Method and system for dynamic monitoring of minimized maximum distance location

Abstract

The invention provides a method and a system for dynamic monitoring of the minimized maximum distance location. The method includes presetting a customer point set C, a facility point set F and a candidate position set P; inserting all the facility points f and customer points c into an undirected graph shown as the formula Go=(Vo,Eo) for representing a road net to divide edges of the Eo into new edges; to each point p<CUF and on first consideration that the edge e where the points p located belongs to Eo, setting two end points of the e as v1 and vr, dividing the e into two parts, namely the part from the v1 to the p and the part from the p to the vr so as to make the p as a new vertex of the undirected graph, adding all the new vertexes to generate a new undirected graph shown as the formula G=(VE); dividing the undirected graph G into n sub graphs from G1 to Gn according to edges; acquiring the p according to the initial facility point set F and customer point set C of the undirected graph G; dynamically monitoring the p at any time according to updating of the facility point set F or customer point set C of the undirected graph G; wherein the minimized maximum distance location is shown as the following formula; the value of the n is set according to requirements of users. By the method and the system, the minimized maximum distance location can be searched quickly and dynamically.

Description

technical field [0001] The invention relates to a dynamic monitoring method and system for minimizing the maximum distance position. Background technique [0002] In the past few years, there has been a lot of work on a class of "facility placement problems" in the presence of sets of customer points (see reference 8: Farahani, R.Z., Hekmatfar, M.: Facility Location: Concepts, Models, Algorithms and Case Studies, 1st edn. Physica-Verlag HD (2009), Literature 15: Nickel, S., Puerto, J.: Location Theory: A Unified Approach, 1st edn. Springer (2005)). In the most general case, the problem consists of: (1) a set C of customer points and a set P of facility candidates, and (2) query the locations of k new facilities in P such that a pre-defined optimal condition. This kind of problem has a polynomial time algorithm when k is a constant, and it is an NP-hard problem when k is a general variable (see literature 8 and 15). The existing work mainly studies its approximate algorithm...

AI Technical Summary

Problems solved by technology

The techniques in these research works do not solve the optimal location query problem, because the closest point query problem is different from the optimal location query problem

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