Hybrid tabu search algorithm for unrelated parallel machine scheduling in semiconductor fabs with setup times, job release, and expired times

• Published in: Computers & industrial engineering Vol. 165; p. 107915
• Main Authors: Chen, Changyu, Fathi, Mahdi, Khakifirooz, Marzieh, Wu, Kan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2022
• Subjects: Expired times; Job release; Mixed integer programming; Scheduling; Setup times; Tabu search; Unrelated parallel machines; Wafer fabrication; Tabu search; Unrelated parallel machines; Setup times; Job release; Expired times; Wafer fabrication; Mixed integer programming; Scheduling
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2021.107915

•Scheduling problem of ion implantation process of wafer fabrication.•Considering unrelated parallel machine scheduling with sequence-dependent setup times.•Considering job release time and expired time.•Maximizing the number of processed jobs, minimizing the maximum makespan.•Considering mixed-integer programming model adapted by a hybrid tabu search. This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processed on a specific machine, defined as: R|rj,eij,STsd|Cmax. The objective is first to maximize the number of processed jobs, then minimize the maximum completion time (makespan), and finally minimize the maximum completion times of the non-bottleneck machines. A mixed-integer programming (MIP) model is proposed as a solution approach and adopts a hybrid tabu search (TS) algorithm to acquire approximate feasible solutions. The MIP model has two phases and attempts to achieve the first two objectives. The hybrid TS algorithm has three phases and attempts to achieve all three objectives. In a real setting, computational results demonstrate that the maximum number of processed jobs can be acquired within a short time utilizing the hybrid TS algorithm (average 8 s). By comparing the two approaches, the TS outperforms the MIP model regarding solution quality and computational time for the second objective, minimizing the makespan. Furthermore, the third phase of the hybrid TS algorithm shows the effectiveness further to enhance the utilization of the ion implantation equipment.