Convergence of simulated annealing using Foster-Lyapunov criteria
Christophe Andrieu, Laird A. Breyer, and Arnaud Doucet
Source: J. Appl. Probab. Volume 38, Number 4
(2001), 975-994.
Abstract
Simulated annealing is a popular and much studied method for maximizing functions on finite or compact spaces. For noncompact state spaces, the method is still sound, but convergence results are scarce. We show here how to prove convergence in such cases, for Markov chains satisfying suitable drift and minorization conditions.
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Keywords: Simulated annealing; Markov chain Monte Carlo; optimization; Foster-Lyapunov; nonhomogeneous Markov chain
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Links and Identifiers
Permanent link to this document: http://projecteuclid.org/euclid.jap/1011994186
Digital Object Identifier: doi:10.1239/jap/1011994186
Mathematical Reviews number (MathSciNet): MR1876553
Zentralblatt MATH identifier: 0999.60066
Journal of Applied Probability
