A Hybrid Genetic Algorithm for Parallel Machine Scheduling at Semiconductor Back-End Production - Adan, Jelle; Adan, Ivo; Akcay, Alp; Van den Dobbelsteen, Rick; Stokkermans, Joep (Proceedings of the International Conference on Automated Planning and Scheduling, 2018)
This paper addresses batch scheduling at a back-end semiconductor plant of Nexperia. This complex manufacturing environment is characterized by a large product and batch size variety, numerous parallel machines with large capacity differences, sequence and machine dependent setup times and machine eligibility constraints. A hybrid genetic algorithm is proposed to improve the scheduling process, the main features of which are a local search enhanced crossover mechanism, two additional fast local search procedures and a user-controlled multi-objective fitness function. Testing with real-life production data shows that this multi-objective approach can strike the desired balance between production time, setup time and tardiness, yielding high-quality practically feasible production schedules.