Convergence of simulated annealing-hastings

  • Authors:
  • Harold M. Hastings

  • Affiliations:
  • Department of Mathematics, Hofstra University, Hempstead, NY

  • Venue:
  • ACM SIGACT News
  • Year:
  • 1985

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Abstract

We develop worst-case and typical estimates for the rate of convergence of annealing algorithms. The worst-case estimates extend results of Geman and Geman (1983) for pattern recognition. However, as Geman and Geman observe, and empirical results imply, simulated annealing usually displays much faster convergence (and thus allows much faster cooling) than their worst-case results. Our typical case results help to explain this phenomenon.