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Genetic algorithm essentials /

This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts over...

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Détails bibliographiques
Cote:Libro Electrónico
Auteur principal: Kramer, Oliver (Auteur)
Format: Électronique eBook
Langue:Inglés
Publié: Cham, Switzerland : Springer, 2017.
Collection:Studies in computational intelligence ; v. 679.
Sujets:
Accès en ligne:Texto completo
Table des matières:
  • Part I: Foundations
  • Introduction
  • Genetic Algorithms
  • Parameters
  • Part II: Solution Spaces
  • Multimodality
  • Constraints
  • Multiple Objectives
  • Part III: Advanced Concepts
  • Theory
  • Machine Learning
  • Applications
  • Part IV: Ending
  • Summary and Outlook
  • Index
  • References.