Hybrid spotted hyena-Nelder-Mead optimization algorithm for selection of optimal machining parameters in grinding operations

Phnldee N., Patel V. K., Sait S. M., Bureerat S., Tildiz A. R.

MATERIALS TESTING, cilt.63, sa.3, ss.293-298, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 63 Sayı: 3
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1515/mt-2020-0043
  • Dergi Adı: MATERIALS TESTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.293-298
  • Anahtar Kelimeler: Spotted hyena optimization algorithm, nelder-mead optimization, manufacturing, grinding operation, PARTICLE SWARM OPTIMIZATION, MULTIPASS TURNING OPERATIONS, MULTIOBJECTIVE OPTIMIZATION, DESIGN OPTIMIZATION, STRUCTURAL OPTIMIZATION, SEARCH APPROACH, CRASHWORTHINESS
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

In this research, a novel optimization algorithm, which is a hybrid spotted hyena-Nelder-Mead optimization algorithm (HSHO-NM) algorithm, has been introduced in solving grinding optimization problems. A well-known grinding optimization problem is solved to prove the superiority of the HSHO-NM over other algorithms. The results of the HSHO-NM are compared with others. The results show that HSHO-NM is an efficient optimization approach for obtaining the optimal manufacturing variables in grinding operations.