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Convergence properties of simulated annealing for continuous global optimization

Part of: Combinatorial probability

Published online by Cambridge University Press:  14 July 2016

M. Locatelli
M. Locatelli*
Affiliation:
Universitá degli studi di Milano
*
∗Postal address: Dipartimento di Scienze dell'Informazione, Via Comelico, 39/41–20135 Milano, Italy.
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Abstract

In this paper conditions for the convergence of a class of simulated annealing algorithms for continuous global optimization are given. The previous literature about the subject gives results for the convergence of algorithms in which the next candidate point is generated according to a probability distribution whose support is the whole feasible set. A class of possible cooling schedules has been introduced in order to remove this restriction.

Keywords

SIMULATED ANNEALINGCONTINUOUS GLOBAL OPTIMIZATIONCOOLING SCHEDULE

MSC classification

Primary: 60C05: Combinatorial probability
Type
Research Papers
Information
Journal of Applied Probability , Volume 33 , Issue 4 , December 1996 , pp. 1127 - 1140
Copyright
Copyright © Applied Probability Trust 1996 

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