Genetic Algorithm by Sivanathan and Deepa
Introduction to Genetic Algorithms
S.N.Sivanandam · S.N.Deepa
Introduction to Genetic Algorithms
With 193 Figures and 13 Tables
Authors
S.N.Sivanandam Professor and Head Dept. of Computer Science and Engineering PSG College of Technology Coimbatore - 641 004 TN, India S.N.Deepa Ph.D Scholar Dept. of Computer Science and Engineering PSG College of Technology Coimbatore - 641 004 TN, India
Library of Congress Control Number: 2007930221
ISBN 978-3-540-73189-4 Springer Berlin Heidelberg New York
This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable for prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springer.com c Springer-Verlag Berlin Heidelberg 2008 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: Integra Software Services Pvt. Ltd., India Cover design: Erich Kirchner, Heidelberg Printed on acid-free paper SPIN: 12053230 89/3180/Integra 5 4 3 2 1 0
Preface
The origin of evolutionary algorithms was an attempt to mimic some of the processes taking place in natural evolution. Although the details of biological evolution are not completely understood (even nowadays), there exist some points supported by strong experimental evidence: • Evolution is a process operating over chromosomes rather
S.N.Sivanandam · S.N.Deepa
Introduction to Genetic Algorithms
With 193 Figures and 13 Tables
Authors
S.N.Sivanandam Professor and Head Dept. of Computer Science and Engineering PSG College of Technology Coimbatore - 641 004 TN, India S.N.Deepa Ph.D Scholar Dept. of Computer Science and Engineering PSG College of Technology Coimbatore - 641 004 TN, India
Library of Congress Control Number: 2007930221
ISBN 978-3-540-73189-4 Springer Berlin Heidelberg New York
This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable for prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springer.com c Springer-Verlag Berlin Heidelberg 2008 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: Integra Software Services Pvt. Ltd., India Cover design: Erich Kirchner, Heidelberg Printed on acid-free paper SPIN: 12053230 89/3180/Integra 5 4 3 2 1 0
Preface
The origin of evolutionary algorithms was an attempt to mimic some of the processes taking place in natural evolution. Although the details of biological evolution are not completely understood (even nowadays), there exist some points supported by strong experimental evidence: • Evolution is a process operating over chromosomes rather