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.

Authors
Shoshana Anily and Awi Federgruen
Format
Journal Article
Publication Date
Journal
Journal of Applied Probability

Full Citation

Anily, Shoshana and Awi Federgruen
. “Simulated annealing methods with general acceptance probabilities.”
Journal of Applied Probability
vol.
24
, (September 01, 1987):
657
-
667
.