Statistical Science

Simulated Annealing

Dimitris Bertsimas and John Tsitsiklis

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Abstract

Simulated annealing is a probabilistic method proposed in Kirkpatrick, Gelett and Vecchi (1983) and Cerny (1985) for finding the global minimum of a cost function that may possess several local minima. It works by emulating the physical process whereby a solid is slowly cooled so that when eventually its structure is "frozen," this happens at a minimum energy configuration. We restrict ourselves to the case of a cost function defined on a finite set. Extensions of simulated annealing to the case of functions defined on continuous sets have also been introduced in the literature (e.g., Geman and Hwang, 1986; Gidas, 1985a; Holley, Kusuoka and Stroock, 1989; Jeng and Woods, 1990; Kushner, 1985). Our goal in this review is to describe the method, its convergence and its behavior in applications.

Article information

Source
Statist. Sci. Volume 8, Number 1 (1993), 10-15.

Dates
First available: 19 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.ss/1177011077

JSTOR
links.jstor.org

Digital Object Identifier
doi:10.1214/ss/1177011077

Mathematical Reviews number (MathSciNet)
MR1194437

Zentralblatt MATH identifier
0764.60073

Citation

Bertsimas, Dimitris; Tsitsiklis, John. Simulated Annealing. Statistical Science 8 (1993), no. 1, 10--15. doi:10.1214/ss/1177011077. http://projecteuclid.org/euclid.ss/1177011077.


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