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

Bibliographic Details
Parent link:Neural Computing & Applications
Vol. 34, iss. 6.— 2022.— [P. 4081–4110]
Corporate Author: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение информационных технологий
Other Authors: Abualigah L. Laith, Mokhamed Elsaed (Mohamed Abd Elaziz) A. M. Akhmed Mokhamed, Khasawneh A. M. Ahmad, Alshinwan M. Mohammad, Ibrahim R. A. Rehab Ali, Al-qaness Mohammed A. A., Mirjalili S. Seyedali, Sumari P. Putra, Gandomi A. H. Amir
Summary:Title screen
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.
Режим доступа: по договору с организацией-держателем ресурса
Published: 2022
Subjects:
Online Access:https://doi.org/10.1007/s00521-021-06747-4
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=668708

MARC

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200 1 |a Meta-heuristic optimization algorithms for solving real-world mechanical engineering design problems: a comprehensive survey, applications, comparative analysis, and results  |f L. Abualigah, A. M. Mokhamed Elsaed (Mohamed Abd Elaziz), A. M. Khasawneh [et al.] 
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300 |a Title screen 
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330 |a 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. 
333 |a Режим доступа: по договору с организацией-держателем ресурса 
461 |t Neural Computing & Applications 
463 |t Vol. 34, iss. 6  |v [P. 4081–4110]  |d 2022 
610 1 |a электронный ресурс 
610 1 |a труды учёных ТПУ 
610 1 |a meta-heuristic optimization algorithms 
610 1 |a differential evolution 
610 1 |a real-world engineering design problems 
610 1 |a optimization problems 
610 1 |a algorithm 
610 1 |a benchmark 
610 1 |a метаэвристические алгоритмы 
610 1 |a проблемы 
610 1 |a инженерное проектирование 
610 1 |a алгоритмы 
610 1 |a оптимизация 
701 1 |a Abualigah  |b L.  |g Laith 
701 1 |a Mokhamed Elsaed (Mohamed Abd Elaziz)  |b A. M.  |c Specialist in the field of informatics and computer technology  |c Professor of Tomsk Polytechnic University  |f 1987-  |g Akhmed Mokhamed  |3 (RuTPU)RU\TPU\pers\46943 
701 1 |a Khasawneh  |b A. M.  |g Ahmad 
701 1 |a Alshinwan  |b M.  |g Mohammad 
701 1 |a Ibrahim  |b R. A.  |g Rehab Ali 
701 1 |a Al-qaness Mohammed  |b A. A. 
701 1 |a Mirjalili  |b S.  |g Seyedali 
701 1 |a Sumari  |b P.  |g Putra 
701 1 |a Gandomi  |b A. H.  |g Amir 
712 0 2 |a Национальный исследовательский Томский политехнический университет  |b Инженерная школа информационных технологий и робототехники  |b Отделение информационных технологий  |3 (RuTPU)RU\TPU\col\23515 
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