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Licensed Unlicensed Requires Authentication Published by De Gruyter May 23, 2021

A comparative analysis of the queuing search algorithm, the sine-cosine algorithm, the ant lion algorithm to determine the optimal weight design problem of a spur gear drive system

Hammoudi Abderazek, Ferhat Hamza, Ali Riza Yildiz, Liang Gao and Sadiq M. Sait
From the journal Materials Testing

Abstract

Metaheuristic optimization algorithms have gained relevance and have effectively been investigated for solving complex real design problems in diverse fields of science and engineering. In this paper, a recent meta-heuristic approach inspired by human social concepts, namely the queuing search algorithm (QSA), is implemented for the first time to optimize the main parameters of the spur gear, in particular, to minimize the weight of a single-stage spur gear. The effectiveness of the algorithm introduced is examined in two steps. First, the algorithm used is compared with descriptions in previous studies and indicates that the final results obtained by QSA lead to a reduction in gear weight by 7.5 %. Furthermore, the outcomes obtained are compared with those for the other five algorithms. The results reveal that the QSA outperforms the techniques with which it is compared such as the sine-cosine optimization algorithm, the ant lion optimization algorithm, the interior search algorithm, the teaching-learning-based algorithm, and the jaya algorithm in terms of robustness, success rate, and convergence capability.


Prof. Dr. Ali Rıza Yıldız Department of Automotive Engineering Uludağ University Görükle, Bursa, Turkey

Acknowledgment

The authors would like to express their gratitude to Bursa Uludağ University, Bursa, Turkey, and King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia, for their support of this research.

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Published Online: 2021-05-23
Published in Print: 2021-05-26

© 2021 Walter de Gruyter GmbH, Berlin/Boston, Germany

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