The p-Regions Problem
dc.citation.journalTitle | GEOGRAPHICAL ANALYSIS | |
dc.contributor.author | Duque, Juan C. | spa |
dc.contributor.author | Church, Richard L. | spa |
dc.contributor.author | Middleton, Richard S. | spa |
dc.contributor.department | Universidad EAFIT. Departamento de Economía y Finanzas | spa |
dc.contributor.researchgroup | Research in Spatial Economics (RISE) | eng |
dc.date.accessioned | 2021-04-12T14:26:14Z | |
dc.date.available | 2021-04-12T14:26:14Z | |
dc.date.issued | 2011-01-01 | |
dc.description.abstract | The p-regions problem involves the aggregation or clustering of n small areas into p spatially contiguous regions while optimizing some criteria. The main objective of this article is to explore possible avenues for formulating this problem as a mixed integer-programming (MIP) problem. The critical issue in formulating this problem is to ensure that each region is a spatially contiguous cluster of small areas. We introduce three MIP models for solving the p regions problem. Each model minimizes the sum of dissimilarities between all pairs of areas within each region while guaranteeing contiguity. Three strategies designed to ensure contiguity are presented: (1) an adaptation of the Miller, Tucker, and Zemlin tour-breaking constraints developed for the traveling salesman problem; (2) the use of ordered-area assignment variables based upon an extension of an approach by Cova and Church for the geographical site design problem; and (3) the use of flow constraints based upon an extension of work by Shirabe. We test the efficacy of each formulation as well as specify a strategy to reduce overall problem size. © 2011 The Ohio State University. | eng |
dc.identifier | https://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=1596 | |
dc.identifier.doi | 10.1016/j.econlet.2010.08.004 | |
dc.identifier.issn | 00167363 | |
dc.identifier.issn | 15384632 | |
dc.identifier.other | WOS;000284250100002 | |
dc.identifier.other | SCOPUS;2-s2.0-77956875873 | |
dc.identifier.uri | http://hdl.handle.net/10784/28026 | |
dc.language.iso | eng | eng |
dc.publisher | WILEY-BLACKWELL | |
dc.relation.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650793094&doi=10.1111%2fj.1538-4632.2010.00810.x&partnerID=40&md5=2ae7db1c96724e29b1dea410ff18b3d2 | |
dc.rights | https://v2.sherpa.ac.uk/id/publication/issn/0016-7363 | |
dc.source | GEOGRAPHICAL ANALYSIS | |
dc.subject.keyword | cluster analysis | eng |
dc.subject.keyword | data management | eng |
dc.subject.keyword | data set | eng |
dc.subject.keyword | econometrics | eng |
dc.subject.keyword | linear programing | eng |
dc.subject.keyword | numerical model | eng |
dc.subject.keyword | optimization | eng |
dc.title | The p-Regions Problem | eng |
dc.type | article | eng |
dc.type | info:eu-repo/semantics/article | eng |
dc.type | info:eu-repo/semantics/publishedVersion | eng |
dc.type | publishedVersion | eng |
dc.type.local | Artículo | spa |
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