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, vol.64, no.5, pp.706-713, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 64 Issue: 5
  • Publication Date: 2022
  • Doi Number: 10.1515/mt-2022-0012
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.706-713
  • Keywords: 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 Uludag University Affiliated: Yes


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.