Optimization based on the smart behavior of plants with its engineering applications: Ivy algorithm
This study presents a powerful and new modeling variant of bio-inspired algorithms, namely, the Ivy algorithm (IVYA), drawn from the growth patterns of Ivy plants. The algorithm simulates the coordinated and ordered population growth and the spreading and evolution of Ivy plants. The growth rate of...
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| Vydáno v: | Knowledge-based systems Ročník 295; s. 111850 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
08.07.2024
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| Témata: | |
| ISSN: | 0950-7051, 1872-7409 |
| On-line přístup: | Získat plný text |
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| Abstract | This study presents a powerful and new modeling variant of bio-inspired algorithms, namely, the Ivy algorithm (IVYA), drawn from the growth patterns of Ivy plants. The algorithm simulates the coordinated and ordered population growth and the spreading and evolution of Ivy plants. The growth rate of Ivy plants is modeled using a differential equation and a data-intensive experimental process. The algorithm utilizes the knowledge of nearby Ivy plants to determine the direction of growth. Additionally, the algorithm mimics the behavior of Ivy plants in nature by choosing the closest and most vital neighbor for self-improvement. The IVYA's unique characteristics of preserving population diversity and its simplicity and flexibility allow for easy modification and extension, thus enabling researchers and practitioners to explore various modifications and techniques to enhance its performance and capabilities. These are the basic needs in optimizing engineering problems. The IVYA is compared with ten other algorithms on 26 classical test functions, demonstrating superior performance. Furthermore, the effectiveness of IVYA is shown by solving 12 engineering optimization problems and comparing the results with various optimization algorithms. The experimental results highlight the efficacy and competitiveness of the IVYA in solving optimization problems. Consider that the source code of the IVYA is publicly available at https://www.optim-app.com/projects/ivya. |
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| AbstractList | This study presents a powerful and new modeling variant of bio-inspired algorithms, namely, the Ivy algorithm (IVYA), drawn from the growth patterns of Ivy plants. The algorithm simulates the coordinated and ordered population growth and the spreading and evolution of Ivy plants. The growth rate of Ivy plants is modeled using a differential equation and a data-intensive experimental process. The algorithm utilizes the knowledge of nearby Ivy plants to determine the direction of growth. Additionally, the algorithm mimics the behavior of Ivy plants in nature by choosing the closest and most vital neighbor for self-improvement. The IVYA's unique characteristics of preserving population diversity and its simplicity and flexibility allow for easy modification and extension, thus enabling researchers and practitioners to explore various modifications and techniques to enhance its performance and capabilities. These are the basic needs in optimizing engineering problems. The IVYA is compared with ten other algorithms on 26 classical test functions, demonstrating superior performance. Furthermore, the effectiveness of IVYA is shown by solving 12 engineering optimization problems and comparing the results with various optimization algorithms. The experimental results highlight the efficacy and competitiveness of the IVYA in solving optimization problems. Consider that the source code of the IVYA is publicly available at https://www.optim-app.com/projects/ivya. |
| ArticleNumber | 111850 |
| Author | Trojovský, Pavel Zare, Mohsen Rao, Ravipudi Venkata Trojovská, Eva Kandasamy, Venkatachalam Ghasemi, Mojtaba |
| Author_xml | – sequence: 1 givenname: Mojtaba surname: Ghasemi fullname: Ghasemi, Mojtaba organization: Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran – sequence: 2 givenname: Mohsen orcidid: 0000-0002-2604-615X surname: Zare fullname: Zare, Mohsen organization: Department of Electrical Engineering, Faculty of Engineering, Jahrom University, Jahrom, Iran – sequence: 3 givenname: Pavel orcidid: 0000-0001-8992-125X surname: Trojovský fullname: Trojovský, Pavel email: pavel.trojovsky@uhk.cz organization: Department of Mathematics, Faculty of Science, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic – sequence: 4 givenname: Ravipudi Venkata surname: Rao fullname: Rao, Ravipudi Venkata organization: Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Ichchanath, Surat, Gujarat, India – sequence: 5 givenname: Eva orcidid: 0000-0001-9901-5867 surname: Trojovská fullname: Trojovská, Eva organization: Department of Mathematics, Faculty of Science, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic – sequence: 6 givenname: Venkatachalam surname: Kandasamy fullname: Kandasamy, Venkatachalam organization: Department of Mathematics, Faculty of Science, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic |
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| SubjectTerms | Engineering design Global optimization Ivy algorithm Meta-heuristic algorithms Nature-inspired algorithm |
| Title | Optimization based on the smart behavior of plants with its engineering applications: Ivy algorithm |
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