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A PTAS for Semiconductor Burn-in Scheduling

Author

Listed:
  • Xiaotie Deng

    (City University of Hong Kong)

  • Haodi Feng

    (Shandong University)

  • Guojun Li

    (Shandong University
    Chinese Academy of Sciences)

  • Benyun Shi

    (City University of Hong Kong)

Abstract

In this paper a polynomial time approximation scheme, PTAS for short, is presented for the problem of scheduling jobs in a batch processing system. Each job has a pre-defined release date, which indicates when the job is available, and a pre-defined burn-in time, which is the least time needed for processing the job. At one time, at most B jobs can be processed together, where B is a pre-given number. No preemption is permitted.

Suggested Citation

  • Xiaotie Deng & Haodi Feng & Guojun Li & Benyun Shi, 2005. "A PTAS for Semiconductor Burn-in Scheduling," Journal of Combinatorial Optimization, Springer, vol. 9(1), pages 5-17, February.
    • Handle: RePEc:spr:jcomop:v:9:y:2005:i:1:d:10.1007_s10878-005-5480-7
    DOI: 10.1007/s10878-005-5480-7
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    References listed on IDEAS

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    1. Dorit S. Hochbaum & Dan Landy, 1997. "Scheduling Semiconductor Burn-In Operations to Minimize Total Flowtime," Operations Research, INFORMS, vol. 45(6), pages 874-885, December.
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    Cited by:

    1. Zhou, Shengchao & Xie, Jianhui & Du, Ni & Pang, Yan, 2018. "A random-keys genetic algorithm for scheduling unrelated parallel batch processing machines with different capacities and arbitrary job sizes," Applied Mathematics and Computation, Elsevier, vol. 334(C), pages 254-268.
    2. Ozturk, Onur, 2020. "A truncated column generation algorithm for the parallel batch scheduling problem to minimize total flow time," European Journal of Operational Research, Elsevier, vol. 286(2), pages 432-443.
    3. Li, Shuguang, 2017. "Approximation algorithms for scheduling jobs with release times and arbitrary sizes on batch machines with non-identical capacities," European Journal of Operational Research, Elsevier, vol. 263(3), pages 815-826.
    4. Zhou, Shengchao & Liu, Ming & Chen, Huaping & Li, Xueping, 2016. "An effective discrete differential evolution algorithm for scheduling uniform parallel batch processing machines with non-identical capacities and arbitrary job sizes," International Journal of Production Economics, Elsevier, vol. 179(C), pages 1-11.
    5. Li, Shuguang, 2017. "Parallel batch scheduling with inclusive processing set restrictions and non-identical capacities to minimize makespan," European Journal of Operational Research, Elsevier, vol. 260(1), pages 12-20.

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