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On the optimization of unimodal functions with the (1+1) evolutionary algorithm

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Parallel Problem Solving from Nature — PPSN V (PPSN 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1498))

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Abstract

We investigate the expected running time of the (1+1) EA, a very simple Evolutionary Algorithm, on the class of unimodal fitness functions with Boolean inputs. We analyze the behavior on a generalized version of long paths [6, 10] and prove an exponential lower bound on the expected running time. Thereby we show that unimodal functions can be very difficult to be optimized for the (1+1) EA. Furthermore, we prove that a little modification in the selection method can lead to huge changes in the expected running time.

This work was supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the Collaborative Research Center “Computational Intelligence” (531).

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References

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Agoston E. Eiben Thomas Bäck Marc Schoenauer Hans-Paul Schwefel

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© 1998 Springer-Verlag Berlin Heidelberg

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Droste, S., Jansen, T., Wegener, I. (1998). On the optimization of unimodal functions with the (1+1) evolutionary algorithm. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN V. PPSN 1998. Lecture Notes in Computer Science, vol 1498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056845

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  • DOI: https://doi.org/10.1007/BFb0056845

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65078-2

  • Online ISBN: 978-3-540-49672-4

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