Fr. 206.00

Nature-Inspired Optimization Algorithms

English · Hardback

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Description

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The book is a lucid description of fifteen of the existing important optimization algorithms that are based on swarm intelligence and superior in performance. Nature has a rich abundance of flora and fauna that inspired the development of nature inspired optimization techniques

List of contents

1.Introduction 2. Classical Optimization Methods. 3. Nature inspired Algorithms. 4. Genetic Algorithm. 5. Genetic Programming. 6. Particle Swarm Optimization. 7. Differential Evolution 8. Ant Colony Optimization. 9. Bee Colony Optimization. 10. Fish School Search Optimization. 11. Cuckoo Search Algorithm 12. Firefly Algorithm. 13. Bat Algorithm. 14. Flower Pollination Algorithm. 15. Grey Wolf Optimization 16. Elephant Herding Algorithm. 17. Crow Search Algorithm. 18. Raven Roosting Optimization Algorithm 19. Applications 20. Conclusion.

About the author

Dr. Vasuki A is currently working as Professor in the Department of Mechatronics Engineering at Kumaraguru College of Technology, Coimbatore, India. She has more than 27 years of teaching, research and academic administration experience. She has completed B.E in Electronics and Communication Engineering from PSG College of Technology in 1989. She has completed her postgraduate degree M.E Applied Electronics from Coimbatore Institute of Technology in 1991. She has done her Ph.D in Image Compression from PSG College of Technology under Anna University Chennai in 2010. Her research interests are Signal Processing, Image Processing, Communication and Optimization. She has published 3 Book Chapters, 38 National and International Journal papers and 60 National and International Conference papers. She has guided 30 PG projects and 50 UG projects. She is an approved Research Supervisor under Anna University Chennai and is currently guiding 9 research scholars.

Summary

The book is a lucid description of fifteen of the existing important optimization algorithms that are based on swarm intelligence and superior in performance. Nature has a rich abundance of flora and fauna that inspired the development of nature inspired optimization techniques

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