Markov chains and optimality of the Hamiltonian cycle

Nelli Litvak, Vladimir Ejov

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Abstract

We consider the Hamiltonian cycle problem (HCP) embedded in a controlled Markov decision process. In this setting, HCP reduces to an optimization problem on a set of Markov chains corresponding to a given graph. We prove that Hamiltonian cycles are minimizers for the trace of the fundamental matrix on a set of all stochastic transition matrices. In case of doubly stochastic matrices with symmetric linear perturbation, we show that Hamiltonian cycles minimize a diagonal element of a fundamental matrix for all admissible values of the perturbation parameter. In contrast to the previous work on this topic, our arguments are primarily based on probabilistic rather than algebraic methods.
Original languageEnglish
Place of PublicationEnschede
PublisherUniversity of Twente, Department of Applied Mathematics
Number of pages12
Publication statusPublished - Jun 2007

Publication series

NameMemorandum
PublisherUniversity of Twente, Department of Applied Mathematics
No.1841
ISSN (Print)1874-4850

Keywords

  • MSC-05C45
  • Singular perturbation
  • Hamiltonian cycle
  • Fundamental matrix
  • MSC-60J10
  • Markov chains
  • MSC-15A51

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