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Min–Max Scheduling of Batch or Drop-Line Jobs Under Agreeable Release and Processing Times

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  • Yuan Gao

    (School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China2School of Information Engineering, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China)

Abstract

We study the Pareto optimization scheduling on an unbounded parallel-batch machine with jobs having agreeable release dates and processing times for minimizing makespan and maximum cost simultaneously. The jobs considered in this paper are of two types: batch jobs and drop-line jobs. For batch jobs, the completion time of a job is given by the completion time of the batch containing this job. For drop-line jobs, the completion time of a job is given by the starting time of the batch containing this job plus the processing time of this job. For both of batch jobs and drop-line jobs, we present polynomial-time algorithms for finding all Pareto optimal points.

Suggested Citation

  • Yuan Gao, 2022. "Min–Max Scheduling of Batch or Drop-Line Jobs Under Agreeable Release and Processing Times," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 39(02), pages 1-15, April.
    • Handle: RePEc:wsi:apjorx:v:39:y:2022:i:02:n:s0217595921500238
    DOI: 10.1142/S0217595921500238
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    Cited by:

    1. Yijie Li, 2023. "Bicriteria fabrication scheduling of two-component jobs on a single machine," Operational Research, Springer, vol. 23(4), pages 1-13, December.

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