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Heuristic optimization of the p-median problem and population re-distribution
Högskolan Dalarna, Akademin Industri och samhälle, Mikrodataanalys.ORCID-id: 0000-0003-4212-8582
2013 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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. 

Ort, förlag, år, upplaga, sidor
Borlänge: Dalarna University, 2013. , s. 126
Serie
Dalarna Doctoral Dissertations in Microdata Analysis ; 1
Nationell ämneskategori
Övrig annan samhällsvetenskap
Forskningsämne
Komplexa system - mikrodataanalys
Identifikatorer
URN: urn:nbn:se:du-13255ISBN: 978-91-89020-89-4 (tryckt)OAI: oai:DiVA.org:du-13255DiVA, id: diva2:663359
Disputation
2013-11-22, Clas Ohlson, Borlänge, 13:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2013-11-11 Skapad: 2013-11-11 Senast uppdaterad: 2019-08-26Bibliografiskt granskad
Delarbeten
1. Does Euclidean distance work well when the p-median model is applied in rural areas?
Öppna denna publikation i ny flik eller fönster >>Does Euclidean distance work well when the p-median model is applied in rural areas?
2012 (Engelska)Ingår i: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 201, nr 1, s. 83-97Artikel i tidskrift (Refereegranskat) 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.

Nyckelord
optimal location, Euclidean distance, network distance, travel time, spatial aggregation, location model
Nationell ämneskategori
Annan data- och informationsvetenskap
Forskningsämne
Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - metod; Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - transporter
Identifikatorer
urn:nbn:se:du-10827 (URN)10.1007/s10479-012-1214-2 (DOI)000312070500005 ()
Forskningsfinansiär
Handelns utvecklingsråd
Tillgänglig från: 2012-09-27 Skapad: 2012-09-27 Senast uppdaterad: 2019-08-26Bibliografiskt granskad
2. Distance measure and the p-median problem in rural areas
Öppna denna publikation i ny flik eller fönster >>Distance measure and the p-median problem in rural areas
2012 (Engelska)Rapport (Övrigt vetenskapligt)
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.

Förlag
s. 12
Serie
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2012:07
Nyckelord
dense network, location model, optimal location, simulated annealing, travel time, urban areas
Nationell ämneskategori
Annan data- och informationsvetenskap
Forskningsämne
Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - transporter; Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - metod
Identifikatorer
urn:nbn:se:du-11398 (URN)
Forskningsfinansiär
Handelns utvecklingsråd
Tillgänglig från: 2012-12-06 Skapad: 2012-12-06 Senast uppdaterad: 2019-08-26Bibliografiskt granskad
3. How do different densities in a network affect the optimal location of service centers?
Öppna denna publikation i ny flik eller fönster >>How do different densities in a network affect the optimal location of service centers?
2013 (Engelska)Rapport (Övrigt vetenskapligt)
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. 

Ort, förlag, år, upplaga, sidor
Borlänge: Högskolan Dalarna, 2013
Serie
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2013:15
Nyckelord
location-allocation problem, inter-urban location, intra-urban location, p-median model, network distance, simulated annealing heuristics
Nationell ämneskategori
Sannolikhetsteori och statistik
Forskningsämne
Komplexa system - mikrodataanalys
Identifikatorer
urn:nbn:se:du-12606 (URN)
Tillgänglig från: 2013-06-13 Skapad: 2013-06-13 Senast uppdaterad: 2019-08-26
4. An empirical test of the gravity p-median model
Öppna denna publikation i ny flik eller fönster >>An empirical test of the gravity p-median model
2012 (Engelska)Rapport (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Borlänge: Högskolan Dalarna, 2012. s. 18
Serie
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2012:10
Nyckelord
distance decay, market share, network, retail, simulated annealing, travel time
Nationell ämneskategori
Ekonomisk geografi Annan data- och informationsvetenskap
Forskningsämne
Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - handel; Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - metod; Komplexa system - mikrodataanalys, Allmänt Mikrodataaanalys - transporter
Identifikatorer
urn:nbn:se:du-11508 (URN)
Forskningsfinansiär
Handelns utvecklingsråd
Tillgänglig från: 2012-12-21 Skapad: 2012-12-20 Senast uppdaterad: 2019-08-26Bibliografiskt granskad

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