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Data Surrogation Error in p-Median Models

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  • M. Hodgson

Abstract

The p-median model locates facilities to provide optimal service to target populations. Where, for some reason, an inappropriate variable is used to stand in for a target population's demand, less than ideal facility systems can result. This effect is termed surrogation error. In this paper, I introduce this concept and perform an experiment which, with data for 25 Canadian cities, demonstrates that significant surrogation error can occur if general population is used in place of children or senior populations. I identify some of the correlates of surrogation error and conclude with a warning to location scientists to be conscious of, and to try to avoid, this problem. Copyright Kluwer Academic Publishers 2002

Suggested Citation

  • M. Hodgson, 2002. "Data Surrogation Error in p-Median Models," Annals of Operations Research, Springer, vol. 110(1), pages 153-165, February.
    • Handle: RePEc:spr:annopr:v:110:y:2002:i:1:p:153-165:10.1023/a:1020771702141
    DOI: 10.1023/A:1020771702141
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    Cited by:

    1. Chandra Irawan & Said Salhi, 2015. "Solving large $$p$$ p -median problems by a multistage hybrid approach using demand points aggregation and variable neighbourhood search," Journal of Global Optimization, Springer, vol. 63(3), pages 537-554, November.
    2. Irawan, Chandra Ade & Salhi, Said & Scaparra, Maria Paola, 2014. "An adaptive multiphase approach for large unconditional and conditional p-median problems," European Journal of Operational Research, Elsevier, vol. 237(2), pages 590-605.
    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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