Monte Carlo pp 335-491 | Cite as

Random Tours

  • George S. Fishman
Part of the Springer Series in Operations Research book series (ORFE)


This chapter considerably broadens the range of application of the Monte Carlo method by introducing the concept of a random tour on discrete, continuous, and general state spaces. This development serves several purposes, of which the ability to sample from a multivariable distribution remains preeminent. Let {F(x), x ∈ ℋ} denote an m-dimensional d.f. defined on a region ℋ ⊆ ℝ m , and let {g(x), x ∈ ℋ} denote a known function satisfying ∫ g 2(x)dF(x) < ∞. Suppose that the objective is to evaluate
$$\mu \left( g \right) = \int {_x} g\left( x \right)dF\left( x \right).$$


Markov Chain Random Walk Span Tree Transition Matrix Convex Body 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • George S. Fishman
    • 1
  1. 1.Department of Operations ResearchUniversity of North CarolinaChapel HillUSA

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