Jean Cardinal ; Stefan Langerman ; Guy Louchard
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Randomized Optimization: a Probabilistic Analysis
dmtcs:3540 -
Discrete Mathematics & Theoretical Computer Science,
January 1, 2007,
DMTCS Proceedings vol. AH, 2007 Conference on Analysis of Algorithms (AofA 07)
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https://doi.org/10.46298/dmtcs.3540
Randomized Optimization: a Probabilistic AnalysisArticle
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.