Comments on: Continuous approximation models in freight distribution management 2
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John Gunnar Carlsson [1]
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[1] University of Southern California
University of Southern California
Estados Unidos
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- Localización: Top, ISSN-e 1863-8279, ISSN 1134-5764, Vol. 25, Nº. 3, 2017, págs. 438-439
- Idioma: inglés
- DOI: 10.1007/s11750-017-0458-z
- Enlaces
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Resumen
Any time a group of authors of this caliber gets together, the result is sure to be a great read, and this article is no exception. This paper is a survey of the continuous approximation paradigm for logistics systems analysis, which is a reductionist philosophy that seeks to isolate the factors that influence a geospatial optimization problem most significantly. The defining feature of continuous approximation models is that “detailed data are replaced by concise summaries, and numerical methods are replaced by analytic models” (Daganzo 2005); this means that rather than finding an algorithm to solve a particular problem instance efficiently, one seeks a simple, algebraic expression that approximates the true cost of that problem under suitable probabilistic or geometric conditions (e.g. a limiting condition under uniformly distributed demand in a convex planar region).
