Abstract
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).
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.