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Meta-heuristic optimization algorithms for solving real-world mechanical engineering design problems: a comprehensive survey, applications, comparative analysis, and results

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Abstract

Real-world engineering design problems are widespread in various research disciplines in both industry and industry. Many optimization algorithms have been employed to address these kinds of problems. However, the algorithm’s performance substantially reduces with the increase in the scale and difficulty of problems. Various versions of the optimization methods have been proposed to address the engineering design problems in the literature efficiently. In this paper, a comprehensive review of the meta-heuristic optimization methods that have been used to solve engineering design problems is proposed. We use six main keywords in collecting the data (meta-heuristic, optimization, algorithm, engineering, design, and problems). It is worth mentioning that there is no survey or comparative analysis paper on this topic available in the literature to the best of our knowledge. The state-of-the-art methods are presented in detail over several categories, including basic, modified, and hybrid methods. Moreover, we present the results of the state-of-the-art methods in this domain to figure out which version of optimization methods performs better in solving the problems studied. Finally, we provide remarkable future research directions for the potential methods. This work covers the main important topics in the engineering and artificial intelligence domain. It presents a large number of published works in the literature related to the meta-heuristic optimization methods in solving various engineering design problems. Future researches can depend on this review to explore the literature on meta-heuristic optimization methods and engineering design problems.

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Authors and Affiliations

  1. Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan

    Laith Abualigah, Ahmad M. Khasawneh & Mohammad Alshinwan

  2. School of Computer Science, Universiti Sains Malaysia, Penang, Malaysia

    Laith Abualigah & Putra Sumari

  3. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, 44519, Egypt

    Mohamed Abd Elaziz & Rehab Ali Ibrahim

  4. Faculty of Engineering, Sana’a University, Sana’a, 12544, Yemen

    Mohammed A. A. Al-qaness

  5. Centre for Artificial Intelligence Research and Optimization, Torrens University Australia, 90 Bowen Terrace, Fortitude Valley, QLD, 4006, Australia

    Seyedali Mirjalili

  6. Yonsei Frontier Lab, Yonsei University, Seoul, Korea

    Seyedali Mirjalili

  7. Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, 2007, Australia

    Amir H. Gandomi

  8. Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, 346, United Arab Emirates

    Mohamed Abd Elaziz

  9. Faculty of Computer Science & Engineering, Galala University, Suze, 435611, Egypt

    Mohamed Abd Elaziz

  10. School of Computer Science and Robotics, Tomsk Polytechnic University, Tomsk, 634050, Russia

    Mohamed Abd Elaziz

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  1. Laith Abualigah
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Abualigah, L., Elaziz, M.A., Khasawneh, A.M. et al. Meta-heuristic optimization algorithms for solving real-world mechanical engineering design problems: a comprehensive survey, applications, comparative analysis, and results. Neural Comput & Applic 34, 4081–4110 (2022). https://doi.org/10.1007/s00521-021-06747-4

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