General simulated annealing

Xin YAO, Guojie LI

Research output: Journal PublicationsJournal Article (refereed)peer-review

11 Citations (Scopus)


Simulated annealing is a new kind of random search methods developed in recent years. It can also be considered as an extension to the classical hill-climbing method in AI-probabilistic hill climbing. One of its most important features is its global convergence. The convergence of simulated annealing algorithm is determined by state generating probability, state accepting probability, and temperature decreasing rate. This paper gives a generalized simulated annealing algorithm with dynamic generating and accepting probabilities. The paper also shows that the generating and accepting probabilities can adopt many different kinds of distributions while the global convergence is guaranteed. © 1991 Science Press, Beijing China and Allerton Press Inc.
Original languageEnglish
Pages (from-to)329-338
Number of pages10
JournalJournal of Computer Science and Technology
Issue number4
Publication statusPublished - Oct 1991
Externally publishedYes


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