A novel hybrid arithmetic optimization algorithm for solving constrained optimization problems


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

KNOWLEDGE-BASED SYSTEMS, vol.271, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 271
  • Publication Date: 2023
  • Doi Number: 10.1016/j.knosys.2023.110554
  • Journal Name: KNOWLEDGE-BASED SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, Library and Information Science Abstracts, Library, Information Science & Technology Abstracts (LISTA)
  • Keywords: Hybrid algorithm, Arithmetic optimization, Nelder-Mead, Metaheuristics, Manufacturing problems, Engineering optimization, BEE COLONY ALGORITHM, PARAMETER OPTIMIZATION, DESIGN OPTIMIZATION, MILLING OPERATIONS, GENETIC ALGORITHM, SEARCH HEURISTICS
  • Bursa Uludag University Affiliated: Yes

Abstract

The present study aims to optimize the engineering design and manufacturing problems with a novel hybrid optimizer named: AOA-NM (Arithmetic optimization-Nelder mead). To overcome the local optima trap shortcoming and improve the solution quality of a recently introduced arithmetic optimization algorithm (AOA), the Nelder-Mead local search methodology has been incorporated into the basic AOA framework. The objective of the proposed hybridization approach was to facilitate the refinement of the exploration-exploitation behaviour of the AOA search. In the numerical validation stage, numerous multidimensional benchmarks from the CEC2020 were used as challenging testing functions to investigate the suggested AOA-NM optimizer. To investigate the viability of the proposed hybridized algorithm in real-world applications, it is investigated for ten constrained engineering de-sign problems, and the performance was contrasted with other distinguished metaheuristics extracted from the literature. Additionally, a hands-on manufacturing problem of milling process parameter optimization and vehicle structure shape optimization is posed and solved at the forefront to evaluate both AOA and AOA-NM efficacy. The proficiency of the AOA-NM algorithm, in terms of both solution quality and stability, is confirmed by performed comparative analysis and found to be robust in handling challenging practical issues.(c) 2023 Published by Elsevier B.V.