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

Author

Listed:
  • Shaojun Lu

    (Hefei University of Technology)

  • Min Kong

    (Anhui Normal University
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Zhiping Zhou

    (Hefei University of Technology)

  • Xinbao Liu

    (Hefei University of Technology)

  • Siwen Liu

    (Hefei University of Technology
    University of Texas at Dallas)

Abstract

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.

Suggested Citation

  • Shaojun Lu & Min Kong & Zhiping Zhou & Xinbao Liu & Siwen Liu, 2022. "A hybrid metaheuristic for a semiconductor production scheduling problem with deterioration effect and resource constraints," Operational Research, Springer, vol. 22(5), pages 5405-5440, November.
    • Handle: RePEc:spr:operea:v:22:y:2022:i:5:d:10.1007_s12351-022-00720-2
    DOI: 10.1007/s12351-022-00720-2
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    References listed on IDEAS

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    Cited by:

    1. Yi-Chun Wang & Si-Han Wang & Ji-Bo Wang, 2023. "Resource Allocation Scheduling with Position-Dependent Weights and Generalized Earliness–Tardiness Cost," Mathematics, MDPI, vol. 11(1), pages 1-11, January.

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