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

  • Ali Riza Yildiz EMAIL logo and Pranav Mehta

    Pranav Mehta is an Assistant Professor at the Department of Mechanical Engineering, Dharmsinh Desai University, Gujarat, India.

Published/Copyright: May 9, 2022
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Abstract

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.


Corresponding author: Ali Riza Yildiz, Department of Mechanical Engineering, Bursa Uludag Universitesi, Bursa, Turkey, E-mail:

Funding source: Bursa Uludag University Scientific Research Projects Centre (BAP)

Award Identifier / Grant number: BUAP(MH)-2019/2

About the author

Pranav Mehta

Pranav Mehta is an Assistant Professor at the Department of Mechanical Engineering, Dharmsinh Desai University, Gujarat, India.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: Professor Ali Riza Yildiz gratefully acknowledges the support provided by Bursa Uludag University Scientific Research Projects Centre (BAP) under Grant Nos. BUAP(MH)-2019/2.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Published Online: 2022-05-09
Published in Print: 2022-05-25

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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