Genetic Engineering Algorithm (GEA): An Eﬃcient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems-Reference-Cited by-同舟云学术

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Genetic Engineering Algorithm (GEA): An Eﬃcient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems

Published:2024-12-15 Issue:3 Volume: Page:
ISSN:2413-9777
Container-title:Автоматика и телемеханика
language:
Short-container-title:Avtomatika i telemehanika

Author:

Sohrabi Majid¹,Fathollahi-Fard Amir M.²,Gromov V. A¹

Affiliation:

1. Национальный исследовательский университет “Высшая школа экономики”

2. Университет Квебека в Монреале

Publisher

The Russian Academy of Sciences

Reference41 articles.

1. Holland J. Adaptation in natural and artiﬁcial systems. Ann Arbor: University of Michigan Press, 1975.

2. Elshaer R., Awad H. A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants // Computers Indust. Engin. 2020. V. 140.P. 106242.

3. Katoch S., Chauhan S.S., Kumar V. A review on genetic algorithm: past, present, and future // Multimedia Tools Appli. 2021. V. 80. P. 8091–8126.

4. Yang X.S., Deb S. Engineering optimisation by cuckoo search // Int. J. Math. Modell. Numer. Optim. 2010. V. 1. No. 4. P. 330–343.

5. Mirjalili S., Lewis A. The whale optimization algorithm // Advanc. Engin. Software. 2016. V. 95. P. 51–67.

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