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Unbounded parallel-batch scheduling under agreeable release and processing to minimize total weighted number of tardy jobs

Author

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  • Yuan Gao

    (Zhengzhou University)

  • Jinjiang Yuan

    (Zhengzhou University)

Abstract

We study the unbounded parallel-batch scheduling problem with the jobs having agreeable release dates and processing times to minimize the total weighted number of tardy jobs. In this problem, we consider two types of jobs: 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 show that (1) the problems are binary NP-hard, (2) the problems are solvable in pseudo-polynomial times, and when the number of weights is a constant, the problems are solvable in polynomial times, and (3) the problems have a fully polynomial-time approximation scheme.

Suggested Citation

  • Yuan Gao & Jinjiang Yuan, 2019. "Unbounded parallel-batch scheduling under agreeable release and processing to minimize total weighted number of tardy jobs," Journal of Combinatorial Optimization, Springer, vol. 38(3), pages 698-711, October.
    • Handle: RePEc:spr:jcomop:v:38:y:2019:i:3:d:10.1007_s10878-019-00407-z
    DOI: 10.1007/s10878-019-00407-z
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    References listed on IDEAS

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    4. T.C.E. Cheng & C.T. Ng & J.J. Yuan & Z.H. Liu, 2004. "Single machine parallel batch scheduling subject to precedence constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(7), pages 949-958, October.
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    Cited by:

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    2. Jae Won Jang & Yong Jae Kim & Byung Soo Kim, 2022. "A Three-Stage ACO-Based Algorithm for Parallel Batch Loading and Scheduling Problem with Batch Deterioration and Rate-Modifying Activities," Mathematics, MDPI, vol. 10(4), pages 1-26, February.

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