Solving the k-influence region problem with the GPU
dc.contributor.author
dc.date.accessioned
2016-01-28T10:41:41Z
dc.date.available
2016-01-28T10:41:41Z
dc.date.issued
2014
dc.identifier.issn
0020-0255
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dc.description.abstract
In this paper we study a problem that arises in the competitive facility location field. Facilities and customers are represented by points of a planar Euclidean domain. We associate a weighted distance to each facility to reflect that customers select facilities depending on distance and importance. We define, by considering weighted distances, the k-influence region of a facility as the set of points of the domain that has the given facility among their k-nearest/farthest neighbors. On the other hand, we partition the domain into subregions so that each subregion has a non-negative weight associated to it which measures a characteristic related to the area of the subregion. Given a weighted partition of the domain, the k-influence region problem finds the points of the domain where are new facility should be opened. This is done considering the known weight associated to the new facility and ensuring a minimum weighted area of its k-influence region. We present a GPU parallel approach, designed under CUDA architecture, for approximately solving the k-influence region problem. In addition, we describe how to visualize the solutions, which improves the understanding of the problem and reveals complicated structures that would be hard to capture otherwise. Integration of computation and visualization facilitates decision makers with an iterative what-if analysis process, to acquire more information to obtain an approximate optimal location. Finally, we provide and discuss experimental results showing the efficiency and scalability of our approach
dc.description.sponsorship
Work partially supported by the Spanish Ministerio de Economia y Competitividad under Grant TIN2010-20590-C02-02
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application/pdf
dc.language.iso
eng
dc.publisher
Elsevier
dc.relation
info:eu-repo/grantAgreement/MICINN//TIN2010-20590-C02-02/ES/AVANCES EN REALIDAD VIRTUAL PARA APLICACIONES PUNTERAS-UDG/
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Reproducció digital del document publicat a: http://dx.doi.org/10.1016/j.ins.2013.12.002
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© Information Sciences, 2014, vol. 269, p. 255-269
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Articles publicats (D-IMA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Solving the k-influence region problem with the GPU
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/embargoedAccess
dc.embargo.terms
Cap
dc.date.embargoEndDate
info:eu-repo/date/embargoEnd/2026-01-01
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
021568
dc.contributor.funder
dc.relation.ProjectAcronym