Comprehensive Metaheuristics
eBook - ePub

Comprehensive Metaheuristics

Algorithms and Applications

  1. 466 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Comprehensive Metaheuristics

Algorithms and Applications

Book details
Table of contents
Citations

About This Book

Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applications across a variety of research fields. The book starts with fundamentals, mathematical prerequisites, and conceptual approaches to provide readers with a solid foundation. After presenting multi-objective optimization, constrained optimization, and problem formation for metaheuristics, world-renowned authors give readers in-depth understanding of the full spectrum of algorithms and techniques. Scientists, researchers, academicians, and practitioners who are interested in optimizing a process or procedure to achieve a goal will benefit from the case studies of real-world applications from different domains.

The book takes a much-needed holistic approach, putting the most widely used metaheuristic algorithms together with an in-depth treatise on multi-disciplinary applications of metaheuristics. Each algorithm is thoroughly analyzed to observe its behavior, providing a detailed tutorial on how to solve problems using metaheuristics. New case studies and research problem statements are also discussed, which will help researchers in their application of the concepts.

  • Presented by world-renowned researchers and practitioners in metaheuristics
  • Includes techniques, algorithms, and applications based on real-world case studies
  • Presents the methodology for formulating optimization problems for metaheuristics
  • Provides readers with methods for analyzing and tuning the performance of a metaheuristic, as well as for integrating metaheuristics in other AI techniques
  • Features online complementary source code from the applications and algorithms

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Yes, you can access Comprehensive Metaheuristics by Seyedali Mirjalili,Seyedali Mirjalili,Amir Hossein Gandomi,Ali Mirjalili in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributors
  6. Chapter 1: Chaos theory in metaheuristics
  7. Chapter 2: Metaheuristic approaches for solving multiobjective optimization problems
  8. Chapter 3: A brief overview of physics-inspired metaheuristics
  9. Chapter 4: Evolutionary computation techniques for optimal response actions against water distribution networks contamination
  10. Chapter 5: Metaheuristic technique for solving fuzzy nonlinear equations
  11. Chapter 6: Metaheuristic algorithms in network intrusion detection
  12. Chapter 7: Metaheuristic algorithms in text clustering
  13. Chapter 8: Application of metaheuristic algorithms in optimal design of sewer collection systems
  14. Chapter 9: Space truss structures’ optimization using metaheuristic optimization algorithms
  15. Chapter 10: Metaheuristics for solving the wind turbine placement problem
  16. Chapter 11: Use of metaheuristics in industrial development and their future perspectives
  17. Chapter 12: LĂ©vy flight and Chaos theory based metaheuristics for grayscale image thresholding
  18. Chapter 13: Metaheuristics for optimal feature selection in high-dimensional datasets
  19. Chapter 14: Optimal deployment of sensors for leakage detection in water distribution systems using metaheuristics
  20. Chapter 15: Metaheuristic-based automatic generation controller in interconnected power systems with renewable energy sources
  21. Chapter 16: Route optimization in MANET using swarm intelligence algorithm
  22. Chapter 17: The promise of metaheuristic algorithms for efficient operation of a highly complex power system
  23. Chapter 18: Genome sequence assembly using metaheuristics
  24. Chapter 19: Metaheuristics for optimizing weights in neural networks
  25. Chapter 20: Metaheuristics for clustering problems
  26. Chapter 21: Employment of bio-inspired algorithms in the field of antenna array optimization: A review
  27. Chapter 22: Foundations of combinatorial optimization, heuristics, and metaheuristics
  28. Index