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Simulated annealing methods with general acceptance probabilities

Published online by Cambridge University Press:  14 July 2016

S. Anily and
A. Federgruen
S. Anily*
Affiliation:
The University of British Columbia
A. Federgruen*
Affiliation:
Columbia University
*
∗ Postal address: Faculty of Commerce and Business Administration, The University of British Columbia, Vancouver, B.C., Canada V6T 1Y8.
∗∗ Postal address: Graduate School of Business, Uris Hall, Columbia University, New York, NY 10027, USA.
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Abstract

Heuristic solution methods for combinatorial optimization problems are often based on local neighborhood searches. These tend to get trapped in a local optimum and the final result is often heavily dependent on the starting solution. Simulated annealing methods attempt to avoid these problems by randomizing the procedure so as to allow for occasional changes that worsen the solution. In this paper we provide probabilistic analyses of different designs of these methods.

Keywords

PROBABILISTIC PERFORMANCE ANALYSISCONVERGENCE CONDITIONSGENERAL ACCEPTANCE PROBABILITIES

Information

Type
Research Papers
Information
Journal of Applied Probability , Volume 24 , Issue 3 , September 1987, pp. 657 - 667
Copyright
Copyright © Applied Probability Trust 1987 

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