An iterative algorithm for finding a nearest pair of points in two convex subsets of \(\mathbb{R}^n\)

DOI10.1016/S0898-1221(00)85008-7zbMath1016.90032WikidataQ59313208 ScholiaQ59313208MaRDI QIDQ1591950

R. Smith

Publication date: 14 January 2001

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

zbMATH Keywords

polyhedralocal searchnonexpansive operatorsconvex polyhedraEuclidean distanceprojection algorithms

Mathematics Subject Classification ID

Convex programming (90C25) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18)

Related Items (7)

Uniform tree approximation by global optimization techniques ⋮ Representation complexity of adaptive 3D distance fields ⋮ A local search algorithm for ray-convex polyhedron intersection ⋮ Hausdorff matching and Lipschitz optimization ⋮ A general soft method for learning SVM classifiers with \(L_{1}\)-norm penalty ⋮ Efficient computation of the Hausdorff distance between polytopes by exterior random covering ⋮ Kernel projection algorithm for large-scale SVM problems.

Cites Work

• Solution of projection problems over polytopes
• A recursive algorithm for finding the minimum norm point in a polytope and a pair of closest points in two polytopes
• Finding the projection on a polytope: An iterative method
• Optimal Algorithms for the Intersection and the Minimum Distance Problems Between Planar Polygons
• Finding the nearest point in A polytope
• On Projection Algorithms for Solving Convex Feasibility Problems
• A DUAL ALGORITHM FOR FINDING A NEAREST PAIR OF POINTS IN TWO POLYTOPES
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