Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems

M. Fesanghary, Mehrdad Mahdavi, M. Minary-Jolandan, Y. Alizadeh

Research output: Contribution to journalArticle

236 Scopus citations

Abstract

This study presents a hybrid harmony search algorithm (HHSA) to solve engineering optimization problems with continuous design variables. Although the harmony search algorithm (HSA) has proven its ability of finding near global regions within a reasonable time, it is comparatively inefficient in performing local search. In this study sequential quadratic programming (SQP) is employed to speed up local search and improve precision of the HSA solutions. Moreover, an empirical study is performed in order to determine the impact of various parameters of the HSA on convergence behavior. Various benchmark engineering optimization problems are used to illustrate the effectiveness and robustness of the proposed algorithm. Numerical results reveal that the proposed hybrid algorithm, in most cases is more effective than the HSA and other meta-heuristic or deterministic methods.

Original languageEnglish (US)
Pages (from-to)3080-3091
Number of pages12
JournalComputer Methods in Applied Mechanics and Engineering
Volume197
Issue number33-40
DOIs
StatePublished - Jun 1 2008

All Science Journal Classification (ASJC) codes

  • Computational Mechanics
  • Mechanics of Materials
  • Mechanical Engineering
  • Physics and Astronomy(all)
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems'. Together they form a unique fingerprint.

  • Cite this