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The Moth-Flame Optimization Algorithm of Abrasive Water Jet Cutting Process.

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Τίτλος: The Moth-Flame Optimization Algorithm of Abrasive Water Jet Cutting Process.
Συγγραφείς: Kawecka, Elżbieta1 (AUTHOR) ekawecka@ajp.edu.pl, Puzio, Piotr1 (AUTHOR)
Πηγή: Procedia Computer Science. 2024, Vol. 246, p2912-2921. 10p.
Θεματικοί όροι: Metaheuristic algorithms, Optimization algorithms, Water jet cutting, Water jets, Structural steel
Περίληψη: The article presents the possibility of using the Moth-Flame Optimization (MFO) algorithm for Abrasive Water Jet machining (AWJ) of structural steel materials. In order to carry out the optimization, an original program was written in Python programming language. In turn, for this optimization process the objective function was determined using the Response Surface Methodology (RSM). Then, a set of control parameters was determined at which the value of the objective function reaches an extreme value. The optimal value calculated based on the Moth-Flame Optimization algorithm was compared with the value of the best effect determined experimentally. [ABSTRACT FROM AUTHOR]
Βάση Δεδομένων: Supplemental Index
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  – Url: https://www.doi.org/10.1016/j.procs.2024.09.379?
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An: 181191876
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PubType: Academic Journal
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PreciseRelevancyScore: 965.713256835938
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: The Moth-Flame Optimization Algorithm of Abrasive Water Jet Cutting Process.
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  Data: <searchLink fieldCode="AR" term="%22Kawecka%2C+Elżbieta%22">Kawecka, Elżbieta</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ekawecka@ajp.edu.pl</i><br /><searchLink fieldCode="AR" term="%22Puzio%2C+Piotr%22">Puzio, Piotr</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Procedia+Computer+Science%22">Procedia Computer Science</searchLink>. 2024, Vol. 246, p2912-2921. 10p.
– Name: Subject
  Label: Subject Terms
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  Data: <searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Water+jet+cutting%22">Water jet cutting</searchLink><br /><searchLink fieldCode="DE" term="%22Water+jets%22">Water jets</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+steel%22">Structural steel</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The article presents the possibility of using the Moth-Flame Optimization (MFO) algorithm for Abrasive Water Jet machining (AWJ) of structural steel materials. In order to carry out the optimization, an original program was written in Python programming language. In turn, for this optimization process the objective function was determined using the Response Surface Methodology (RSM). Then, a set of control parameters was determined at which the value of the objective function reaches an extreme value. The optimal value calculated based on the Moth-Flame Optimization algorithm was compared with the value of the best effect determined experimentally. [ABSTRACT FROM AUTHOR]
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      – Type: doi
        Value: 10.1016/j.procs.2024.09.379
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 2912
    Subjects:
      – SubjectFull: Metaheuristic algorithms
        Type: general
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Water jet cutting
        Type: general
      – SubjectFull: Water jets
        Type: general
      – SubjectFull: Structural steel
        Type: general
    Titles:
      – TitleFull: The Moth-Flame Optimization Algorithm of Abrasive Water Jet Cutting Process.
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          Name:
            NameFull: Kawecka, Elżbieta
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          Name:
            NameFull: Puzio, Piotr
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          Dates:
            – D: 01
              M: 08
              Text: 2024
              Type: published
              Y: 2024
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            – Type: volume
              Value: 246
          Titles:
            – TitleFull: Procedia Computer Science
              Type: main
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