Search and Optimization by Metaheuristics Techniques and Algorithms Inspired by Nature /

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphas...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Du, Ke-Lin (Autor), Swamy, M. N. S. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Birkhäuser, 2016.
Edición:1st ed. 2016.
Temas:
Mathematics-Data processing.
Algorithms.
Mathematical optimization.
Computer simulation.
Computational intelligence.
Computational Science and Engineering.
Optimization.
Computer Modelling.
Computational Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Preface
  • Introduction
  • Simulated Annealing
  • Optimization by Recurrent Neural Networks
  • Genetic Algorithms and Genetic Programming
  • Evolutionary Strategies
  • Differential Evolution
  • Estimation of Distribution Algorithms
  • Mimetic Algorithms
  • Topics in EAs
  • Particle Swarm Optimization
  • Artificial Immune Systems
  • Ant Colony Optimization
  • Tabu Search and Scatter Search
  • Bee Metaheuristics
  • Harmony Search
  • Biomolecular Computing
  • Quantum Computing
  • Other Heuristics-Inspired Optimization Methods
  • Dynamic, Multimodal, and Constraint-Satisfaction Optimizations
  • Multiobjective Optimization
  • Appendix 1: Discrete Benchmark Functions
  • Appendix 2: Test Functions
  • Index.

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