Handbook of Simulation Optimization
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advan
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Michael C. Fu Editor
Handbook of Simulation Optimization
International Series in Operations Research & Management Science Volume 216
Series Editor Camille C. Price Stephen F. Austin State University, TX, USA Associate Series Editor Joe Zhu Worcester Polytechnic Institute, MA, USA Founding Series Editor Frederick S. Hillier Stanford University, CA, USA
More information about this series at http://www.springer.com/series/6161
Michael C. Fu Editor
Handbook of Simulation Optimization
123
Editor Michael C. Fu University of Maryland College Park, MD, USA
ISSN 0884-8289 ISSN 2214-7934 (electronic) ISBN 978-1-4939-1383-1 ISBN 978-1-4939-1384-8 (eBook) DOI 10.1007/978-1-4939-1384-8 Springer New York Heidelberg Dordrecht London Library of Congress Control Number: 2014950046 © Springer Science+Business Media New York 2015 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. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. 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. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
Arguably, the two most powerful operations research/management science (OR/MS) techniques are simulation and optimization. Simulation in this book will refer to stochastic simulation, whereby there is randomness in the system, also known as Monte Carlo simulation. Optimization dates back many centuries and is generally considered the older of the two siblings. Both approaches were propelle
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