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


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
JournalNatural Computing
Publication statusE-pub ahead of print/First online - 10 Feb 2021


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

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