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Does Euclidean distance work well when the p-median model is applied in rural areas?
Högskolan Dalarna, Akademin Industri och samhälle, Statistik.ORCID-id: 0000-0003-2317-9157
Högskolan Dalarna, Akademin Industri och samhälle, Statistik.ORCID-id: 0000-0003-4212-8582
Högskolan Dalarna, Akademin Industri och samhälle, Kulturgeografi.ORCID-id: 0000-0003-4871-833X
2012 (engelsk)Inngår i: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 201, nr 1, s. 83-97Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The p-median model is used to locate P centers to serve a geographically distributed population. A cornerstone of such a model is the measure of distance between a service center and demand points, i.e. the location of the population (customers, pupils, patients, and so on). Evidence supports the current practice of using Euclidean distance. However, we find that the location of multiple hospitals in a rural region of Sweden with anon-symmetrically distributed population is quite sensitive to distance measure, and somewhat sensitive to spatial aggregation of demand points.

sted, utgiver, år, opplag, sider
2012. Vol. 201, nr 1, s. 83-97
Emneord [en]
optimal location, Euclidean distance, network distance, travel time, spatial aggregation, location model
HSV kategori
Forskningsprogram
Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - metod; Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - transporter
Identifikatorer
URN: urn:nbn:se:du-10827DOI: 10.1007/s10479-012-1214-2ISI: 000312070500005OAI: oai:DiVA.org:du-10827DiVA, id: diva2:557110
Forskningsfinansiär
Swedish Retail and Wholesale Development CouncilTilgjengelig fra: 2012-09-27 Laget: 2012-09-27 Sist oppdatert: 2019-08-26bibliografisk kontrollert
Inngår i avhandling
1. Heuristic optimization of the p-median problem and population re-distribution
Åpne denne publikasjonen i ny fane eller vindu >>Heuristic optimization of the p-median problem and population re-distribution
2013 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

This thesis contributes to the heuristic optimization of the p-median problem and Swedish population redistribution.  

The p-median model is the most representative model in the location analysis. When facilities are located to a population geographically distributed in Q demand points, the p-median model systematically considers all the demand points such that each demand point will have an effect on the decision of the location. However, a series of questions arise. How do we measure the distances? Does the number of facilities to be located have a strong impact on the result? What scale of the network is suitable? How good is our solution? We have scrutinized a lot of issues like those. The reason why we are interested in those questions is that there are a lot of uncertainties in the solutions. We cannot guarantee our solution is good enough for making decisions. The technique of heuristic optimization is formulated in the thesis.  

Swedish population redistribution is examined by a spatio-temporal covariance model. A descriptive analysis is not always enough to describe the moving effects from the neighbouring population. A correlation or a covariance analysis is more explicit to show the tendencies. Similarly, the optimization technique of the parameter estimation is required and is executed in the frame of statistical modeling. 

sted, utgiver, år, opplag, sider
Borlänge: Dalarna University, 2013. s. 126
Serie
Dalarna Doctoral Dissertations in Microdata Analysis ; 1
HSV kategori
Forskningsprogram
Komplexa system - mikrodataanalys
Identifikatorer
urn:nbn:se:du-13255 (URN)978-91-89020-89-4 (ISBN)
Disputas
2013-11-22, Clas Ohlson, Borlänge, 13:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2013-11-11 Laget: 2013-11-11 Sist oppdatert: 2019-08-26bibliografisk kontrollert

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