Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/12960
Título: A GIS based model for solving the planar Huff problem considering different demand distributions and forbidden regions
Autores/as: Suárez-Vega, Rafael 
Santos-Peñate, Dolores R. 
Dorta-González, Pablo 
Clasificación UNESCO: 530999 Otras (especificar)
5309 Organización industrial y políticas gubernamentales
Palabras clave: Competitive location
Planar Huff problem
Demand distribution
Surface model of population
Forbidden region, et al.
Fecha de publicación: 2010
Resumen: In this paper, we have used Geographical Information Systems (GIS) to solve the planar Huff problem considering different demand distributions and forbidden regions. Most of the papers connected with the competitive location problems consider that the demand is aggregated in a finite set of points. In other few cases, the models suppose that the demand is distributed along the feasible region according to a functional form, mainly a uniform distribution. In this case, in addition to the discrete and uniform demand distributions we have considered that the demand is represented by a population surface model, that is, a raster map where each pixel has associated a value corresponding to the population living in the area that it covers. Taking into account the demand distribution and the location and size of the existing facilities, we have obtained a raster map where each pixel has associated the estimated capture for a new competing firm if it decides to locate on it. Finally, a real example is solved where the solution for the three scenarios is compared.
URI: http://hdl.handle.net/10553/12960
Fuente: 9th International Conference on Operations Research (ICOR2010) La Habana
Colección:Actas de congresos
miniatura
Adobe PDF (419,43 kB)
Vista completa

Visitas

76
actualizado el 06-abr-2024

Descargas

32
actualizado el 06-abr-2024

Google ScholarTM

Verifica


Comparte



Exporta metadatos



Este elemento está sujeto a una licencia Licencia Creative Commons Creative Commons