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Foundations of Generic Optimization: Volume 1: A Combinatorial Approach to Epistasis: Mathematical Modelling: Theory and Applications, cartea 20

Autor M. Iglesias Editat de R. Lowen Autor B. Naudts Editat de A. Verschoren Autor C. Vidal
en Limba Engleză Hardback – 6 iul 2005

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Specificații

ISBN-13: 9781402036668
ISBN-10: 1402036663
Pagini: 296
Ilustrații: XIII, 298 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 1.02 kg
Ediția:2005
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Mathematical Modelling: Theory and Applications

Locul publicării:Dordrecht, Netherlands

Public țintă

Research

Cuprins

Genetic algorithms: a guide for absolute beginners.- Evolutionary algorithms and their theory.- Epistasis.- Examples.- Walsh transforms.- Multary epistasis.- Generalized Walsh transforms.

Recenzii

From the reviews:
"This book deals with combinatorial aspects of epistasis, especially normalized epistasis, a concept that exists in genetics and evolutionary algorithms. It starts with the theory of evolutionary algorithms. This illustrative introduction makes the book readable independent on other textbooks. … The book is very well written and presents many important and useful results. … It shows also that difficult practical problems can only be efficiently solved by a combination of Modelling, Mathematics and Computing." (Christian Posthoff, Zentralblatt MATH, Vol. 1108 (10), 2007)

Caracteristici

Only book dealing exclusively with the notion of epistasis in the framework of evelotionary algorithms and genetic algorithms in particular Completely self-contained (even includes a mathematical refresher intended for users with more computer science than math background) Chapter 0 is intended for neophytes in the field of genetic algorithms and optimization theory; it provides in a very readable way the basics of genetic algorithms Provides new questions (and answers) in the field between combinatorics and optimization theory, between discrete and mathematics and theoretical computer science, between linear algebra and complexity theory