Manta ray foraging optimization algorithm and hybrid Taguchi salp swarm-Nelder-Mead algorithm for the structural design of engineering components

Yıldız A. R., Mehta P.

MATERIALS TESTING, cilt.64, sa.5, ss.706-713, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 64 Sayı: 5
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1515/mt-2022-0012
  • Dergi Adı: MATERIALS TESTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.706-713
  • Anahtar Kelimeler: hybrid salp swarm algorithm, manta ray foraging optimizer, Nelder-Mead, structural optimization, Taguchi, weight reduction, NATURE-INSPIRED ALGORITHM, GRADIENT-BASED OPTIMIZER, HEAT-TRANSFER SEARCH, PERFORMANCE
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

The adaptability of metaheuristics is proliferating rapidly for optimizing engineering designs and structures. The imperative need for the fuel-efficient design of vehicles with lightweight structures is also a soaring demand raised by the different industries. This research contributes to both areas by using both the hybrid Taguchi salp swarm algorithm-Nelder-Mead (HTSSA-NM) and the manta ray foraging optimization (MRFO) algorithm to optimize the structure and shape of the automobile brake pedal. The results of HTSSA-NM and MRFO are compared with some well-established metaheuristics such as horse herd optimization algorithm, black widow optimization algorithm, squirrel search algorithm, and Harris Hawks optimization algorithm to verify its performance. It is observed that HTSSA-NM is robust and superior in terms of optimizing shape with the least mass of the engineering structures. Also, HTSSA-NM realize the best value for the present problem compared to the rest of the optimizer.