Skip to main content
Log in

Using scenario trees and progressive hedging for stochastic inventory routing problems

  • Published:
Journal of Heuristics Aims and scope Submit manuscript

Abstract

The Stochastic Inventory Routing Problem is a challenging problem, combining inventory management and vehicle routing, as well as including stochastic customer demands. The problem can be described by a discounted, infinite horizon Markov Decision Problem, but it has been showed that this can be effectively approximated by solving a finite scenario tree based problem at each epoch. In this paper the use of the Progressive Hedging Algorithm for solving these scenario tree based problems is examined. The Progressive Hedging Algorithm can be suitable for large-scale problems, by giving an effective decomposition, but is not trivially implemented for non-convex problems. Attempting to improve the solution process, the standard algorithm is extended with locking mechanisms, dynamic multiple penalty parameters, and heuristic intermediate solutions. Extensive computational results are reported, giving further insights into the use of scenario trees as approximations of Markov Decision Problem formulations of the Stochastic Inventory Routing Problem.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Adelman, D.: A price-directed approach to stochastic inventory/routing. Oper. Res. 52, 499–514 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  • Beasley, J.E.: Lagrangian relaxation. In: Reeves, C.R. (ed.) Modern Heuristic Techniques for Combinatorial Problems, pp. 243–303. Blackwell Scientific Publications, Oxford (1993)

    Google Scholar 

  • Campbell, A.M., Clarke, L.W., Kleywegt, A.J., Savelsbergh, M.W.P.: The inventory routing problem. In: Crainic, T.G., Laporte, G. (eds.) Fleet Management and Logistics. Kluwer Academic, Dordrecht (1998)

    Google Scholar 

  • Campbell, A.M., Clarke, L.W., Savelsbergh, M.W.P.: Inventory routing in practice. In: The Vehicle Routing Problem, Society for Industrial and Applied Mathematics, pp. 309-330. Philadelphia (2001)

  • Chien, T.W., Balakrishnan, A., Wong, R.T.: An integrated inventory allocation and vehicle routing problem. Transp. Sci. 23, 67–76 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  • Federgruen, A., Zipkin, P.: A combined vehicle routing and inventory allocation problem. Oper. Res. 32, 1019–1036 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  • Glover, F., Klingman, D.: Layering strategies for creating exploitable structure in linear and integer programs. Math. Program. 40, 165–181 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  • Haugen, K.K., Løkketangen, A., Woodruff, D.L.: Progressive hedging as a meta-heuristic applied to stochastic lot-sizing. Eur. J. Oper. Res. 132, 116–122 (2001)

    Article  MATH  Google Scholar 

  • Hvattum, L.M.: Heuristics for stochastic vehicle and inventory routing problems. PhD thesis, Molde University College, Molde, Norway (2007)

  • Hvattum, L.M., Løkketangen, A., Laporte, G.: Scenario tree based heuristics for stochastic inventory routing problems. Working paper 2007:2, Molde University College (2007)

  • Jonsbråten, T.W.: Oil field optimization under price uncertainty. J. Oper. Res. Soc. 49, 811–818 (1998)

    Article  MATH  Google Scholar 

  • Kall, P., Wallace, S.W.: Stochastic Programming. Wiley, New York (1994)

    MATH  Google Scholar 

  • Kleywegt, A.J., Nori, V.S., Savelsbergh, M.W.P.: The stochastic inventory routing problem with direct deliveries. Transp. Sci. 36, 94–118 (2002)

    Article  MATH  Google Scholar 

  • Kleywegt, A.J., Nori, V.S., Savelsbergh, M.W.P.: Dynamic programming approximations for a stochastic inventory routing problem. Transp. Sci. 38, 42–70 (2004)

    Article  Google Scholar 

  • Listes, O., Dekker, R.: A scenario aggregation based approach for determining a robust airline fleet composition. Transp. Sci. 39, 367–382 (2005)

    Article  Google Scholar 

  • Løkketangen, A., Woodruff, D.: Progressive hedging and tabu search applied to mixed integer (0,1) multi-stage stochastic programming. J. Heuristics 2, 111–128 (1996)

    Google Scholar 

  • Moin, N.H., Salhi, S.: Inventory routing problems: a logistical overview. J. Oper. Res. Soc. 58, 1185–1194 (2007)

    Article  MATH  Google Scholar 

  • Mulvey, J.M., Vladimirou, H.: Applying the progressive hedging algorithm to stochastic generalized networks. Ann. Oper. Res. 31, 399–424 (1991a)

    Article  MATH  MathSciNet  Google Scholar 

  • Mulvey, J.M., Vladimirou, H.: Solving multistage stochastic networks: An application of scenario aggregation. Networks 21, 619–643 (1991b)

    Article  MATH  MathSciNet  Google Scholar 

  • Puterman, M.L.: Markov Decision Processes. Wiley, New York (1994)

    Book  MATH  Google Scholar 

  • Resende, M.G.C., Ribeiro, C.C.: Greedy randomized adaptive search procedures. In: Glover, F., Kochenberger, G.A. (eds.) Handbook of Metaheuristics, pp. 219–249. Kluwer, Boston (2003)

    Google Scholar 

  • Rockafellar, R.T., Wets, R.J.-B.: Scenarios and policy aggregation in optimization under uncertainty. Math. Oper. Res. 16, 119–147 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  • Silver, E.A., Pyke, D.F., Peterson, R.: Inventory Management and Production Planning and Scheduling. Wiley, New York (1998)

    Google Scholar 

  • Toth, P., Vigo, D. (eds.): The Vehicle Routing Problem. SIAM, Philadelphia (2002)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Arne Løkketangen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hvattum, L.M., Løkketangen, A. Using scenario trees and progressive hedging for stochastic inventory routing problems. J Heuristics 15, 527–557 (2009). https://doi.org/10.1007/s10732-008-9076-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10732-008-9076-0

Keywords

Navigation