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A Randomized Approach to Volume Constrained Polyhedronization Problem

机译:体积约束多面体化问题的随机方法

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摘要

Given a finite set of points in R3, polyhedronization deals with constructing a simple polyhedron such that the vertices of the polyhedron are precisely the given points. In this paper, we present randomized approximation algorithms for minimal volume polyhedronization (MINVP) and maximal volume polyhedronization (MAXVP) of three dimensional point sets in general position. Both, MINVP and MAXVP, problems have been shown to be NP-hard and to the best of our knowledge, no practical algorithms exist to solve these problems. It has been shown that for any point set S in R3, there always exists a tetrahe-dralizable polyhedronization of S. We exploit this fact to develop a greedy heuristic for MINVP and MAXVP constructions. Further, we present an empirical analysis on the quality of the approximation results of some well defined point sets. The algorithms have been validated by comparing the results with the optimal results generated by an exhaustive searching (brute force) method for MINVP and MAXVP for some well chosen point sets of smaller sizes. Finally, potential applications of minimum and maximum volume polyhedra in 4D printing and surface lofting, respectively, have been discussed.
机译:给定R3中有限的点集,多面体化处理构造一个简单的多面体,以使多面体的顶点恰好是给定的点。在本文中,我们提出了在一般位置上三维点集的最小体积多面体化(MINVP)和最大体积多面体化(MAXVP)的随机近似算法。 MINVP和MAXVP问题均已证明是NP难题,据我们所知,尚无实际算法可解决这些问题。已经表明,对于R3中的任何点集S,总会存在S的四面体可多面体化。我们利用这一事实来开发MINVP和MAXVP构造的贪婪启发式方法。此外,我们对一些定义明确的点集的逼近结果的质量进行了实证分析。通过将结果与穷举搜索(强力)方法对一些较小尺寸的精选点集的MINVP和MAXVP生成的最佳结果进行比较,对算法进行了验证。最后,讨论了最小体积和最大体积多面体分别在4D打印和表面放样中的潜在应用。

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