Chapman and Hall/CRC
280 pages | 125 B/W Illus.
Nature Inspired Optimization Algorithms is a comprehensive book on the most popular optimization algorithms that are based on nature. It starts with an overview of optimization and goes from the classical to the latest swarm intelligence algorithm. Nature has a rich abundance of flora and fauna that inspired the development of nature inspired optimization techniques. The study of the intelligent survival strategies of animals, birds and insects in a hostile and ever-changing environment has led to the development of techniques emulating their behaviour. Nature provides us with simple solutions to complex problems in an effective and adaptive manner.
This book is a valuable resource for engineers, researchers, faculty and students who are devising optimum solutions to any type of problem. The problems range from computer science to economics covering diverse areas that require maximizing output and minimizing resources and this is the crux of all optimization algorithms. The book is a lucid description of fifteen of the existing important optimization algorithms that are based on swarm intelligence and superior in performance.
This book is a reference for under-graduate and post-graduate students. It will be useful to faculty members teaching the subject on optimization. It also a comprehensive guide for researchers who are looking for optimizing resources in attaining the best solution to a problem. The nature inspired optimization algorithms are unconventional and this makes them more efficient than their traditional counterparts.
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.