du.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
Heuristic optimization of the p-median problem and population re-distribution
Dalarna University, School of Technology and Business Studies, Statistics.
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: urn:nbn:se:du-13255ISBN: 978-91-89020-89-4 (print)OAI: oai:DiVA.org:du-13255DiVA: diva2:663359
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
List of papers
1. Does Euclidean distance work well when the p-median model is applied in rural areas?
Open this publication in new window or tab >>Does Euclidean distance work well when the p-median model is applied in rural areas?
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.

Keyword
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:nbn:se:du-10827 (URN)10.1007/s10479-012-1214-2 (DOI)000312070500005 ()
Funder
Swedish Retail and Wholesale Development Council
Available from: 2012-09-27 Created: 2012-09-27 Last updated: 2015-07-01Bibliographically approved
2. Distance measure and the p-median problem in rural areas
Open this publication in new window or tab >>Distance measure and the p-median problem in rural areas
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.

Publisher
12 p.
Series
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2012:07
Keyword
dense network, location model, optimal location, simulated annealing, travel time, urban areas
National Category
Other Computer and Information Science
Research subject
Komplexa system - mikrodataanalys, General Microdata Analysis - transports; Komplexa system - mikrodataanalys, General Microdata Analysis - methods
Identifiers
urn:nbn:se:du-11398 (URN)
Funder
Swedish Retail and Wholesale Development Council
Available from: 2012-12-06 Created: 2012-12-06 Last updated: 2015-07-01Bibliographically approved
3. How do different densities in a network affect the optimal location of service centers?
Open this publication in new window or tab >>How do different densities in a network affect the optimal location of service centers?
2013 (English)Report (Other academic)
Abstract [en]

The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

Place, publisher, year, edition, pages
Borlänge: Högskolan Dalarna, 2013
Series
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2013:15
Keyword
location-allocation problem, inter-urban location, intra-urban location, p-median model, network distance, simulated annealing heuristics
National Category
Probability Theory and Statistics
Research subject
Komplexa system - mikrodataanalys
Identifiers
urn:nbn:se:du-12606 (URN)
Available from: 2013-06-13 Created: 2013-06-13 Last updated: 2015-07-01
4. An empirical test of the gravity p-median model
Open this publication in new window or tab >>An empirical test of the gravity p-median model
2012 (English)Report (Other academic)
Abstract [en]

A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be implemented and tested empirically. We implemented the model in an empirical problem of locating locksmiths, vehicle inspections, and retail stores ofv ehicle spare-parts, and we compared the solutions with those of the p-median model. We found the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

Place, publisher, year, edition, pages
Borlänge: Högskolan Dalarna, 2012. 18 p.
Series
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2012:10
Keyword
distance decay, market share, network, retail, simulated annealing, travel time
National Category
Economic Geography Other Computer and Information Science
Research subject
Komplexa system - mikrodataanalys, General Microdata Analysis - retail; Komplexa system - mikrodataanalys, General Microdata Analysis - methods; Komplexa system - mikrodataanalys, General Microdata Analysis - transports
Identifiers
urn:nbn:se:du-11508 (URN)
Funder
Swedish Retail and Wholesale Development Council
Available from: 2012-12-21 Created: 2012-12-20 Last updated: 2015-07-01Bibliographically approved

Open Access in DiVA

fulltext(5257 kB)1486 downloads
File information
File name FULLTEXT02.pdfFile size 5257 kBChecksum SHA-512
7cddee0ecbe331d3846359694c34a4dde38d031f50fbe29d4215340d40923a0a61018ec157a856dff731dac72aa84bc74e8f36eb5716164846a2710281ad7156
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Han, Mengjie
By organisation
Statistics
Other Social Sciences not elsewhere specified

Search outside of DiVA

GoogleGoogle Scholar
Total: 1487 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 931 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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