Metaheuristic and hybrid simulation-based optimization for solving scheduling problems with major and minor setup times

This work has been motivated by an industrial case study in the field of printed circuit board's assembly production. Two- and four-stage Hybrid Flow Shop (HFS) scheduling problems with family major and minor sequence-dependent setup times are investigated. The majority of HFS scheduling problems are NP-hard optimization problems. Therefore, in this work, a metaheuristic and two hybrid simulation based optimization approaches will be presented to solve the problems and present a decision-making support tool for setting scheduling policies. Hybrid solution approaches that combine Genetic Algorithms (GA) with a heuristic are presented to solve the problems and compared to the GA. The optimization approaches are integrated into a discrete-event simulation model, which contributes as well as evaluates the quality of the obtained solutions. The formulated optimization problems are based on multi-objective measures to take into consideration the optimization of the system utilization through minimizing the makespan and the total number of major setup times as well as the customer satisfaction through minimizing the total tardiness. The presented solution techniques are evaluated based on real data, which are supported by the enterprise.