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
Hlavní autoři: Ghasemi, Mojtaba, Zare, Mohsen, Trojovský, Pavel, Rao, Ravipudi Venkata, Trojovská, Eva, Kandasamy, Venkatachalam
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 08.07.2024
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.
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
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  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
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  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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Ivy algorithm
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Snippet 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...
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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
URI https://dx.doi.org/10.1016/j.knosys.2024.111850
Volume 295
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