Enhancing Classic Coverage Location Models
AbstractAn important area of regional science has long been location analysis and modeling. Its significance continues, now more formally known as location science, and has evolved because of the need to address complex facility siting problems and issues. This article focuses on classic coverage location problems, and how advances along theoretical and methodological fronts have enabled such problems to be viewed in new ways. Specifically, notions of implicit and explicit coverage, along with geographic information systems (GIS), provide the capacity to reconceptualize as well as better model intended planning goals and objectives. This article reviews covering problems and presents a comparative framework for both linkage and assessment. This research is significant because evolving models enable issues of frame independence, and the modifiable area unit problem, to be addressed, making planning and analysis more reliable and valuable.
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Bibliographic InfoArticle provided by in its journal International Regional Science Review.
Volume (Year): 33 (2010)
Issue (Month): 2 (April)
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- Murray, Alan T. & Wei, Ran, 2013. "A computational approach for eliminating error in the solution of the location set covering problem," European Journal of Operational Research, Elsevier, vol. 224(1), pages 52-64.
- Caro Vela, María Dolores & Paralera Morales, Concepción, 2011. "Una propuesta para la localización de áreas de servicio y descanso adaptadas al transporte de mercancías peligrosas mediante un modelo de optimización; aplicación al territorio español = A Propo," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 11(1), pages 17-32, June.
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