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

Betül Sultan Yildiz*, Pranav Mehta, Sadiq M. Sait, Natee Panagant, Sumit Kumar, Ali Riza Yildiz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

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.

Original languageEnglish
Pages (from-to)1043-1050
Number of pages8
JournalMaterialpruefung/Materials Testing
Volume64
Issue number7
DOIs
StatePublished - Jul 2022

Bibliographical note

Publisher Copyright:
© 2022 Walter de Gruyter GmbH, Berlin/Boston.

Keywords

  • artificial hummingbird algorithm
  • planetary gear train
  • simulated annealing
  • ten bar truss problem
  • vehicle crash problem

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering

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