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


YILDIZ B. S. , Mehta P., Sait S. M. , Panagant N., Kumar S., YILDIZ A. R.

MATERIALS TESTING, vol.64, no.7, pp.1043-1050, 2022 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 64 Issue: 7
  • Publication Date: 2022
  • Doi Number: 10.1515/mt-2022-0123
  • Journal Name: MATERIALS TESTING
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.1043-1050
  • Keywords: artificial hummingbird algorithm, planetary gear train, simulated annealing, ten bar truss problem, vehicle crash problem, OPTIMIZATION ALGORITHM, DESIGN OPTIMIZATION, SEARCH ALGORITHM, TRUSS STRUCTURES, CRASHWORTHINESS

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.