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Decomposing inventory routing problems with approximate value functions

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  • Alejandro Toriello
  • George Nemhauser
  • Martin Savelsbergh

Abstract

We present a time decomposition for inventory routing problems. The methodology is based on valuing inventory with a concave piecewise linear function and then combining solutions to single‐period subproblems using dynamic programming techniques. Computational experiments show that the resulting value function accurately captures the inventory's value, and solving the multiperiod problem as a sequence of single‐period subproblems drastically decreases computational time without sacrificing solution quality. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010

Suggested Citation

  • Alejandro Toriello & George Nemhauser & Martin Savelsbergh, 2010. "Decomposing inventory routing problems with approximate value functions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(8), pages 718-727, December.
    • Handle: RePEc:wly:navres:v:57:y:2010:i:8:p:718-727
    DOI: 10.1002/nav.20433
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    Cited by:

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    3. Andreas Bärmann & Alexander Martin & Hanno Schülldorf, 2017. "A Decomposition Method for Multiperiod Railway Network Expansion—With a Case Study for Germany," Transportation Science, INFORMS, vol. 51(4), pages 1102-1121, November.
    4. Onur Kaya & Dogus Ozkok, 2020. "A Blood Bank Network Design Problem with Integrated Facility Location, Inventory and Routing Decisions," Networks and Spatial Economics, Springer, vol. 20(3), pages 757-783, September.
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    6. Dimitri J. Papageorgiou & Myun-Seok Cheon & George Nemhauser & Joel Sokol, 2015. "Approximate Dynamic Programming for a Class of Long-Horizon Maritime Inventory Routing Problems," Transportation Science, INFORMS, vol. 49(4), pages 870-885, November.

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