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Algorithmica

, Volume 81, Issue 2, pp 886–915 | Cite as

Island Models Meet Rumor Spreading

  • Benjamin Doerr
  • Philipp FischbeckEmail author
  • Clemens Frahnow
  • Tobias Friedrich
  • Timo Kötzing
  • Martin Schirneck
Article
  • 62 Downloads
Part of the following topical collections:
  1. Special Issue on Theory of Genetic and Evolutionary Computation

Abstract

Island models in evolutionary computation solve problems by a careful interplay of independently running evolutionary algorithms on the island and an exchange of good solutions between the islands. In this work, we conduct rigorous run time analyses for such island models trying to simultaneously obtain good run times and low communication effort. We improve the existing upper bounds for both measures (i) by improving the run time bounds via a careful analysis, (ii) by balancing individual computation and communication in a more appropriate manner, and (iii) by replacing the usual communicate-with-all approach with randomized rumor spreading. In the latter, each island contacts a randomly chosen neighbor. This epidemic communication paradigm is known to lead to very fast and robust information dissemination in many applications. Our results concern island models running simple \((1+1)\) evolutionary algorithms to optimize the classic test functions OneMax and LeadingOnes. We investigate binary trees, d-dimensional tori, and complete graphs as communication topologies.

Keywords

Evolutionary algorithm Run time analysis Communication costs Island model Rumor spreading 

Notes

Acknowledgements

This work has been partially supported by the Direction générale l’armement of the French Ministry of Defense under the X-DGA Contract and by the German Research Foundation under Grant Agreement FR2988 (TOSU). We would like to thank the anonymous reviewers as well as the guest editors, Carola Doerr and Dirk Sudholt, for their constructive feedback, which significantly improved the quality of the paper.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Laboratoire d’Informatique (LIX)École PolytechniquePalaiseauFrance
  2. 2.Hasso Plattner InstitutePotsdamGermany

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