Simulated annealing process in general state space

The stochastic process corresponding to the simulated annealing optimization algorithm is generalized to the case of an arbitrary state space. Conditions for the strong and weak convergence of the process are established. In addition the relation between the size of the generating distributions and...

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Veröffentlicht in:	Advances in applied probability 1991-12, Vol.23 (4), p.866-893
Hauptverfasser:	Haario, Heikki, Saksman, Eero
Format:	Artikel
Sprache:	eng
Schlagworte:	Absolute minimum Annealing Applied sciences Cooling Ergodic theory Exact sciences and technology Markov chains Markov processes Mathematical functions Mathematical minima Operational research and scientific management Operational research. Management science Optimization. Search problems Perceptron convergence procedure Simulated annealing
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Beschreibung
Zusammenfassung:	The stochastic process corresponding to the simulated annealing optimization algorithm is generalized to the case of an arbitrary state space. Conditions for the strong and weak convergence of the process are established. In addition the relation between the size of the generating distributions and the possible rate of cooling is studied.
ISSN:	0001-8678 1475-6064
DOI:	10.2307/1427681