to solve the HFS scheduling problem: an integrated simulation-based optimization algorithm (ISBO) developed by the authors and two metaheuristics, simulated annealing and tabu search. All approaches lead to an improvement in terms of producing more jobs on time while minimizing the makespan compared to the decision rules used so far in the analyzed company. The ISBO delivers results much faster than the two metaheuristics. The two metaheuristics lead to slightly better results than the ISBO in terms of total tardiness.