Similarity in metaheuristics: a gentle step towards a comparison methodology

Jesica de Armas, Eduardo Lalla-Ruiz*, Surafel Luleseged Tilahun, Stefan Voß

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Scopus)
101 Downloads (Pure)


Metaheuristics are found to be efficient in different applications where the use of exact algorithms becomes short-handed. In the last decade, many of these algorithms have been introduced and used in a wide range of applications. Nevertheless, most of those approaches share similar components leading to a concern related to their novelty or contribution. Thus, in this paper, a pool template is proposed and used to categorize algorithm components permitting to analyze them in a structured way. We exemplify its use by means of continuous optimization metaheuristics, and provide some measures and methodology to identify their similarities and novelties. Finally, a discussion at a component level is provided in order to point out possible design differences and commonalities.

Original languageEnglish
Pages (from-to)265-287
JournalNatural Computing
Early online date10 Feb 2021
Publication statusPublished - 1 Jun 2022


  • UT-Hybrid-D
  • Comparison methodology
  • Metaheuristics design
  • Pool template
  • Metaheuristics
  • Decomposition
  • Comparison
  • Methodology
  • Continuous optimization
  • Optimization
  • Artificial Intelligence
  • decision support
  • Algorithm similarity
  • 22/1 OA procedure


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