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Distance measure and the p-median problem in rural areas

Listed author(s):
  • Carling, Kenneth

    (HUI Research)

  • Han, Mengjie

    (School of Technology and Business Studies)

  • Håkansson, Johan


    (School of Technology and Business Studies)

  • Rebreyend, Pascal

    (School of Technology and Business Studies)

Registered author(s):

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region with a sparse, heterogeneous network and a non-symmetric distribution of the population. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as good a solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

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    Paper provided by HUI Research in its series HUI Working Papers with number 78.

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    Length: 12 pages
    Date of creation: 04 Dec 2012
    Handle: RePEc:hhs:huiwps:0078
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    1. L Bach, 1981. "The Problem of Aggregation and Distance for Analyses of Accessibility and Access Opportunity in Location-Allocation Models," Environment and Planning A, , vol. 13(8), pages 955-978, August.
    2. L Bach, 1981. "The problem of aggregation and distance for analyses of accessibility and access opportunity in location - allocation models," Environment and Planning A, Pion Ltd, London, vol. 13(8), pages 955-978, August.
    3. R. Francis & T. Lowe & M. Rayco & A. Tamir, 2009. "Aggregation error for location models: survey and analysis," Annals of Operations Research, Springer, vol. 167(1), pages 171-208, March.
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