Distance predicting functions and applied location-allocation models
Dominique Peeters () and
Journal of Geographical Systems, 2000, vol. 2, issue 2, 167-184
Abstract. Distances between demand points and potential sites for implementing facilities are essential inputs to location-allocation models. Computing actual road distances for a given problem can be quite burdensome since it involves digitalizing a network, while approximating these distances by l p -norms, using for instance a geographical information system, is much easier. We may then wonder how sensitive the solutions of a location-allocation model are to the choice of a particular metric. In this paper, simulations are performed on a lattice of 225 points using the k-median problem. Systematic changes in p and in the orientation of the orthogonal reference axes are used. Results suggest that the solutions of the k-median are rather insensitive to the specification of the l p -norm.
Keywords: Key words: Location; allocation; p-median; distance predicting function; JEL classification: C6; R3; R4 (search for similar items in EconPapers)
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