Skip to main content

Black-Box Complexity: Breaking the O(n logn) Barrier of LeadingOnes

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7401))

Abstract

We show that the unrestricted black-box complexity of the n-dimensional XOR- and permutation-invariant LeadingOnes function class is O(n log(n) / loglogn). This shows that the recent natural looking O(nlogn) bound is not tight.

The black-box optimization algorithm leading to this bound can be implemented in a way that only 3-ary unbiased variation operators are used. Hence our bound is also valid for the unbiased black-box complexity recently introduced by Lehre and Witt. The bound also remains valid if we impose the additional restriction that the black-box algorithm does not have access to the objective values but only to their relative order (ranking-based black-box complexity).

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   72.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Droste, S., Jansen, T., Wegener, I.: Upper and lower bounds for randomized search heuristics in black-box optimization. Theory of Computing Systems 39, 525–544 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  2. Lehre, P.K., Witt, C.: Black-box search by unbiased variation. In: Proc. of Genetic and Evolutionary Computation Conference (GECCO 2010), pp. 1441–1448. ACM (2010)

    Google Scholar 

  3. Doerr, B., Winzen, C.: Towards a Complexity Theory of Randomized Search Heuristics: Ranking-Based Black-Box Complexity. In: Kulikov, A., Vereshchagin, N. (eds.) CSR 2011. LNCS, vol. 6651, pp. 15–28. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  4. Doerr, B., Winzen, C.: Playing Mastermind with constant-size memory. In: Proc. of 29th International Symposium on Theoretical Aspects of Computer Science (STACS 2012), pp. 441–452. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik (2012)

    Google Scholar 

  5. Rudolph, G.: Convergence Properties of Evolutionary Algorithms. Kovac (1997)

    Google Scholar 

  6. Mühlenbein, H.: How genetic algorithms really work: Mutation and hillclimbing. In: Proc. of Parallel Problem Solving from Nature (PPSN II), pp. 15–26. Elsevier (1992)

    Google Scholar 

  7. Droste, S., Jansen, T., Wegener, I.: On the analysis of the (1+1) evolutionary algorithm. Theoretical Computer Science 276, 51–81 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  8. Doerr, B., Johannsen, D., Kötzing, T., Lehre, P.K., Wagner, M., Winzen, C.: Faster black-box algorithms through higher arity operators. In: Proc. of Foundations of Genetic Algorithms (FOGA 2011), pp. 163–172. ACM (2011)

    Google Scholar 

  9. Auger, A., Doerr, B.: Theory of Randomized Search Heuristics. World Scientific (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Doerr, B., Winzen, C. (2012). Black-Box Complexity: Breaking the O(n logn) Barrier of LeadingOnes. In: Hao, JK., Legrand, P., Collet, P., Monmarché, N., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2011. Lecture Notes in Computer Science, vol 7401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35533-2_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35533-2_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35532-5

  • Online ISBN: 978-3-642-35533-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics