Evolutionary Optimization Algorithms
Dan Simon
Sold by THE SAINT BOOKSTORE, Southport, United Kingdom
AbeBooks Seller since June 14, 2006
New - Hardcover
Condition: New
Quantity: Over 20 available
Add to basketSold by THE SAINT BOOKSTORE, Southport, United Kingdom
AbeBooks Seller since June 14, 2006
Condition: New
Quantity: Over 20 available
Add to basketThis item is printed on demand. New copy - Usually dispatched within 5-9 working days 1210.
Seller Inventory # C9780470937419
A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms
Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies.
This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others.
Evolutionary Optimization Algorithms:
Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.
DAN SIMON is a Professor at Cleveland State University in the Department of Electrical and Computer Engineering. His teaching and research interests include control theory, computer intelligence, embedded systems, technical writing, and related subjects. He is the author of the book Optimal State Estimation (Wiley).
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