Finding a Guard that Sees Most and a Shop that Sells Most
Discrete & Computational Geometry
On k-Nearest Neighbor Voronoi Diagrams in the Plane
IEEE Transactions on Computers
A Fast Similarity Join Algorithm Using Graphics Processing Units
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Solving the k-influence region problem with the GPU
Information Sciences: an International Journal
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In this paper we introduce an optimization problem, that arises in the competitive facility location area, which involves the maximization of the weighted area of the region where a new facility has influence. We consider a finite set of points S in a bounded polygonal region domain D subdivided into several non-negative weighted regions according to a weighted domain partition $\mathcal{P}$. For each point in S we define its k-nearest/farthest neighbor influence region as the region containing all the points of D having the considered point as one of their k-nearest/farthest neighbors in S. We want to find a new point s in D whose k-influence region is maximal in terms of weighted area according to the weighted partition $\mathcal{P}$. We present a GPU parallel approach, designed under CUDA architecture, for approximately solving the problem and we also provide experimental results showing the efficiency and scalability of the approach.