Abstract
This research considers an unrelated parallel machine scheduling problem with ready times, machine eligibility and sequence-dependent setup times. The objective of the problem is to minimize the weight sum of setup times and delay times. Accordingly, a mixed integer programming formulation is presented. Since the single machine scheduling problem with sequence-dependent setup times is known to be NP-hard, a genetic algorithm is then developed with neighborhood search operator to solve the deterministic scheduling problem, which is also NP-hard. However, the ready time of each job is uncertain in real world. In this case, the optimal solution from deterministic model may become an infeasible or a bad solution. Therefore, the deterministic model may be unsuitable. A robust optimization model is then proposed for identifying a robust schedule across all possible scenarios. In this research, a robust optimization model is developed to solve the unrelated parallel machine scheduling problem in Semiconductor Assembly Factory with consideration of the ready times uncertainty. Due to the ready times uncertainty, this research not only minimizes setup time and delay time but also remains feasible in all scenarios.