A comprehensive survey of the harmony search algorithm in clustering applications

Laith Abualigah, Ali Diabat, Zong Woo Geem

Research output: Contribution to journalArticlepeer-review


The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions.

Original languageEnglish (US)
Article number3827
JournalApplied Sciences (Switzerland)
Issue number11
StatePublished - Jun 1 2020


  • Clustering applications
  • Harmony search algorithm
  • Meta-heuristic optimization algorithms
  • Optimization problems

ASJC Scopus subject areas

  • General Materials Science
  • Instrumentation
  • General Engineering
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes


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