Skip to main content
Log in

A Stopping Criterion for Logarithmic Simulated Annealing

  • Published:
Computing Aims and scope Submit manuscript

Abstract

We perform a convergence analysis of simulated annealing-based search for the special case of logarithmic cooling schedules. Emphasis is put on the impact of structural parameters of the underlying configuration space on the number of transitions kL that is sufficient to achieve a certain probability (confidence 1−δ) of being in an optimum configuration. Since such a lower bound L of the transition number depends on some constants that are difficult to calculate, we evaluate a much simplified version L'L of the lower bound for the problem of finding short conjunctions representing a ``positive'' Boolean vector and rejecting a set of ``negative'' Boolean vectors. The evaluation is based on computational experiments where the frequency of occurrences of configurations is calculated for simulated annealing-based search that terminates after L' transitions. The experiments produce a good correspondence between frequencies of minimum configurations and the required confidence 1−δ, i.e., our study provides empirical evidence that the relation of basic parameters in the lower bound L, if calculated for small constants assigned to the parameters and thus resulting in L', can be used as a termination criterion in simulated annealing-based search.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • E. H. L. Aarts (1998) Local search in combinatorial optimization Wiley New York Occurrence Handle01973378

    MATH  Google Scholar 

  • Albrecht, A.: On the complexity to approach optimum solutions by inhomogeneous Markov chains. In: Proc. Genetic and Evolutionary Computation Conference (GECCO'04), LNCS vol. 3102. Berlin: Springer 2004, pp. 642–653.

  • A. Albrecht M. J. Loomes K. Steinhöfel M. Taupitz (2002) ArticleTitleAdaptive simulated annealing for CT image classification Int. J. Pattern. Recogn. Artif. Intell. 16 573–588 Occurrence Handle10.1142/S0218001402001848

    Article  Google Scholar 

  • A. Albrecht St. A. Vinterbo L. Ohno-Machado (2003) ArticleTitleAn Epicurean learning approach to gene-expression data classification Artif. Intell. Med. 28 75–87 Occurrence Handle10.1016/S0933-3657(03)00036-8

    Article  Google Scholar 

  • O. Catoni (1992) ArticleTitleRough large deviation estimates for simulated annealing: applications to exponential schedules Ann. Probability 20 1109–1146 Occurrence Handle0755.60021 Occurrence Handle1175253

    MATH  MathSciNet  Google Scholar 

  • V. Černy (1985) ArticleTitleA thermodynamical approach to the travelling salesman problem J. Optim. Theor. Appl. 45 41–51 Occurrence Handle10.1007/BF00940812 Occurrence Handle0534.90091

    Article  MATH  Google Scholar 

  • I. Guyon J. Weston St. Barnhill V. Vapnik (2002) ArticleTitleGene selection for cancer classification using support vector machines Machine Learning 46 389–422 Occurrence Handle0998.68111 Occurrence Handle10.1023/A:1012487302797

    Article  MATH  Google Scholar 

  • B. Hajek (1988) ArticleTitleCooling schedules for optimal annealing Math. Oper. Res. 13 311–329 Occurrence Handle0652.65050 Occurrence Handle942621 Occurrence Handle10.1287/moor.13.2.311

    Article  MATH  MathSciNet  Google Scholar 

  • Hart, W. E.: A theoretical comparison of evolutionary algorithms and simulated annealing. In: Proc. 5th Annual Conf. on Evolutionary Programming. Cambridge, MA: MIT Press 1996, pp. 147–154.

  • S. Kirkpatrick C.-D. Gelatt SuffixJr. M. P. Vecchi (1983) ArticleTitleOptimization by simulated annealing Science 220 671–680 Occurrence Handle702485

    MathSciNet  Google Scholar 

  • G. Lappas R. J. Frank A. A. Albrecht (2006) ArticleTitleA computational study on circuit size vs. circuit depth Int. J. Artif. Intell. Tools 15 143–162 Occurrence Handle10.1142/S0218213006002606

    Article  Google Scholar 

  • P. Merz B. Freisleben (2000) ArticleTitleFitness landscapes, memetic algorithms, and greedy operators for graph bipartitioning Evol. Comput. 8 61–91 Occurrence Handle10.1162/106365600568103

    Article  Google Scholar 

  • Merz, P.: An iterated local search approach for minimum sum-of-squares clustering. In: Proc. Adv. Intelligent Data Analysis V, LNCS vol. 2810. Berlin: Springer 2003, pp. 286–296.

  • N. Metropolis A. W. Rosenbluth M. N. Rosenbluth A. H. Teller E. Teller (1953) ArticleTitleEquation of state calculations by fast computing machines J. Chem. Phys. 21 1087–1092 Occurrence Handle10.1063/1.1699114

    Article  Google Scholar 

  • P. Salomon P. Sibani R. Frost (2002) Facts, conjectures, and improvements for simulated annealing SIAM Publishers Philadelphia

    Google Scholar 

  • L. M. Schmitt (2001) ArticleTitleTheory of genetic algorithms Theor. Comput. Sci. 259 1–61 Occurrence Handle0972.68133 Occurrence Handle10.1016/S0304-3975(00)00406-0

    Article  MATH  Google Scholar 

  • P.-M.-B. Vitanyi (2000) ArticleTitleA discipline of evolutionary programming Theor. Comput. Sci. 241 3–23 Occurrence Handle0944.68009 Occurrence Handle1778921 Occurrence Handle10.1016/S0304-3975(99)00263-7

    Article  MATH  MathSciNet  Google Scholar 

  • M. T. Wolfinger Svrcek-Seiler Ch. Flamm I.-L. Hofacker P.-F. Stadler (2004) ArticleTitleExact folding dynamics of RNA secondary structures J. Phys. A – Mathematical General 37 4731–4741 Occurrence Handle1050.81729 Occurrence Handle2066326 Occurrence Handle10.1088/0305-4470/37/17/005

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andreas A. Albrecht.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Albrecht, A.A. A Stopping Criterion for Logarithmic Simulated Annealing. Computing 78, 55–79 (2006). https://doi.org/10.1007/s00607-006-0167-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00607-006-0167-1

AMS Subject Classifications

Keywords

Navigation