Data in Brief (Aug 2020)

A comprehensive database of Nature-Inspired Algorithms

  • Alexandros Tzanetos,
  • Iztok Fister, Jr.,
  • Georgios Dounias

Journal volume & issue
Vol. 31
p. 105792

Abstract

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These data contain a comprehensive collection of all Nature-Inspired Algorithms. This collection is a result of two corresponding surveys, where all Nature-Inspired Algorithms that have been published to-date were gathered and preliminary data acquired. The rapidly increasing number of nature-inspired approaches makes it hard for interested researchers to keep up. Moreover, a proper taxonomy is necessary, based on specific features of the algorithms. Different taxonomies and useful insight into the application areas that the algorithms have coped with is given through these data. This article provides a detailed description of the above mentioned collection.

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