Global-best harmony search

Mahamed G.H. Omran, Mehrdad Mahdavi

Research output: Contribution to journalArticlepeer-review

750 Scopus citations


Harmony search (HS) is a new meta-heuristic optimization method imitating the music improvisation process where musicians improvise their instruments' pitches searching for a perfect state of harmony. A new variant of HS, called global-best harmony search (GHS), is proposed in this paper where concepts from swarm intelligence are borrowed to enhance the performance of HS. The performance of the GHS is investigated and compared with HS and a recently developed variation of HS. The experiments conducted show that the GHS generally outperformed the other approaches when applied to ten benchmark problems. The effect of noise on the performance of the three HS variants is investigated and a scalability study is conducted. The effect of the GHS parameters is analyzed. Finally, the three HS variants are compared on several Integer Programming test problems. The results show that the three approaches seem to be an efficient alternative for solving Integer Programming problems.

Original languageEnglish (US)
Pages (from-to)643-656
Number of pages14
JournalApplied Mathematics and Computation
Issue number2
StatePublished - May 1 2008

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Applied Mathematics


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