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A new hybrid artificial hummingbird-simulated annealing algorithm to solve constrained mechanical engineering problems

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Yıldız, Betül Sultan
Mehta, Pranav
Sait, Sadiq M.
Panagant, Natee
Kumar, Sumit
Yıldız, Ali Rıza

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Walter de Gruyter Gmbh

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Nature-inspired algorithms known as metaheuristics have been significantly adopted by large-scale organizations and the engineering research domain due their several advantages over the classical optimization techniques. In the present article, a novel hybrid metaheuristic algorithm (HAHA-SA) based on the artificial hummingbird algorithm (AHA) and simulated annealing problem is proposed to improve the performance of the AHA. To check the performance of the HAHA-SA, it was applied to solve three constrained engineering design problems. For comparative analysis, the results of all considered cases are compared to the well-known optimizers. The statistical results demonstrate the dominance of the HAHA-SA in solving complex multi-constrained design optimization problems efficiently. Overall study shows the robustness of the adopted algorithm and develops future opportunities to optimize critical engineering problems using the HAHA-SA.

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Search algorithm, Truss structures, Optimization algorithm, Design optimization, Crashworthiness, Artificial hummingbird algorithm, Planetary gear train, Simulated annealing, Ten bar truss problem, Vehicle crash problem, Materials science

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