Nature-inspired optimization algorithms /

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-cho...

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Main Author: Yang, Xin-She, (Author)
Format: Book Electronic
Language:English
Published:Amsterdam : Elsevier, 2014.
Series:Elsevier insights.
Subjects:
Online Access:ebook Central Access is available only to authorized users.
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Table of Contents:
  • 880-01 1. Introduction to algorithms
  • 2. Analysis of algorithms
  • 3. Random walks and optimization
  • 4. Simulated annealing
  • 5. Genetic algorithms
  • 6. Differential evolution
  • 7. Particle swarm optimization
  • 8. Firefly algorithms
  • 9. Cuckoo search
  • 10. Bat algorithms
  • Flower pollination algorithms
  • 12. A framework for self-tuning algorithms
  • 13. How to deal with constraints
  • 14. Multi-objective optimization
  • 15. Other algorithms and hybrid algorithms
  • Appendices.