General Lower Bounds for the Running Time of Evolutionary Algorithms

  • Dirk Sudholt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6238)

Abstract

We present a new method for proving lower bounds in evolutionary computation based on fitness-level arguments and an additional condition on transition probabilities between fitness levels. The method yields exact or near-exact lower bounds for LO, OneMax, and all functions with a unique optimum. All lower bounds hold for every evolutionary algorithm that only uses standard mutation as variation operator.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Dirk Sudholt
    • 1
  1. 1.International Computer Science InstituteBerkeleyUSA

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