Heuristic and metaheuristic simulation-based optimization for solving a hybrid flow shop scheduling problem

This paper solves the hybrid flow shop (HFS) scheduling problem of a printed circuit board assembly. The production system investigated consists of four Surface-Mount Device (SMD) placement machines in the first production stage and five Automated Optical Inspection (AOI) machines in the second production stage. The objective is to minimize the makespan and to minimize the total tardiness. This paper describes and compares four approaches to solve the HFS scheduling problem: an integrated simulation-based optimization (ISBO) and three metaheuristics, simulated annealing, tabu search and genetic algorithm. 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 printed circuit board assembly. The integrated simulation-based optimization delivers results much faster than the metaheuristics. The metaheuristics lead to slightly better results in terms of total tardiness