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- W2148693377 abstract "This paper proposes a new method for probabilistic analysis of online algorithms. It is based on the notion of stochastic dominance. We develop the method for the online bin coloring problem introduced in [15]. Using methods for the stochastic comparison of Markov chains we establish the result that the performance of the online algorithm $textsc{GreedyFit}$ is stochastically better than the performance of the algorithm $textsc{OneBin}$ for any number of items processed. This result gives a more realistic picture than competitive analysis and explains the behavior observed in simulations." @default.
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- W2148693377 date "2008-08-30" @default.
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- W2148693377 title "Probabilistic Analysis of Online Bin Coloring Algorithms Via Stochastic Comparison" @default.
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- W2148693377 doi "https://doi.org/10.1007/978-3-540-87744-8_44" @default.
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