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Distance measure and the p-median problem in rural areas

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Carling, Kenneth & Han, Mengjie & Håkansson, Johan & Rebreyend, Pascal, 2012. "Distance measure and the p-median problem in rural areas," HUI Working Papers 78, HUI Research.
  • Handle: RePEc:hhs:huiwps:0078
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    References listed on IDEAS

    as
    1. Trevor Hale & Christopher Moberg, 2003. "Location Science Research: A Review," Annals of Operations Research, Springer, vol. 123(1), pages 21-35, October.
    2. Kenneth Carling & Mengjie Han & Johan Håkansson, 2012. "Does Euclidean distance work well when the p-median model is applied in rural areas?," Annals of Operations Research, Springer, vol. 201(1), pages 83-97, December.
    3. Drezner, Tammy & Drezner, Zvi, 2007. "The gravity p-median model," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1239-1251, June.
    4. 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.
    5. S. L. Hakimi, 1964. "Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph," Operations Research, INFORMS, vol. 12(3), pages 450-459, June.
    6. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    dense network; location model; optimal location; simulated annealing; travel time; urban areas;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
    • R50 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - General

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