TY  - BOOK
AU  - Iglesias,M.
AU  - Naudts,B.
AU  - Verschoren,A.
AU  - Vidal,C.
AU  - Lowen,R.
AU  - Verschoren,A.
ED  - SpringerLink (Online service)
TI  - Foundations of Generic Optimization: Volume 1: A Combinatorial Approach to Epistasis 
T2  - Mathematical Modelling: Theory and Applications,
SN  - 9781402036651
U1  - 004.0151 23
PY  - 2005///
CY  - Dordrecht
PB  - Springer Netherlands
KW  - COMPUTER SCIENCE
KW  - COMPUTATIONAL COMPLEXITY
KW  - GENETICS
KW  - MATHEMATICS
KW  - COMBINATORICS
KW  - MATHEMATICAL OPTIMIZATION
KW  - MATHEMATICS OF COMPUTING
KW  - DISCRETE MATHEMATICS IN COMPUTER SCIENCE
KW  - GENETICS AND POPULATION DYNAMICS
KW  - OPTIMIZATION
N1  - Genetic algorithms: a guide for absolute beginners -- Evolutionary algorithms and their theory -- Epistasis -- Examples -- Walsh transforms -- Multary epistasis -- Generalized Walsh transforms
N2  - The success of a genetic algorithm when applied to an optimization problem depends upon several features present or absent in the problem to be solved, including the quality of the encoding of data, the geometric structure of the search space, deception or epistasis. This book deals essentially with the latter notion, presenting for the first time a complete state-of-the-art research on this notion, in a structured completely self-contained and methodical way. In particular, it contains a refresher on the linear algebra used in the text as well as an elementary introductory chapter on genetic algorithms aimed at readers unacquainted with this notion. In this way, the monograph aims to serve a broad audience consisting of graduate and advanced undergraduate students in mathematics and computer science, as well as researchers working in the domains of optimization, artificial intelligence, theoretical computer science, combinatorics and evolutionary algorithms
UR  - http://dx.doi.org/10.1007/1-4020-3665-5
ER  -