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On Non-elitist Evolutionary Algorithms Optimizing Fitness Functions with a Plateau

  • Anton V. EremeevEmail author
Conference paper
  • 199 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12095)

Abstract

We consider the expected runtime of non-elitist evolutionary algorithms (EAs), when they are applied to a family of fitness functions \(\text {Plateau} _r\) with a plateau of second-best fitness in a Hamming ball of radius r around a unique global optimum. On one hand, using the level-based theorems, we obtain polynomial upper bounds on the expected runtime for some modes of non-elitist EA based on unbiased mutation and the bitwise mutation in particular. On the other hand, we show that the EA with fitness proportionate selection is inefficient if the bitwise mutation is used with the standard settings of mutation probability.

Keywords

Evolutionary algorithm Selection Runtime Plateau Unbiased mutation 

Notes

Acknowledgment

The work was funded by program of fundamental scientific research of the Russian Academy of Sciences, I.5.1., project 0314-2019-0019. The author is grateful to Duc-Cuong Dang for helpful comments on preliminary version of the paper.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Sobolev Institute of MathematicsOmskRussia

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