Abstract
Probabilistic methods have long been applied to solve discrete mathematics problems (see, for example, Erdős [38]–[39], and Alon and Spencer [3] for a recent and comprehensive treatment on probabilistic methods). Similarly, connections between Markov chains and graph theory have long been made (see Harary [57]). Our contribution here is to apply properties of Markov chains to the Hamiltonian cycle problem and to take advantage of the still emerging theory of perturbed Markov chains in this context.
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© 2012 Springer Science+Business Media, LLC
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Borkar, V.S., Ejov, V., Filar, J.A., Nguyen, G.T. (2012). Markov Chains. In: Hamiltonian Cycle Problem and Markov Chains. International Series in Operations Research & Management Science, vol 171. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3232-6_3
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DOI: https://doi.org/10.1007/978-1-4614-3232-6_3
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Print ISBN: 978-1-4614-3231-9
Online ISBN: 978-1-4614-3232-6
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