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Joint replenishment meets scheduling

Author

Listed:
  • Péter Györgyi

    (Eötvös Loránd Research Network)

  • Tamás Kis

    (Eötvös Loránd Research Network)

  • Tímea Tamási

    (Eötvös Loránd Research Network
    ELTE Eötvös Loránd University)

  • József Békési

    (University of Szeged)

Abstract

In this paper, we consider a combination of the joint replenishment problem (JRP) and single-machine scheduling with release dates. There is a single machine and one or more item types. Each job has a release date, a positive processing time, and it requires a subset of items. A job can be started at time t only if all the required item types were replenished between the release date of the job and time point t. The ordering of item types for distinct jobs can be combined. The objective is to minimize the total ordering cost plus a scheduling criterion, such as total weighted completion time or maximum flow time, where the cost of ordering a subset of items simultaneously is the sum of a joint ordering cost, and an additional item ordering cost for each item type in the subset. We provide several complexity results for the offline problem, and competitive analysis for online variants with min–sum and min–max criteria, respectively.

Suggested Citation

  • Péter Györgyi & Tamás Kis & Tímea Tamási & József Békési, 2023. "Joint replenishment meets scheduling," Journal of Scheduling, Springer, vol. 26(1), pages 77-94, February.
    • Handle: RePEc:spr:jsched:v:26:y:2023:i:1:d:10.1007_s10951-022-00768-0
    DOI: 10.1007/s10951-022-00768-0
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    References listed on IDEAS

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    1. Retsef Levi & Robin Roundy & David Shmoys & Maxim Sviridenko, 2008. "A Constant Approximation Algorithm for the One-Warehouse Multiretailer Problem," Management Science, INFORMS, vol. 54(4), pages 763-776, April.
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    Cited by:

    1. Péter Györgyi & Tamás Kis & Tímea Tamási, 2023. "An online joint replenishment problem combined with single machine scheduling," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-20, July.

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