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Approximation schemes for the joint inventory selection and online resource allocation problem

Author

Listed:
  • Xingxing Chen
  • Jacob Feldman
  • Seung Hwan Jung
  • Panos Kouvelis

Abstract

In this paper, we introduce and study the joint inventory selection and online resource allocation problem, which is characterized by two sequential sets of decisions that are irrevocably linked. First, a decision maker (DM) must select starting inventory levels for a set of available resources. Subsequently, the DM must match arriving customers to available resources in an online fashion so as to maximize expected reward. We first study the problem in its most general form, before focusing on a specific version that arises at Anheuser Busch InBev (ABI). This particular application of our general setting is referred to as the ABI Trailer Problem, and it considers how ABI ships its beer to vendors via third‐party delivery trucks. In this problem, ABI must select the weights of preloaded trailers of beer, which are then matched in an online fashion to the arriving third‐party delivery trucks. For the general setting, we develop simple and easy‐to‐implement approaches that come with robust worst‐case performance guarantees. For the ABI setting, we reveal a simplifying structural property related to the optimal matching policy, which gives rise to a natural adaptation of our original approach. We test the efficacy of these policies through extensive numerical experiments, where we find that our approaches are either near‐optimal or improve upon state‐of‐the‐art benchmarks. In particular, using a data set from ABI, we are able to generate instances of the ABI Trailer Problem, on which our algorithm has the potential to yield revenue improvements in the range of millions of dollars per year.

Suggested Citation

  • Xingxing Chen & Jacob Feldman & Seung Hwan Jung & Panos Kouvelis, 2022. "Approximation schemes for the joint inventory selection and online resource allocation problem," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3143-3159, August.
  • Handle: RePEc:bla:popmgt:v:31:y:2022:i:8:p:3143-3159
    DOI: 10.1111/poms.13742
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    References listed on IDEAS

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    1. Dorothée Honhon & Vishal Gaur & Sridhar Seshadri, 2010. "Assortment Planning and Inventory Decisions Under Stockout-Based Substitution," Operations Research, INFORMS, vol. 58(5), pages 1364-1379, October.
    2. Yuhang Ma & Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "An Approximation Algorithm for Network Revenue Management Under Nonstationary Arrivals," Operations Research, INFORMS, vol. 68(3), pages 834-855, May.
    3. Clifford Stein & Van-Anh Truong & Xinshang Wang, 2020. "Advance Service Reservations with Heterogeneous Customers," Management Science, INFORMS, vol. 66(7), pages 2929-2950, July.
    4. Jacob B. Feldman & Huseyin Topaloglu, 2017. "Revenue Management Under the Markov Chain Choice Model," Operations Research, INFORMS, vol. 65(5), pages 1322-1342, October.
    5. Carri W. Chan & Vivek F. Farias, 2009. "Stochastic Depletion Problems: Effective Myopic Policies for a Class of Dynamic Optimization Problems," Mathematics of Operations Research, INFORMS, vol. 34(2), pages 333-350, May.
    6. Huseyin Topaloglu, 2009. "Using Lagrangian Relaxation to Compute Capacity-Dependent Bid Prices in Network Revenue Management," Operations Research, INFORMS, vol. 57(3), pages 637-649, June.
    7. Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "Dynamic Assortment Optimization for Reusable Products with Random Usage Durations," Management Science, INFORMS, vol. 66(7), pages 2820-2844, July.
    8. Kalyan Talluri & Garrett van Ryzin, 1999. "A Randomized Linear Programming Method for Computing Network Bid Prices," Transportation Science, INFORMS, vol. 33(2), pages 207-216, May.
    9. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    10. Martin I. Reiman & Qiong Wang, 2015. "Asymptotically Optimal Inventory Control for Assemble-to-Order Systems with Identical Lead Times," Operations Research, INFORMS, vol. 63(3), pages 716-732, June.
    11. Dan Zhang & William L. Cooper, 2005. "Revenue Management for Parallel Flights with Customer-Choice Behavior," Operations Research, INFORMS, vol. 53(3), pages 415-431, June.
    12. Levi DeValve & Saša Pekeč & Yehua Wei, 2020. "A Primal-Dual Approach to Analyzing ATO Systems," Management Science, INFORMS, vol. 66(11), pages 5389-5407, November.
    13. Lingxiu Dong & Panos Kouvelis & Zhongjun Tian, 2009. "Dynamic Pricing and Inventory Control of Substitute Products," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 317-339, December.
    14. Vineet Goyal & Retsef Levi & Danny Segev, 2016. "Near-Optimal Algorithms for the Assortment Planning Problem Under Dynamic Substitution and Stochastic Demand," Operations Research, INFORMS, vol. 64(1), pages 219-235, February.
    15. Siddharth Mahajan & Garrett van Ryzin, 2001. "Stocking Retail Assortments Under Dynamic Consumer Substitution," Operations Research, INFORMS, vol. 49(3), pages 334-351, June.
    16. Stefanus Jasin & Sunil Kumar, 2012. "A Re-Solving Heuristic with Bounded Revenue Loss for Network Revenue Management with Customer Choice," Mathematics of Operations Research, INFORMS, vol. 37(2), pages 313-345, May.
    17. Michael O. Ball & Maurice Queyranne, 2009. "Toward Robust Revenue Management: Competitive Analysis of Online Booking," Operations Research, INFORMS, vol. 57(4), pages 950-963, August.
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    1. Jung, Seung Hwan & Yang, Yunsi, 2023. "On the value of operational flexibility in the trailer shipment and assignment problem: Data-driven approaches and reinforcement learning," International Journal of Production Economics, Elsevier, vol. 264(C).

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