Bionic Optimization in Structural Design Stochastically Based Method
The book provides suggestions on how to start using bionic optimization methods, including pseudo-code examples of each of the important approaches and outlines of how to improve them. The most efficient methods for accelerating the studies are discussed.
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Bionic Optimization in Structural Design Stochastically Based Methods to Improve the Performance of Parts and Assemblies
Bionic Optimization in Structural Design
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Rolf Steinbuch • Simon Gekeler Editors
Bionic Optimization in Structural Design Stochastically Based Methods to Improve the Performance of Parts and Assemblies
Editors Rolf Steinbuch Reutlingen University Reutlingen Germany
Simon Gekeler Reutlingen University Reutlingen Germany
ISBN 978-3-662-46595-0 ISBN 978-3-662-46596-7 DOI 10.1007/978-3-662-46596-7
(eBook)
Library of Congress Control Number: 2015955744 Springer Heidelberg New York Dordrecht London © Springer-Verlag Berlin Heidelberg 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer-Verlag GmbH (www.springer.com)
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Preface
Bionics has become more and more popular during the last few decades. Many engineering problems are now solved by copying solutions found in nature. Especially the broad field of optimization has been inspired by the variety of methods to accomplish tasks that can be observed in nature. Popularly known examples include the strategies that ant colonies use to reduce their transport distances to feed their always hungry population, the dynamics of swarms of birds or fishes, and even replication of the brain’s learning and adapting to different challenges. Over more than a decade, we have been studying Bionic Optimization at the Reutlingen Research Institute (RRI). After early attempts to design optimization solutions using parameterized CAD-systems and evolutionary strategies, our field of interest became broader. Our work taught us how the different bionic optimization strategies might be applied, which strong points and which weaknesses they exhibited, and where they might be powerful and where inappropriate. During a series of joint research projects with different partners and supported by the Germa
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