Yıldız, Betül SultanMehta, PranavSait, Sadiq M.Panagant, NateeKumar, SumitYıldız, Ali Rıza2024-10-142024-10-142022-07-260025-5300https://doi.org/10.1515/mt-2022-0123https://www.degruyter.com/document/doi/10.1515/mt-2022-0123/htmlhttps://hdl.handle.net/11452/46390Nature-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.eninfo:eu-repo/semantics/closedAccessSearch algorithmTruss structuresOptimization algorithmDesign optimizationCrashworthinessArtificial hummingbird algorithmPlanetary gear trainSimulated annealingTen bar truss problemVehicle crash problemMaterials scienceArticle0008213922000121043105064710.1515/mt-2022-0123