Soft Computing

, Volume 21, Issue 5, pp 1253–1270 | Cite as

Noisy extremal optimization

Methodologies and Application

Abstract

Noisy extremal optimization is a new optimization-based heuristic designed to identify the community structure of complex networks by maximizing the modularity function. The extremal optimization algorithm evolves configurations that represent network covers, composed of nodes evaluated separately. Each iteration, a number of nodes having the worst fitness values are randomly assigned different communities. A network shifting procedure is used to induce a noise in the population as a diversity preserving mechanism. Numerical experiments, performed on synthetic and real-world networks, illustrate the potential of this approach.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Rodica Ioana Lung
    • 1
  • Mihai Suciu
    • 1
  • Noémi Gaskó
    • 1
  1. 1.Babes-Bolyai UniversityCluj-NapocaRomania

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