5 research outputs found

    New bounds on the average distance from the Fermat-Weber center of a planar convex body

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    The Fermat-Weber center of a planar body QQ is a point in the plane from which the average distance to the points in QQ is minimal. We first show that for any convex body QQ in the plane, the average distance from the Fermat-Weber center of QQ to the points of QQ is larger than 1/6Δ(Q){1/6} \cdot \Delta(Q), where Δ(Q)\Delta(Q) is the diameter of QQ. This proves a conjecture of Carmi, Har-Peled and Katz. From the other direction, we prove that the same average distance is at most 2(43)13Δ(Q)<0.3490Δ(Q)\frac{2(4-\sqrt3)}{13} \cdot \Delta(Q) < 0.3490 \cdot \Delta(Q). The new bound substantially improves the previous bound of 233Δ(Q)0.3849Δ(Q)\frac{2}{3 \sqrt3} \cdot \Delta(Q) \approx 0.3849 \cdot \Delta(Q) due to Abu-Affash and Katz, and brings us closer to the conjectured value of 1/3Δ(Q){1/3} \cdot \Delta(Q). We also confirm the upper bound conjecture for centrally symmetric planar convex bodies.Comment: 13 pages, 2 figures. An earlier version (now obsolete): A. Dumitrescu and Cs. D. T\'oth: New bounds on the average distance from the Fermat-Weber center of a planar convex body, in Proceedings of the 20th International Symposium on Algorithms and Computation (ISAAC 2009), 2009, LNCS 5878, Springer, pp. 132-14

    Approximating Median Points in a Convex Polygon

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    We develop two simple and efficient approximation algorithms for the continuous kk-medians problems, where we seek to find the optimal location of kk facilities among a continuum of client points in a convex polygon CC with nn vertices in a way that the total (average) Euclidean distance between clients and their nearest facility is minimized. Both algorithms run in O(n+k+klogn)\mathcal{O}(n + k + k \log n) time. Our algorithms produce solutions within a factor of 2.002 of optimality. In addition, our simulation results applied to the convex hulls of the State of Massachusetts and the Town of Brookline, MA show that our algorithms generally perform within a range of 5\% to 22\% of optimality in practice
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