Distance predicting functions and applied location-allocation models. |
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| Authors: | Dominique Peeters Isabelle Thomas |
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| Institution: | (1) Department of Geography, Center of Operations Research and EconometricsUniversité catholique de Louvain, 1348 Louvain-la-Neuve, Belgium, BE;(2) National Fund for Scientific Research Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium (e-mail: Isabelle@geog.ucl.ac.be), BE |
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| 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.
Received: 12 October 1998/Accepted: 17 September 1999 |
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| Keywords: | : Location allocation p-median distance predicting function |
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