Linear programming and convex hulls made easy

SCG '90 Pub Date : 1990-05-01 DOI:10.1145/98524.98570
R. Seidel
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引用次数: 206

Abstract

We present two randomized algorithms. One solves linear programs involving m constraints in d variables in expected time &Ogr;(m). The other constructs convex hulls of n points in Rd, d > 3, in expected time &Ogr;(nd/2⌉). In both bounds d is considered to be a constant. In the linear programming algorithm the dependence of the time bound on d is of the form d!. The main virtue of our results lies in the utter simplicity of the algorithms as well as their analyses.
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线性规划和凸包变得很容易
我们提出了两种随机算法。一种是在期望时间(m)内解决涉及d个变量的m个约束的线性规划。另一种是在期望时间&Ogr;(n≤d/2)内构造Rd中n个点的凸包,d > 3。在两个界内,d都被认为是常数。在线性规划算法中,时间边界对d的依赖形式为d!我们的结果的主要优点在于算法及其分析的绝对简单。
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Linear programming and convex hulls made easy Computing the minimum Hausdorff distance for point sets under translation On solving geometric optimization problems using shortest paths Maximin location of convex objects in a polygon and related dynamic Voronoi diagrams An O(n2log n) time algorithm for the MinMax angle triangulation
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