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Online Make-to-Order Joint Replenishment Model: Primal-Dual Competitive Algorithms

Author

Listed:
  • Niv Buchbinder

    () (Statistics and Operations Research Department, Tel Aviv University, Ramat Aviv 6997801, Israel)

  • Tracy Kimbrel

    () (National Science Foundation, Arlington, Virginia 22230)

  • Retsef Levi

    () (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139)

  • Konstantin Makarychev

    () (Microsoft Research, Redmond, Washington 98052)

  • Maxim Sviridenko

    () (Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom)

Abstract

In this paper, we study an online make-to-order variant of the classical joint replenishment problem (JRP) that has been studied extensively over the years and plays a fundamental role in broader planning issues, such as the management of supply chains. In contrast to the traditional approaches of the stochastic inventory theory, we study the problem using competitive analysis against a worst-case adversary.Our main result is a 3-competitive deterministic algorithm for the online version of the JRP. We also prove a lower bound of approximately 2.64 on the competitiveness of any deterministic online algorithm for the problem. Our algorithm is based on a novel primal-dual approach using a new linear programming relaxation of the offline JRP model. The primal-dual approach that we propose departs from previous primal-dual and online algorithms in rather significant ways. We believe that this approach can extend the range of problems to which online and primal-dual algorithms can be applied and analyzed.

Suggested Citation

  • Niv Buchbinder & Tracy Kimbrel & Retsef Levi & Konstantin Makarychev & Maxim Sviridenko, 2013. "Online Make-to-Order Joint Replenishment Model: Primal-Dual Competitive Algorithms," Operations Research, INFORMS, vol. 61(4), pages 1014-1029, August.
  • Handle: RePEc:inm:oropre:v:61:y:2013:i:4:p:1014-1029
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    File URL: http://dx.doi.org/10.1287/opre.2013.1188
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    References listed on IDEAS

    as
    1. Wilco Van den Heuvel & Albert P. M. Wagelmans, 2010. "Worst-Case Analysis for a General Class of Online Lot-Sizing Heuristics," Operations Research, INFORMS, vol. 58(1), pages 59-67, February.
    2. 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.
    3. Michael R. Wagner, 2010. "Fully Distribution-Free Profit Maximization: The Inventory Management Case," Mathematics of Operations Research, INFORMS, vol. 35(4), pages 728-741, November.
    4. Wei-Min Lan & Tava Lennon Olsen, 2006. "Multiproduct Systems with Both Setup Times and Costs: Fluid Bounds and Schedules," Operations Research, INFORMS, vol. 54(3), pages 505-522, June.
    5. Woonghee Tim Huh & Retsef Levi & Paat Rusmevichientong & James B. Orlin, 2011. "Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator," Operations Research, INFORMS, vol. 59(4), pages 929-941, August.
    6. Retsef Levi & Robin O. Roundy & David B. Shmoys, 2006. "Primal-Dual Algorithms for Deterministic Inventory Problems," Mathematics of Operations Research, INFORMS, vol. 31(2), pages 267-284, May.
    7. Pinar Keskinocak & R. Ravi & Sridhar Tayur, 2001. "Scheduling and Reliable Lead-Time Quotation for Orders with Availability Intervals and Lead-Time Sensitive Revenues," Management Science, INFORMS, vol. 47(2), pages 264-279, February.
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    Cited by:

    1. repec:taf:tprsxx:v:55:y:2017:i:4:p:1065-1084 is not listed on IDEAS
    2. Adam N. Elmachtoub & Retsef Levi, 2016. "Supply Chain Management with Online Customer Selection," Operations Research, INFORMS, vol. 64(2), pages 458-473, April.

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