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International Conference on Parallel Problem Solving from Nature

PPSN 2010: Parallel Problem Solving from Nature, PPSN XI pp 32–41Cite as

Adaptive Drift Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6238))

Abstract

We show that the (1+1) evolutionary algorithm using an arbitrary mutation rate p = c/n, c a constant, finds the optimum of any n-bit pseudo-Boolean linear function f in expected time Θ(n logn).

Since previous work shows that universal drift functions cannot exist for c larger than a certain constant, we define drift functions depending on p and f. This seems to be the first time in the theory of evolutionary algorithms that drift functions are used that take into account the particular problem instance.

This work was begun while both authors were visiting the “Centre de Recerca Matemática de Catalunya”. It profited greatly from this ideal environment for collaboration.

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Author information

Authors and Affiliations

  1. Max-Planck-Institut für Informatik, 66123, Saarbrücken, Germany

    Benjamin Doerr

  2. Department of Computer Science, University of Liverpool, Ashton Bldg, Liverpool, L69 3BX, UK

    Leslie Ann Goldberg

Authors
  1. Benjamin Doerr
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  2. Leslie Ann Goldberg
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Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of ComputerScience, AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Robert Schaefer

  2. Departamento de Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  3. Department of Mathematics and Computer Science, University of Bielsko-Biala, Willowa 2, 43-309, Bielsko-Biala, Poland

    Joanna Kołodziej

  4. Fakultät für Informatik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Günter Rudolph

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Doerr, B., Goldberg, L.A. (2010). Adaptive Drift Analysis. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds) Parallel Problem Solving from Nature, PPSN XI. PPSN 2010. Lecture Notes in Computer Science, vol 6238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15844-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-15844-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15843-8

  • Online ISBN: 978-3-642-15844-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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