Crow Search Algorithm: Theory, Recent Advances, and Applications
In this article, a comprehensive overview of the Crow Search Algorithm (CSA) is introduced with detailed discussions, which is intended to keep researchers interested in swarm intelligence algorithms and optimization problems. CSA is a new swarm intelligence algorithm recently developed, which simul...
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| Vydané v: | IEEE access Ročník 8; s. 173548 - 173565 |
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| Hlavní autori: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Piscataway
IEEE
2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2169-3536, 2169-3536 |
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| Abstract | In this article, a comprehensive overview of the Crow Search Algorithm (CSA) is introduced with detailed discussions, which is intended to keep researchers interested in swarm intelligence algorithms and optimization problems. CSA is a new swarm intelligence algorithm recently developed, which simulates crow behavior in storing excess food and retrieving it when needed. In the optimization theory, the crow is the searcher, the surrounding environment is the search space, and randomly storing the location of food is a feasible solution. Among all food locations, the location where the most food is stored is considered to be the global optimal solution, and the objective function is the amount of food. By simulating the intelligent behavior of crows, CSA tries to find optimal solutions to various optimization problems. It has gained a considerable interest worldwide since its advantages like simple implementation, a few numbers of parameters, flexibility, etc. This survey introduces a comprehensive variant of CSA, including hybrid, modified, and multi-objective versions. Furthermore, based on the analyzed papers published in the literature by some publishers such as IEEE, Elsevier, and Springer, the comprehensive application scenarios of CSA such as power, computer science, machine learning, civil engineering have also been reviewed. Finally, the advantages and disadvantages of CSA have been discussed by conducting some comparative experiments with other similar published peers. |
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| AbstractList | In this article, a comprehensive overview of the Crow Search Algorithm (CSA) is introduced with detailed discussions, which is intended to keep researchers interested in swarm intelligence algorithms and optimization problems. CSA is a new swarm intelligence algorithm recently developed, which simulates crow behavior in storing excess food and retrieving it when needed. In the optimization theory, the crow is the searcher, the surrounding environment is the search space, and randomly storing the location of food is a feasible solution. Among all food locations, the location where the most food is stored is considered to be the global optimal solution, and the objective function is the amount of food. By simulating the intelligent behavior of crows, CSA tries to find optimal solutions to various optimization problems. It has gained a considerable interest worldwide since its advantages like simple implementation, a few numbers of parameters, flexibility, etc. This survey introduces a comprehensive variant of CSA, including hybrid, modified, and multi-objective versions. Furthermore, based on the analyzed papers published in the literature by some publishers such as IEEE, Elsevier, and Springer, the comprehensive application scenarios of CSA such as power, computer science, machine learning, civil engineering have also been reviewed. Finally, the advantages and disadvantages of CSA have been discussed by conducting some comparative experiments with other similar published peers. |
| Author | Hussien, Abdelazim G. Amin, Mohamed Wang, Mingjing Gumaei, Abdu Alsanad, Ahmed Chen, Huiling Liang, Guoxi |
| Author_xml | – sequence: 1 givenname: Abdelazim G. orcidid: 0000-0001-5394-0678 surname: Hussien fullname: Hussien, Abdelazim G. organization: Faculty of Science, Fayoum University, Faiyum, Egypt – sequence: 2 givenname: Mohamed surname: Amin fullname: Amin, Mohamed organization: Faculty of Science, Menoufia University, Shebin El-Kom, Egypt – sequence: 3 givenname: Mingjing orcidid: 0000-0003-1985-4076 surname: Wang fullname: Wang, Mingjing organization: Institute of Research and Development, Duy Tan University, Da Nang, Vietnam – sequence: 4 givenname: Guoxi orcidid: 0000-0003-4754-6644 surname: Liang fullname: Liang, Guoxi email: guoxiliang2017@gmail.com organization: Department of Information Technology, Wenzhou Polytechnic, Wenzhou, China – sequence: 5 givenname: Ahmed orcidid: 0000-0003-1702-8643 surname: Alsanad fullname: Alsanad, Ahmed email: aasanad@ksu.edu.sa organization: Department of Information Systems, College of Computer and Information Sciences, STC’s Artificial Intelligence Chair, King Saud University, Riyadh, Saudi Arabia – sequence: 6 givenname: Abdu orcidid: 0000-0001-8512-9687 surname: Gumaei fullname: Gumaei, Abdu organization: Department of Information Systems, College of Computer and Information Sciences, STC’s Artificial Intelligence Chair, King Saud University, Riyadh, Saudi Arabia – sequence: 7 givenname: Huiling orcidid: 0000-0002-7714-9693 surname: Chen fullname: Chen, Huiling email: chenhuiling.jlu@gmail.com organization: College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, China |
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| SubjectTerms | Algorithms Classification algorithms Crow search algorithm CSA Engineering education Food Genetic algorithms Heuristic algorithms Machine learning Mathematical model meta-heuristics nature-inspired algorithms Optimization Particle swarm optimization Search algorithms Swarm intelligence |
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| Title | Crow Search Algorithm: Theory, Recent Advances, and Applications |
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