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Two-Dimensional Maximum p-Coverage Problem with Partial Coverage

Manish Bansal(bansal***at***vt.edu)

Abstract: In this paper, we introduce a new generalization of the classical maximum p-coverage problem (MCP) in which p geometric objects of known dimensions are to be located such that their union covers maximum weight distributed on a two-dimensional plane using another set of geometric objects such as circles, rectangles, polygons, etc. We allow partial coverage in the foregoing generalization and denote this problem by MCP-PC. Using greedy approach, we develop an approximation algorithm to solve the MCP-PC and showcase that this algorithm has approximation ratio of 1- 1/e where e is the base of natural logarithm. We also discuss about the classes of applied problems which can be formulated as the MCP-PC.

Keywords: maximum p-coverage problem; greedy-based approximation algorithm; partial coverage; facility location; geographical informative systems; telerobotics

Category 1: Combinatorial Optimization (Approximation Algorithms )

Category 2: Applications -- OR and Management Sciences (Production and Logistics )

Category 3: Nonlinear Optimization (Other )

Citation: B12, ISE, Virginia Tech, Sept 2017

Download: [PDF]

Entry Submitted: 09/04/2017
Entry Accepted: 09/04/2017
Entry Last Modified: 09/04/2017

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