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How does the use of different road networks effect the optimal location of facilities in rural areas?
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
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 problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure.

Distance measure can vary if the accuracy of the road network varies. The rst aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to nd an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using dierent algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with an asymmetrically distributed population, Dalecarlia.

The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is optimized for. It is also shown that the simulated annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better location solutions.

Place, publisher, year, edition, pages
Borlänge: Högskolan Dalarna , 2012.
Series
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2012:02
Keyword [en]
road network eect, p-median problem, simulated annealing
National Category
Human Geography Probability Theory and Statistics Computer Science
Research subject
Complex Systems – Microdata Analysis, General Microdata Analysis - methods; Complex Systems – Microdata Analysis, General Microdata Analysis - transports
Identifiers
URN: urn:nbn:se:du-10858OAI: oai:DiVA.org:du-10858DiVA: diva2:558282
Available from: 2012-10-03 Created: 2012-10-02 Last updated: 2015-12-11Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
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  • nn-NO
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  • sv-SE
  • Other locale
More languages
Output format
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