Publication: 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
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Authors
Yıldız, Ali Rıza
Authors
Hammoudi, Abderazek
Hamza, Ferhat
Gao, Liang
Sadiq M, Sait
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Walter de Gruyter
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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.
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Keywords
Heuristic methods, Learning algorithms, Optimization, Queueing theory, Ant lion algorithm, Comparative analyzes, Design problems, Mechanical design optimization, Optimization algorithms, Queuing search algorithm, Search algorithms, Sine-cosine algorithm, Single stage, Single-stage spur gear, Spur gears, Materials science, Structural optimization, Hybrid approach, Queuing search algorithm, Sine cosine algorithm, Ant lion algorithm, Single-stage spur gear, Optimization algorithm
Citation
Abderazek, H. vd. (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". Materials Testing, 63(5), 442-447.