Iglesias / Lowen / Naudts Foundations of Generic Optimization

Volume 1: A Combinatorial Approach to Epistasis
1. Auflage 2006
ISBN: 978-1-4020-3665-1
Verlag: Springer Netherland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 20, 298 Seiten, eBook

Reihe: Mathematical Modelling: Theory and Applications

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.

Zielgruppe

Research

Autoren/Hrsg.

Iglesias, M.

Naudts, B.

Verschoren, A.

Vidal, C.

Lowen, R.

Inhaltsverzeichnis

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