International Journal of Computational Geometry & Applications · 2011 · 18 citations · 6 references
ComputingComputer ScienceMathematicsAlgorithmsComputational GeometryOptimizationApproximation AlgorithmsCombinatorial OptimizationGeometric ApproximationGeometric OptimizationInteger ProgrammingConvex Hull AlgorithmsCovering ProblemsPolynomial Time ComplexityPolynomial-time AlgorithmsRange SensingSensingSet Cover Approximation
We consider a geometric optimization problem that arises in sensor network design. Given a polygon P (possibly with holes) with n vertices, a set Y of m points representing sensors, and an integer k, 1 ≤ k ≤ m. The goal is to assign a sensing range, r i , to each of the sensors y i ∈ Y, such that each point p ∈ P is covered by at least k sensors, and the cost, [Formula: see text], of the assignment is minimized, where α is a constant. In this paper, we assume that α = 2, that is, find a set of disks centered at points of Y, such that (i) each point in P is covered by at least k disks, and (ii) the sum of the areas of the disks is minimized. We present, for any constant k ≥ 1, a polynomial-time c 1 -approximation algorithm for this problem, where c 1 = c 1 (k) is a constant. The discrete version, where one has to cover a given set of n points, X, by disks centered at points of Y, arises as a subproblem. We present a polynomial-time c 2 -approximation algorithm for this problem, where c 2 = c 2 (k) is a constant.
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On the hardness of approximating minimization problems
Carsten Lund, Mihalis Yannakakis · Journal of the ACM · 1994 · 890 citations · Full text
Ray shooting in polygons using geodesic triangulations
Bernard Chazelle, Herbert Edelsbrunner, Michelangelo Grigni et al. · Algorithmica · 1994 · 173 citations