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Near-linear-time approximation algorithms for scheduling a batch-processing machine with setups and job rejection

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  • Jinwen Ou

    (Jinan University)

Abstract

In this paper we study a single batch-processing machine scheduling model. In our model, a set of jobs having different release dates needs to be scheduled onto a single machine that can process a batch of jobs simultaneously at a time. Each batch incurs a fixed setup time and a fixed setup cost. The decision maker may reject some of the jobs by paying penalty cost so as to achieve a tight makespan, but the total rejection penalty cost is required to be no greater than a given value. Our model extends several existing batch-processing machine scheduling models in the literature. We present efficient approximation algorithms with near-linear-time complexities.

Suggested Citation

  • Jinwen Ou, 2020. "Near-linear-time approximation algorithms for scheduling a batch-processing machine with setups and job rejection," Journal of Scheduling, Springer, vol. 23(5), pages 525-538, October.
    • Handle: RePEc:spr:jsched:v:23:y:2020:i:5:d:10.1007_s10951-020-00657-4
    DOI: 10.1007/s10951-020-00657-4
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    References listed on IDEAS

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    Cited by:

    1. Ou, Jinwen & Lu, Lingfa & Zhong, Xueling, 2023. "Parallel-batch scheduling with rejection: Structural properties and approximation algorithms," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1017-1032.

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