The planar hub location problem: a probabilistic clustering approach
Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs us...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Iyigun, Cem [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media New York 2013 |
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| Übergeordnetes Werk: |
Enthalten in: Annals of operations research - Springer US, 1984, 211(2013), 1 vom: 01. Juni, Seite 193-207 |
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| Übergeordnetes Werk: |
volume:211 ; year:2013 ; number:1 ; day:01 ; month:06 ; pages:193-207 |
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| DOI / URN: |
10.1007/s10479-013-1394-4 |
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| 520 | |a Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs used) or started by visiting any of the hubs. The travel cost between hubs is discounted with a factor. It is assumed that each point can be served by multiple hubs. We propose a probabilistic clustering method for the planar hub-location problem which is analogous to the method of Iyigun and Ben-Israel (in Operations Research Letters 38, 207–214, 2010; Computational Optmization and Applications, 2013) for the solution of the multi-facility location problem. The proposed method is an iterative probabilistic approach assuming that all trips can be taken with probabilities that depend on the travel costs based on the hub locations. Each hub location is the convex combination of all data points and other hubs. The probabilities are updated at each iteration together with the hub locations. Computations stop when the hub locations stop moving. Fermat-Weber problem and multi-facility location problem are the special cases of the proposed approach. | ||
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10.1007/s10479-013-1394-4 doi (DE-627)OLC2111157724 (DE-He213)s10479-013-1394-4-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Iyigun, Cem verfasserin aut The planar hub location problem: a probabilistic clustering approach 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs used) or started by visiting any of the hubs. The travel cost between hubs is discounted with a factor. It is assumed that each point can be served by multiple hubs. We propose a probabilistic clustering method for the planar hub-location problem which is analogous to the method of Iyigun and Ben-Israel (in Operations Research Letters 38, 207–214, 2010; Computational Optmization and Applications, 2013) for the solution of the multi-facility location problem. The proposed method is an iterative probabilistic approach assuming that all trips can be taken with probabilities that depend on the travel costs based on the hub locations. Each hub location is the convex combination of all data points and other hubs. The probabilities are updated at each iteration together with the hub locations. Computations stop when the hub locations stop moving. Fermat-Weber problem and multi-facility location problem are the special cases of the proposed approach. Hub location problem Planar hub location Clustering Fermat–Weber problem Probabilistic assignments Enthalten in Annals of operations research Springer US, 1984 211(2013), 1 vom: 01. Juni, Seite 193-207 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:211 year:2013 number:1 day:01 month:06 pages:193-207 https://doi.org/10.1007/s10479-013-1394-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT GBV_ILN_4029 AR 211 2013 1 01 06 193-207 |
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10.1007/s10479-013-1394-4 doi (DE-627)OLC2111157724 (DE-He213)s10479-013-1394-4-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Iyigun, Cem verfasserin aut The planar hub location problem: a probabilistic clustering approach 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs used) or started by visiting any of the hubs. The travel cost between hubs is discounted with a factor. It is assumed that each point can be served by multiple hubs. We propose a probabilistic clustering method for the planar hub-location problem which is analogous to the method of Iyigun and Ben-Israel (in Operations Research Letters 38, 207–214, 2010; Computational Optmization and Applications, 2013) for the solution of the multi-facility location problem. The proposed method is an iterative probabilistic approach assuming that all trips can be taken with probabilities that depend on the travel costs based on the hub locations. Each hub location is the convex combination of all data points and other hubs. The probabilities are updated at each iteration together with the hub locations. Computations stop when the hub locations stop moving. Fermat-Weber problem and multi-facility location problem are the special cases of the proposed approach. Hub location problem Planar hub location Clustering Fermat–Weber problem Probabilistic assignments Enthalten in Annals of operations research Springer US, 1984 211(2013), 1 vom: 01. Juni, Seite 193-207 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:211 year:2013 number:1 day:01 month:06 pages:193-207 https://doi.org/10.1007/s10479-013-1394-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT GBV_ILN_4029 AR 211 2013 1 01 06 193-207 |
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10.1007/s10479-013-1394-4 doi (DE-627)OLC2111157724 (DE-He213)s10479-013-1394-4-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Iyigun, Cem verfasserin aut The planar hub location problem: a probabilistic clustering approach 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs used) or started by visiting any of the hubs. The travel cost between hubs is discounted with a factor. It is assumed that each point can be served by multiple hubs. We propose a probabilistic clustering method for the planar hub-location problem which is analogous to the method of Iyigun and Ben-Israel (in Operations Research Letters 38, 207–214, 2010; Computational Optmization and Applications, 2013) for the solution of the multi-facility location problem. The proposed method is an iterative probabilistic approach assuming that all trips can be taken with probabilities that depend on the travel costs based on the hub locations. Each hub location is the convex combination of all data points and other hubs. The probabilities are updated at each iteration together with the hub locations. Computations stop when the hub locations stop moving. Fermat-Weber problem and multi-facility location problem are the special cases of the proposed approach. Hub location problem Planar hub location Clustering Fermat–Weber problem Probabilistic assignments Enthalten in Annals of operations research Springer US, 1984 211(2013), 1 vom: 01. Juni, Seite 193-207 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:211 year:2013 number:1 day:01 month:06 pages:193-207 https://doi.org/10.1007/s10479-013-1394-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT GBV_ILN_4029 AR 211 2013 1 01 06 193-207 |
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10.1007/s10479-013-1394-4 doi (DE-627)OLC2111157724 (DE-He213)s10479-013-1394-4-p DE-627 ger DE-627 rakwb eng 004 VZ 3,2 ssgn Iyigun, Cem verfasserin aut The planar hub location problem: a probabilistic clustering approach 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs used) or started by visiting any of the hubs. The travel cost between hubs is discounted with a factor. It is assumed that each point can be served by multiple hubs. We propose a probabilistic clustering method for the planar hub-location problem which is analogous to the method of Iyigun and Ben-Israel (in Operations Research Letters 38, 207–214, 2010; Computational Optmization and Applications, 2013) for the solution of the multi-facility location problem. The proposed method is an iterative probabilistic approach assuming that all trips can be taken with probabilities that depend on the travel costs based on the hub locations. Each hub location is the convex combination of all data points and other hubs. The probabilities are updated at each iteration together with the hub locations. Computations stop when the hub locations stop moving. Fermat-Weber problem and multi-facility location problem are the special cases of the proposed approach. Hub location problem Planar hub location Clustering Fermat–Weber problem Probabilistic assignments Enthalten in Annals of operations research Springer US, 1984 211(2013), 1 vom: 01. Juni, Seite 193-207 (DE-627)12964370X (DE-600)252629-3 (DE-576)018141862 0254-5330 volume:211 year:2013 number:1 day:01 month:06 pages:193-207 https://doi.org/10.1007/s10479-013-1394-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW SSG-OLC-MAT GBV_ILN_4029 AR 211 2013 1 01 06 193-207 |
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Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs used) or started by visiting any of the hubs. The travel cost between hubs is discounted with a factor. It is assumed that each point can be served by multiple hubs. We propose a probabilistic clustering method for the planar hub-location problem which is analogous to the method of Iyigun and Ben-Israel (in Operations Research Letters 38, 207–214, 2010; Computational Optmization and Applications, 2013) for the solution of the multi-facility location problem. The proposed method is an iterative probabilistic approach assuming that all trips can be taken with probabilities that depend on the travel costs based on the hub locations. Each hub location is the convex combination of all data points and other hubs. The probabilities are updated at each iteration together with the hub locations. Computations stop when the hub locations stop moving. Fermat-Weber problem and multi-facility location problem are the special cases of the proposed approach. © Springer Science+Business Media New York 2013 |
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Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs used) or started by visiting any of the hubs. The travel cost between hubs is discounted with a factor. It is assumed that each point can be served by multiple hubs. We propose a probabilistic clustering method for the planar hub-location problem which is analogous to the method of Iyigun and Ben-Israel (in Operations Research Letters 38, 207–214, 2010; Computational Optmization and Applications, 2013) for the solution of the multi-facility location problem. The proposed method is an iterative probabilistic approach assuming that all trips can be taken with probabilities that depend on the travel costs based on the hub locations. Each hub location is the convex combination of all data points and other hubs. The probabilities are updated at each iteration together with the hub locations. Computations stop when the hub locations stop moving. Fermat-Weber problem and multi-facility location problem are the special cases of the proposed approach. © Springer Science+Business Media New York 2013 |
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Abstract Given the demand between each origin-destination pair on a network, the planar hub location problem is to locate the multiple hubs anywhere on the plane and to assign the traffic to them so as to minimize the total travelling cost. The trips between any two points can be nonstop (no hubs used) or started by visiting any of the hubs. The travel cost between hubs is discounted with a factor. It is assumed that each point can be served by multiple hubs. We propose a probabilistic clustering method for the planar hub-location problem which is analogous to the method of Iyigun and Ben-Israel (in Operations Research Letters 38, 207–214, 2010; Computational Optmization and Applications, 2013) for the solution of the multi-facility location problem. The proposed method is an iterative probabilistic approach assuming that all trips can be taken with probabilities that depend on the travel costs based on the hub locations. Each hub location is the convex combination of all data points and other hubs. The probabilities are updated at each iteration together with the hub locations. Computations stop when the hub locations stop moving. Fermat-Weber problem and multi-facility location problem are the special cases of the proposed approach. © Springer Science+Business Media New York 2013 |
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The planar hub location problem: a probabilistic clustering approach |
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