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Artificial gorilla troops algorithm for the optimization of a fine plate heat exchanger

  • Dildar Gürses

    Dildar Gürses received her B.Sc. and M.Sc. degrees from the Department of Mechanical Engineering, Bursa Uludağ University, Bursa, Turkey. She is a Ph.D. candidate in the same department.

    , Pranav Mehta , Vivek Patel , Sadiq M. Sait and Ali Riza Yildiz EMAIL logo
Published/Copyright: September 6, 2022
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Abstract

Adaptability of the metaheuristic (MH) algorithms in multidisciplinary platforms confirms its significance and effectiveness for the solution of the constraints problems. In this article, one of the imperative thermal system components-plate fin heat exchangers is economically optimized using the novel artificial gorilla troops optimization algorithms (AGTOAs). The cost optimization challenge of the PFHE includes the initial and running cost that needs to be minimized by optimizing several design variables subjecting to critical boundary conditions. To confirm the performance of the AGTOA, the statistical results obtained were compared with nine benchmark MHs algorithms. It was found that AGTO is a robust optimization algorithm because it was able to fetch the best results for the function with 100% of the success rate compared to the rest of the algorithms. Moreover, considering the superior results obtained from the AGTO, it can be applied to numerous applications of the engineering design optimization.


Corresponding author: Ali Riza Yildiz, Department of Mechanical Engineering, Bursa Uludag Universitesi, Uludağ University, Görükle bursa, Bursa 16059, Turkey, E-mail:

About the author

Dildar Gürses

Dildar Gürses received her B.Sc. and M.Sc. degrees from the Department of Mechanical Engineering, Bursa Uludağ University, Bursa, Turkey. She is a Ph.D. candidate in the same department.

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

  2. Research funding: None declared.

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

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Published Online: 2022-09-06
Published in Print: 2022-09-27

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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