A nearest neighbor sweep circle algorithm for computing discrete Voronoi tessellations

Abstract

An algorithm for computing discrete, 2-dimensional, Euclidean Voronoi tessellations is presented. The algorithm combines a limiting sweep circle approach with a nearest neighbor cellular approach. It reduces the computational cost of the naïve approach while at the same time giving the Euclidean Voronoi tessellations that simple nearest neighbor algorithms are unable to produce. The algorithm is shown, through analytical methods, to produce good approximations to corresponding continuous Voronoi tessellations depending on the definition of neighbor used in the nearest neighbor step and the mesh size. The quality of different types of neighbor definitions are discussed as well as the computational cost. The algorithm is general enough to be easily extended to higher dimensions and nonuniform meshes. The analysis lays the groundwork for the computation of discrete centroidal Voronoi tessellations where some kind of numerical integration is required.

Generating 2D Non-Equiaxed Initial Microstructure for Monte Carlo Simulation Using Modified Voronoi Model

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A parallel algorithm for constructing Voronoi diagrams based on point‐set adaptive grouping

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