A Comparative Study of Recent Non-traditional Methods for Mechanical Design Optimization

YILDIZ A. R., Abderazek H., Mirjalili S.

ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, vol.27, no.4, pp.1031-1048, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Review
  • Volume: 27 Issue: 4
  • Publication Date: 2020
  • Doi Number: 10.1007/s11831-019-09343-x
  • Journal Name: ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, MathSciNet, zbMATH, DIALNET
  • Page Numbers: pp.1031-1048
  • Bursa Uludag University Affiliated: Yes

Abstract

Solving practical mechanical problems is considered as a real challenge for evaluating the efficiency of newly developed algorithms. The present article introduces a comparative study on the application of ten recent meta-heuristic approaches to optimize the design of six mechanical engineering optimization problems. The algorithms are: the artificial bee colony (ABC), particle swarm optimization (PSO) algorithm, moth-flame optimization (MFO), ant lion optimizer (ALO), water cycle algorithm (WCA), evaporation rate WCA (ER-WCA), grey wolf optimizer (GWO), mine blast algorithm (MBA), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). The performances of the algorithms are tested quantitatively and qualitatively using convergence speed, solution quality, and the robustness. The experimental results on the six mechanical problems demonstrate the efficiency and the ability of the algorithms used in this article.