Laws of large numbers for the annealing algorithm
type: Item
instance of: scholarly article
title: Laws of large numbers for the annealing algorithm
zbMATH Open document ID: 0715.60089
DOI: 10.1016/0304-4149(90)90009-H
author: Nina Gantert
published in: Stochastic Processes and their Applications
publication date: 1990-01-01T00:00:00Z
review text: A convergence of the algorithm of simulated annealing is considered. First, an error in the paper of \textit{B. Gidas} [J. Stat. Phys. 39, 73-131 (1985; Zbl 0642.60049)] is pointed out. Next, well-known laws of large numbers for time-inhomogeneous Markov chains are applied. Assumptions formulated in terms of Dobrushin contraction coefficients lead to appropriate cooling constant. Namely, in the cooling scheme \(\beta (n)=\gamma \log n\) weak LLN holds for \(\gamma <\gamma_ 0\) and strong LLN holds for \(\gamma <\gamma_ 0/2\) with some given \(\gamma_ 0\).
Mathematics Subject Classification ID: 60J20
Mathematics Subject Classification ID: 60F15
Mathematics Subject Classification ID: 60F05
Mathematics Subject Classification ID: 60J10
zbMATH DE Number: 4178284
zbMATH Keywords: simulated annealing
zbMATH Keywords: laws of large numbers for time-inhomogeneous Markov chains
Wikidata QID: Q115104697
reviewed by: T. Inglot
MaRDI profile type: Publication
cites work: Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
cites work: Nonstationary Markov chains and convergence of the annealing algorithm
cites work: Q5590550
cites work: Q4098444
cites work: Q3242474
description: scientific article; zbMATH DE number 4178284