A hybrid metaheuristic for a semiconductor production scheduling problem with deterioration effect and resource constraints

The scheduling of jobs and resources is challenging in semiconductor production and large-scale integrated circuit design. This paper considers a semiconductor manufacturing alliance where there are several manufacturers with limited resources, and the goal is to minimize the makespan by making decisions on resources allocation, jobs assignment, jobs batching, and batches sequencing. The job processing time is investigated based on a convex resource formulation integrated with the deterioration effect. Jobs in a single batch have the same starting and finishing time. The batch setup time is defined by the time-dependent function. Meanwhile, limited resources can be allocated to jobs to improve the production efficiency in each batch. Focusing on settings where all jobs have been assigned to manufacturers, this paper derives some important structural properties. Then, for the case with a single manufacturer, an optimal schedule rule is established to arrange jobs and resources. Furthermore, a Variable Neighborhood Search algorithm based on the Biogeography-Based Optimization is designed to solve the problem, which is proved to be NP-hard. The computational results show that our algorithm can generate more robust and appropriate schedules compared to other algorithms from the literature.