Hybridizing harmony search algorithm with different mutation operators for continuous problems

Basima Hani F. Hasan, Iyad Abu Doush*, Eslam Al Maghayreh, Faisal Alkhateeb, Mohammad Hamdan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)


Harmony Search (HS) is a recent EA inspired by musical improvisation process to seek a pleasing harmony. Mutation is a vital component used in Evolutionary Algorithms (EA) where a value in the population is randomly selected to be altered to improve the evolution process. The original HS algorithm applies an operation similar to mutation during the random consideration operator. During random selection operator a value within the range of the decision variable is selected randomly to explore different areas in the search space. This paper aims at experimentally evaluating the performance of HS algorithm after replacing the random consideration operator in the original HS with five different mutation methods. The different variations of HS are experimented on standard benchmark functions in terms of final obtained solution and convergence speed. The results show that using polynomial mutation improves the performance of the HS algorithm for most of the used functions.

Original languageEnglish
Pages (from-to)1166-1182
Number of pages17
JournalApplied Mathematics and Computation
Publication statusPublished - 1 Apr 2014


  • Evolutionary Algorithms
  • Harmony Search algorithm
  • Meta-heuristic algorithm
  • Mutation
  • Polynomial mutation

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics


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