Abstract
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.
About the authors
Natee Panagant received a B.Eng. in Mechanical Engineering from Chulalongkorn University, Bangkok, Thailand; M.Eng. and Ph.D. in Mechanical Engineering from Khon Kaen University, Khon Kaen, Thailand. Currently, he is a lecturer at the Department of Mechanical Engineering, Khon Kaen University. His research interests include multidisciplinary design optimization, evolutionary computation, and finite element analysis.
Sumit Kumar received the BEng degree(Hons.) in mechanical engineering from Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India, in 2012, and the MEng degree (Hons.) in design engineering from the Malaviya National Institute of Technology (NIT), Jaipur, India, in 2015. He is currently a Ph.D. research scholar with the College of Sciences and Engineering, Australian Maritime College, University of Tasmania, Launceston, Australia. His major research interests include metaheuristics techniques, multi-objective optimization, evolutionary algorithm, and renewable energy systems.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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