Journal
MATERIALS TESTING
Volume 64, Issue 7, Pages 1043-1050Publisher
WALTER DE GRUYTER GMBH
DOI: 10.1515/mt-2022-0123
Keywords
artificial hummingbird algorithm; planetary gear train; simulated annealing; ten bar truss problem; vehicle crash problem
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The article introduces a novel hybrid metaheuristic algorithm, HAHA-SA, based on the artificial hummingbird algorithm and simulated annealing problem, which shows dominance in efficiently solving complex multi-constrained design optimization problems.
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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