Nature-Inspired Algorithms
eBook - ePub

Nature-Inspired Algorithms

For Engineers and Scientists

  1. 307 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Nature-Inspired Algorithms

For Engineers and Scientists

About this book

This comprehensive reference text discusses nature inspired algorithms and their applications. It presents the methodology to write new algorithms with the help of MATLAB programs and instructions for better understanding of concepts. It covers well-known algorithms including evolutionary algorithms, genetic algorithm, particle Swarm optimization and differential evolution, and recent approached including gray wolf optimization. A separate chapter discusses test case generation using techniques such as particle swarm optimization, genetic algorithm, and differential evolution algorithm.

The book-

  • Discusses in detail various nature inspired algorithms and their applications

  • Provides MATLAB programs for the corresponding algorithm

  • Presents methodology to write new algorithms

  • Examines well-known algorithms like the genetic algorithm, particle swarm optimization and differential evolution, and recent approaches like gray wolf optimization.

  • Provides conceptual linking of algorithms with theoretical concepts

The text will be useful for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering.

Discussing nature inspired algorithms and their applications in a single volume, this text will be useful as a reference text for graduate students in the field of electrical engineering, electronics engineering, computer science and engineering. It discusses important algorithms including deterministic algorithms, randomized algorithms, evolutionary algorithms, particle swarm optimization, big bang big crunch (BB-BC) algorithm, genetic algorithm and grey wolf optimization algorithm. "

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Yes, you can access Nature-Inspired Algorithms by Krishn Kumar Mishra in PDF and/or ePUB format, as well as other popular books in Mathematics & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title
  4. Copyright
  5. Contents
  6. Preface
  7. Acknowledgments
  8. About the Author
  9. Chapter 1 Introduction
  10. Chapter 2 Binary Genetic Algorithms
  11. Chapter 3 Real-Parameter Genetic Algorithm
  12. Chapter 4 Differential Evolution
  13. Chapter 5 Particle Swarm Optimization
  14. Chapter 6 Grey Wolf Optimization
  15. Chapter 7 Environmental Adaptation Method
  16. Chapter 8 Other Important Optimization Algorithms
  17. Chapter 9 Application of Genetic Algorithms, Partial Swarm Optimization, and Differential Evolution in Software Testing
  18. Chapter 10 Application of Genetic Algorithms, Partial Swarm Optimization, and Differential Evolution in Regression Testing
  19. Chapter 11 Application of Genetic Algorithms and Partial Swarm Optimization in Cloud Computing
  20. References and Further Reading
  21. Questions
  22. Answers
  23. Index