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 language | English |
|---|---|
| Pages (from-to) | 1043-1050 |
| Number of pages | 8 |
| Journal | Materialpruefung/Materials Testing |
| Volume | 64 |
| Issue number | 7 |
| DOIs | |
| State | Published - 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