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Randomized algorithms for the separation of point sets and for solving quadratic programs

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Abstract

A randomized algorithm for finding a hyperplane separating two finite point sets in the Euclidean space ℝd and a randomized algorithm for solving linearly constrained general convex quadratic problems are proposed. The expected running time of the separating algorithm isO(dd! (m + n)), wherem andn are cardinalities of sets to be separated. The expected running time of the algorithm for solving quadratic problems isO(dd! s) wheres is the number of inequality constraints. These algorithms are based on the ideas of Seidel's linear programming algorithm [6]. They are closely related to algorithms of [8], [2], and [9] and belong to an abstract class of algorithms investigated in [1]. The algorithm for solving quadratic problems has some features of the one proposed in [7].

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Authors and Affiliations

  1. Institut für Angewandte Mathematik und Statistik, Universität Würzburg, Am Hubland, D-8700, Würzburg, Germany

    N. D. Botkin

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  1. N. D. Botkin
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Communicated by J. Stoer

This research was done when the author was supported by the Alexander von Humboldt Foundation, Germany.

On leave from the Institute of Mathematics and Mechanics, Ural Department of the Russian Academy of Sciences, 620219 Ekaterinburg, S. Kovalevskaya str. 16, Russia.

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Botkin, N.D. Randomized algorithms for the separation of point sets and for solving quadratic programs. Appl Math Optim 32, 195–210 (1995). https://doi.org/10.1007/BF01185230

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