Thuật toán tăng trưởng ngẫu nhiên cho bài toán lấy mẫu ngẫu nhiên trong hình học tính toán

Abstract

Computational geometry often suffers from problems of complexity and computing efficiency, particularly in multidimensional space. Situated in a geometric context, the paper focuses on random sampling algorithms for geometric optimization, including convex hulls, Delaunay triangles, and Voronoi diagrams. Using a random sample incremental technique, the author optimize the partition of space to represent a set of points in two- and three-dimensional space.