Grana - Information Processing with Evolutionary Algorithms (Springer, 2005).pdf - AI, Pattern matching, Data Modelling & Analysis - Yohoho25

Advanced Information and Knowledge Processing

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Manuel Gra˜a, Richard Duro, Alicia d’Anjou

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Information Processing

with Evolutionary

Algorithms

From Industrial Applications to Academic Speculations

With 137 Figures

Manuel Gra˜a, BSc, MSc, PhD

Universidad del Pais Vasco, San Sebastian, Spain

Richard J. Duro, BSc, MSc, PhD

Universidad da Coru˜a, La Coru˜a, Spain

Alicia d’Anjou, BSc, MSc, PhD

Universidad del Pais Vasco, San Sebastian, Spain

Paul P. Wang, PhD

Duke University, Durham, North Carolina, USA

Series Editors

Xindong Wu

Lakhmi Jain

British Library Cataloguing in Publication Data

Information processing with evolutionary algorithms : from

industrial applications to academic speculations. —

(Advanced information and knowledge processing)

1. Evolutionary computation 2. Computer algorithms

I. Gra˜a, Manuel

005.1

ISBN 1852338660

Library of Congress Cataloging-in-Publication Data

Information processing with evolutionary algorithms : from industrial applications to

academic speculations / Manuel Gra˜a ... [et al.].

p. cm. — (Advanced information and knowledge processing)

ISBN 1-85233-866-0 (alk. paper)

1. Evolutionary programming (Computer science) 2. Genetic algorithms. 3. Electronic

data processing. I. Gra˜a, Manuel, 1958– II. Series.

QA76.618.I56 2004

006.3 ′ 36—dc22

2004059333

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under

the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in

any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic

reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries con-

cerning reproduction outside those terms should be sent to the publishers.

AI&KP ISSN 1610-3947

ISBN 1-85233-866-0 Springer London Berlin Heidelberg

Springer Science

Springer-Verlag London Limited 2005

The use of 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 laws and regulations and therefore free for general use.

The publisher makes no representation, express or implied, with regard to the accuracy of the information con-

tained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be

made.

Typesetting: Electronic text files prepared by authors

Printed and bound in the United States of America

34/3830-543210 Printed on acid-free paper SPIN 10984611

Business Media

springeronline.com

Preface

Thelastdecadeofthe20thcenturyhaswitnessedasurgeofinterestinnumer-

ical, computation-intensive approaches to information processing. The lines

thatdrawtheboundariesamongstatistics,optimization,articialintelligence

andinformationprocessing aredisappearing,and itisnotuncommontond

well-founded and sophisticated mathematical approaches in application do-

mains traditionally associated with ad-hoc programming. Heuristics has be-

comeabranchofoptimizationandstatistics.Clusteringisappliedtoanalyze

soft data and to provide fast indexing in the World Wide Web. Non-trivial

matrixalgebrais atthe heartof thelast advancesincomputer vision.

Thebreakthroughimpulse was,apparently,dueto theriseof theinterest

inarticialneural networks, afterits rediscovery inthe late 1980s.Disguised

as ANN, numerical and statistical methods made an appearance in the in-

formation processing scene, and others followed. A key component in many

intelligentcomputationalprocessingisthesearchforanoptimalvalueofsome

function.Sometimes,thisfunctionisnotevidentanditmustbemadeexplicit

inordertoformulatetheproblemasanoptimizationproblem.Thesearch of-

tentakesplaceinhigh-dimensionalspacesthatcanbeeitherdiscrete,orcon-

tinuousormixed.Theshapeofthehigh-dimensionalsurfacethatcorresponds

totheoptimizedfunctionisusuallyverycomplex.Evolutionaryalgorithmsare

increasinglybeingappliedtoinformationprocessingapplicationsthatrequire

anykindofoptimization.Theyprovideasystematicandintuitiveframework

to state the optimization problems, and an already well-established body of

theorythat endorses theirgood mathematical properties. Evolutionary algo-

rithms have reached the status of problem-solving tools in the backpack of

theengineer.However,therearestillexcitingnewdevelopmentstakingplace

intheacademiccommunity.Thedrivingideaintheorganizationofthiscom-

pilationistheemphasisinthecontrastbetweenalreadyacceptedengineering

practiceand ongoing explorationsinthe academic community.

After the seminal works of Holland, Goldberg and Schwefel, the eld of

evolutionaryalgorithmshasexperiencedanexplosionofbothresearchersand

publicationsinboththeapplication-orientedandthefundamentalissues.Itis

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