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Yang, X: Nature-Inspired Metaheuristic Algorithms

By Xin-She Yang

Yang, X: Nature-Inspired Metaheuristic Algorithms

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Description
Modern metaheuristic algorithms such as particle swarm optimization and cuckoo search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms for global optimization, including ant and bee algorithms, bat algorithm, cuckoo search, differential evolution, firefly algorithm, genetic algorithms, harmony search, particle swarm optimization, simulated annealing and support vector machines. In this revised edition, we also include how to deal with nonlinear constraints. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course as well as for self study. As some of the algorithms such as the cuckoo search and firefly algorithms are at the forefront of current research, this book can also serve as a reference for researchers.
Product details
Binding:
Paperback
Edition:
2
Number of Pages:
160
Release Date:
2010-07-01
Publication Date:
2010-07-01
Publisher:
LUNIVER PR
Languages:
Published: English, Original: English
ISBN10:
1905986289
ISBN13:
9781905986286
Weight:
231 g
Height:
154 cm
Width:
236 cm
Thickness:
18 cm
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The items bear minimal signs of past use, such as light scratches or memories in the form of markings. These signs of wear give the items a charming character and tell stories of their previous owners, while not affecting their functionality.
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