Randomized Optimization: a Probabilistic AnalysisConference paper
Authors: Jean Cardinal 1; Stefan Langerman 1; Guy Louchard 1
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Jean Cardinal;Stefan Langerman;Guy Louchard
- 1 Département d'Informatique [Bruxelles]
In 1999, Chan proposed an algorithm to solve a given optimization problem: express the solution as the minimum of the solutions of several subproblems and apply the classical randomized algorithm for finding the minimum of $r$ numbers. If the decision versions of the subproblems are easier to solve than the subproblems themselves, then a faster algorithm for the optimization problem may be obtained with randomization. In this paper we present a precise probabilistic analysis of Chan's technique.
Volume: DMTCS Proceedings vol. AH, 2007 Conference on Analysis of Algorithms (AofA 07)
Section: Proceedings
Published on: January 1, 2007
Imported on: May 10, 2017
Keywords: [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], [MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO], [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], [en] optimization, randomization