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

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 opti...

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Bibliographic Details
Published in:Archives of computational methods in engineering 2020-09, Vol.27 (4), p.1031-1048
Main Authors: Yildiz, Ali Riza, Abderazek, Hammoudi, Mirjalili, Seyedali
Format: Article
Language:English
Subjects:
Algorithms
Comparative studies
Design optimization
Engineering
Evaporation rate
Heuristic methods
Mathematical and Computational Engineering
Mechanical engineering
Original Paper
Particle swarm optimization
Robustness (mathematics)
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Summary: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.
ISSN:1134-3060
1886-1784
DOI:10.1007/s11831-019-09343-x