Simulated annealing

E.H.L. Aarts, P. Horn van der, J.H.M. Korst, W.P.A.J. Michiels, H. Sontrop

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Abstract

Simulated Annealing is a meta-heuristic that performs a randomized local search to reach near-optimal solutions of combinatorial as well as continuous optimization problems, In this chapter we show how it can be used to train artificial neural networks by examples. Experimental results indicate that good results can be obtained with little or no tuning.
Original languageEnglish
Title of host publicationMetaheuristic procedures for training neural networks
Place of PublicationBoston, USA
PublisherSpringer
Pages37-52
Number of pages16
ISBN (Print)978-0-387-33415-8
DOIs
Publication statusPublished - 2007
Externally publishedYes

Publication series

NameOperations Research/Computer Science Interfaces Series

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Aarts, E. H. L., Horn van der, P., Korst, J. H. M., Michiels, W. P. A. J., & Sontrop, H. (2007). Simulated annealing. In Metaheuristic procedures for training neural networks (pp. 37-52). (Operations Research/Computer Science Interfaces Series). Springer. https://doi.org/10.1007/0-387-33416-5_2