Note on the convergence of simulated annealing algorithms

U. Faigle; W. Kern

doi:10.1137/0329008

Note on the convergence of simulated annealing algorithms

U. Faigle
, W. Kern

Discrete Mathematics and Mathematical Programming

Research output: Contribution to journal › Article › Academic › peer-review

21 Citations (Scopus)

Abstract

Generalizing the results of Faigle and Schrader [Inform. Process. Lett., 27 (1988), pp. 189–194] a short inductive proof is given that shows that the stationary distributions of a simulated annealing algorithm converge to a distribution, where nonoptimal elements are generated with probability zero, provided that the “weak reversibility condition” of Hajek [Math. Oper. Res., 13 (1988), pp. 311–329] holds.

Original language	English
Pages (from-to)	153-159
Number of pages	7
Journal	SIAM journal on control and optimization
Volume	29
Issue number	1
DOIs	https://doi.org/10.1137/0329008
Publication status	Published - 1991

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title = "Note on the convergence of simulated annealing algorithms",

abstract = "Generalizing the results of Faigle and Schrader [Inform. Process. Lett., 27 (1988), pp. 189–194] a short inductive proof is given that shows that the stationary distributions of a simulated annealing algorithm converge to a distribution, where nonoptimal elements are generated with probability zero, provided that the “weak reversibility condition” of Hajek [Math. Oper. Res., 13 (1988), pp. 311–329] holds.",

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AU - Kern, W.

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AB - Generalizing the results of Faigle and Schrader [Inform. Process. Lett., 27 (1988), pp. 189–194] a short inductive proof is given that shows that the stationary distributions of a simulated annealing algorithm converge to a distribution, where nonoptimal elements are generated with probability zero, provided that the “weak reversibility condition” of Hajek [Math. Oper. Res., 13 (1988), pp. 311–329] holds.

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DO - 10.1137/0329008

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EP - 159

JO - SIAM journal on control and optimization

JF - SIAM journal on control and optimization

IS - 1

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Note on the convergence of simulated annealing algorithms

Abstract

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