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Hierarchical Planning for Probabilistic Distribution Systems in Euclidean Spaces

Author

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  • David Simchi-Levi

    (Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027)

Abstract

We develop an analytical model to assist the design and control of probabilistic distribution systems. These distribution systems are characterized by the explicit inclusion of probabilistic elements. The probabilistic aspect considered is that only a subset of all potential customers needs service on any given working day. This subset of customers and their demand are determined according to some probability distribution. The cost of operating such systems is significantly affected by decisions on the number and locations of the distribution centers, the allocation of customers to each center, and the routing strategy. We propose a three-stage hierarchical approach in which decisions about the number of centers and their locations (first stage), customers allocations (second stage) and routing strategies (third stage) are combined to reduce total system cost.

Suggested Citation

  • David Simchi-Levi, 1992. "Hierarchical Planning for Probabilistic Distribution Systems in Euclidean Spaces," Management Science, INFORMS, vol. 38(2), pages 198-211, February.
    • Handle: RePEc:inm:ormnsc:v:38:y:1992:i:2:p:198-211
    DOI: 10.1287/mnsc.38.2.198
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    Cited by:

    1. L Muyldermans & D Cattrysse & D Van Oudheusden, 2003. "District design for arc-routing applications," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(11), pages 1209-1221, November.
    2. Cortinhal, Maria João & Mourão, Maria Cândida & Nunes, Ana Catarina, 2016. "Local search heuristics for sectoring routing in a household waste collection context," European Journal of Operational Research, Elsevier, vol. 255(1), pages 68-79.

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