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Herausgeber: 
  • Navid Razmjooy
  • Advanced Techniques for Modifying Metaheuristics: Methods and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  2026  
    Genre:  EDV / Informatik 
     
    algorithm modification / Algorithms & data structures / algorithms and data structures / Artificial Intelligence / Computational Intelligence / COMPUTERS / Artificial Intelligence / Expert Systems / COMPUTERS / Artificial Intelligence / General / COMPUTERS / Programming / Algorithms
    ISBN:  9780443329722 
    EAN-Code: 
    9780443329722 
    Verlag:  Elsevier 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 191 mm / D 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Metaheuristics are widely used optimization techniques that have been successfully applied in various real-world problems. However, no single metaheuristic algorithm can solve all optimization problems with the same level of efficiency and effectiveness. Advanced Techniques for Modifying Metaheuristics: Methods and Applications covers the latest developments in the field of metaheuristics modification, including theoretical aspects, empirical studies, and practical applications. The book is organized into four main parts, introducing metaheuristics and their basic concepts, the theory and principles of modifying metaheuristics, empirical studies and experimental evaluations of modified metaheuristics, and practical applications of modified metaheuristics in various fields. The modification of metaheuristics has been shown to be a promising approach for improving their performance in solving complex optimization problems. However, there is still a need for more advanced and effective techniques for modifying metaheuristics. This book provides a critical analysis of the strengths and weaknesses of different modification techniques, as well as their suitability for different types of optimization problems. It also covers the latest developments in the field, including the use of machine learning and artificial intelligence techniques for modifying metaheuristics.

      



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