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Distance measure and the p-median problem 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.ORCID iD: 0000-0003-4212-8582
Dalarna University, School of Technology and Business Studies, Human Geography.ORCID iD: 0000-0003-4871-833X
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-1015-8015
2012 (English)Report (Other academic)
Abstract [en]

The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

Place, publisher, year, edition, pages
2012. , p. 12
Series
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2012:07
Keywords [en]
dense network, location model, optimal location, simulated annealing, travel time, urban areas
National Category
Other Computer and Information Science
Research subject
Complex Systems – Microdata Analysis, General Microdata Analysis - transports; Complex Systems – Microdata Analysis, General Microdata Analysis - methods
Identifiers
URN: urn:nbn:se:du-11398OAI: oai:DiVA.org:du-11398DiVA, id: diva2:574796
Funder
Swedish Retail and Wholesale Development CouncilAvailable from: 2012-12-06 Created: 2012-12-06 Last updated: 2021-11-12Bibliographically 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: Dalarna University, 2013. p. 126
Series
Dalarna Doctoral Dissertations ; 1
National Category
Probability Theory and Statistics
Research subject
Research Profiles 2009-2020, Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-13255 (URN)978-91-89020-89-4 (ISBN)
Public defence
2013-11-22, Clas Ohlson, Borlänge, 13:00 (English)
Opponent
Supervisors
Available from: 2013-11-11 Created: 2013-11-11 Last updated: 2023-08-17Bibliographically approved

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Authority records

Carling, KennethHåkansson, JohanRebreyend, Pascal

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf