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February, 1993 Simulated Annealing
Dimitris Bertsimas, John Tsitsiklis
Statist. Sci. 8(1): 10-15 (February, 1993). DOI: 10.1214/ss/1177011077


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.


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Dimitris Bertsimas. John Tsitsiklis. "Simulated Annealing." Statist. Sci. 8 (1) 10 - 15, February, 1993.


Published: February, 1993
First available in Project Euclid: 19 April 2007

zbMATH: 0764.60073
MathSciNet: MR1194437
Digital Object Identifier: 10.1214/ss/1177011077

Rights: Copyright © 1993 Institute of Mathematical Statistics


Vol.8 • No. 1 • February, 1993
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