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Does Euclidean distance work well when the p-median model is applied in rural areas?
Dalarna University, School of Technology and Business Studies, Statistics.ORCID iD: 0000-0003-2317-9157
Dalarna University, School of Technology and Business Studies, Statistics.
Dalarna University, School of Technology and Business Studies, Human Geography.ORCID iD: 0000-0003-4871-833X
2012 (English)In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 201, no 1, 83-97 p.Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
2012. Vol. 201, no 1, 83-97 p.
Keyword [en]
optimal location, Euclidean distance, network distance, travel time, spatial aggregation, location model
National Category
Other Computer and Information Science
Research subject
Komplexa system - mikrodataanalys, General Microdata Analysis - methods; Komplexa system - mikrodataanalys, General Microdata Analysis - transports
Identifiers
URN: urn:nbn:se:du-10827DOI: 10.1007/s10479-012-1214-2ISI: 000312070500005OAI: oai:DiVA.org:du-10827DiVA: diva2:557110
Funder
Swedish Retail and Wholesale Development Council
Available from: 2012-09-27 Created: 2012-09-27 Last updated: 2015-07-01Bibliographically approved
In thesis
1. Heuristic optimization of the p-median problem and population re-distribution
Open this publication in new window or tab >>Heuristic optimization of the p-median problem and population re-distribution
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
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. 

Place, publisher, year, edition, pages
Borlänge: Högskolan Dalarna, 2013. 126 p.
Series
Dalarna Doctoral Dissertations, 2013:1
National Category
Other Social Sciences not elsewhere specified
Research subject
Komplexa system - mikrodataanalys
Identifiers
urn:nbn:se:du-13255 (URN)978-91-89020-89-4 (ISBN)
Public defence
2013-11-22, Clas Ohlson, Borlänge, 13:50 (English)
Opponent
Supervisors
Available from: 2013-11-11 Created: 2013-11-11 Last updated: 2015-07-01Bibliographically approved

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