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Dynamic Speed Optimization in Supply Chains with Stochastic Demand

Author

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  • Peter Berling

    (Department of Industrial Management and Logistics, Lund University, 221 00 Lund, Sweden)

  • Victor Martínez-de-Albéniz

    (IESE Business School, University of Navarra, 08034 Barcelona, Spain)

Abstract

In this paper, we analyze how to continuously adjust the speed in a supply chain with stochastic demand. For each unit (e.g., truckload, shipping container) in the chain, one must decide at which speed it should be moved downstream, given the state of the system, to minimize total supply chain costs. We decompose the problem into a set of one-dimensional subproblems that can be easily solved and characterize the optimal variable speed policy: under some assumptions, we show that it is optimal to set a speed that is first increasing in the distance to the market, and then decreasing. As a result, at optimality a given unit will experience an accelerating speed and then it will be slowed down, unless a demand occurs, in which case, the speed will be adjusted upward. We finally provide a transportation case study where we estimate the benefits of a variable-speed compared to a fixed-speed policy and show them to be significant both financially and from a CO 2 -emissions perspective.

Suggested Citation

  • Peter Berling & Victor Martínez-de-Albéniz, 2016. "Dynamic Speed Optimization in Supply Chains with Stochastic Demand," Transportation Science, INFORMS, vol. 50(3), pages 1114-1127, August.
    • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:3:p:1114-1127
    DOI: 10.1287/trsc.2014.0561
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    References listed on IDEAS

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    Cited by:

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    2. Peter Berling & Danja R. Sonntag, 2022. "Inventory control in production–inventory systems with random yield and rework: The unit‐tracking approach," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2628-2645, June.
    3. Höller, Simon J. & Özsen, Raik & Thonemann, Ulrich W., 2020. "Determining optimal parameters for expediting policies under service level constraints," European Journal of Operational Research, Elsevier, vol. 281(2), pages 274-285.
    4. Drent, Melvin & Moradi, Poulad & Arts, Joachim, 2023. "Efficient emission reduction through dynamic supply mode selection," European Journal of Operational Research, Elsevier, vol. 311(3), pages 925-941.

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