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Synopsis
Evolutionary Algorithms-Volume 9 by Alain Petrowski, Sana Ben-Hamida, 9781848218048, John Wiley
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Review
In general, Petrowski and Ben-Hamid display an in-depth understanding of several
optimization classes and their corresponding evolutionary algorithms, along with an
impressive ability to explain, illustrate, motivate, classify and codify. Although nobody
can "do it all" in a field as deep and wide as evolutionary computation, they have chosen
a pertinent subset and done a fine job with it. My own copy of "Evolutionary Algorithms"
became an instant go-to reference as I prepare for another semester of teaching.
( Genetic Programming and Evolvable Machines, December 2018)
About the Author
Alain PETROWSKI is Associate Professor in the Department of Networks and Mobile Multimedia Services at the Telecom-SudParis, Institut Mines-Telecom, Paris-Saclay University, France. His main research interests are related to optimization, metaheuristics and machine learning.
"About this title" may belong to another edition of this title.
- PublisherWiley-ISTE
- Publication date2017
- ISBN 10 1848218044
- ISBN 13 9781848218048
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages256
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Evolutionary Algorithms
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Evolutionary Algorithms (Computer Engineering: Metaheuristics, 9)
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Evolutionary Algorithms
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Evolutionary Algorithms (Hardcover)
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ISTE Ltd and John Wiley & Sons Inc, London, 2017
ISBN 10: 1848218044
ISBN 13: 9781848218048
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Hardcover. Condition: new. Hardcover. Evolutionary algorithms are bio-inspired algorithms based on Darwins theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning. Evolutionary algorithms are bio-inspired algorithms based on Darwin s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781848218048
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Evolutionary Algorithms: An Overview
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Hardcover. Condition: Brand New. 236 pages. 9.50x6.25x0.75 inches. In Stock. This item is printed on demand. Seller Inventory # __1848218044
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