Journal of Global Optimization

, Volume 8, Issue 1, pp 1–13

Simulated Annealing for noisy cost functions

Authors

  • Walter J. Gutjahr
    • Department of Statistics, OR and Computer ScienceUniversity of Vienna
  • Georg Ch. Pflug
    • Department of Statistics, OR and Computer ScienceUniversity of Vienna
Article

DOI: 10.1007/BF00229298

Cite this article as:
Gutjahr, W.J. & Pflug, G.C. J Glob Optim (1996) 8: 1. doi:10.1007/BF00229298

Abstract

We generalize a classical convergence result for the Simulated Annealing algorithm to a stochastic optimization context, i.e., to the case where cost function observations are disturbed by random noise. It is shown that for a certain class of noise distributions, the convergence assertion remains valid, provided that the standard deviation of the noise is reduced in the successive steps of cost function evaluation (e.g., by repeated observation) with a speed O(k), where γ is an arbitrary constant larger than one.

Key words

Simulated Annealingstochastic optimizationnoisy cost functions
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Copyright information

© Kluwer Academic Publishers 1996