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Online production planning to maximize the number of on-time orders

Author

Listed:
  • Nicholas G. Hall

    (The Ohio State University)

  • Marc E. Posner

    (The Ohio State University)

  • Chris N. Potts

    (University of Southampton)

Abstract

We consider a production planning problem with two planning periods. Detailed planning occurs in the first period, when complete information is known about a set of orders that are initially available. An additional set of orders becomes available at the start of the second planning period. The objective is to maximize the number of on-time orders. We derive an upper bound on the competitive ratio of any deterministic online algorithm, relative to the performance of an algorithm with perfect information about the second set of orders. This ratio depends on the relative lengths of the two planning periods. We also describe an efficient algorithm that delivers a solution which asymptotically achieves this upper bound ratio as the number of jobs becomes large.

Suggested Citation

  • Nicholas G. Hall & Marc E. Posner & Chris N. Potts, 2021. "Online production planning to maximize the number of on-time orders," Annals of Operations Research, Springer, vol. 298(1), pages 249-269, March.
    • Handle: RePEc:spr:annopr:v:298:y:2021:i:1:d:10.1007_s10479-018-2928-6
    DOI: 10.1007/s10479-018-2928-6
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    References listed on IDEAS

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    Cited by:

    1. Feifeng Zheng & Yuhong Chen & Ming Liu & Yinfeng Xu, 2022. "Competitive analysis of online machine rental and online parallel machine scheduling problems with workload fence," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1060-1076, September.

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