Multiattribute Group Decision-Making Methods with Intuitionistic Fuzzy Sets
In the preceding Chap. 3, we developed some effective multiattribute decision-making methods with intuitionistic fuzzy sets such as the linear weighted averaging method, TOPSIS, optimum seeking method, LINMAP, and fraction mathematical programming method
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Deng-Feng Li
Decision and Game Theory in Management with Intuitionistic Fuzzy Sets
Studies in Fuzziness and Soft Computing Volume 308
Series Editor J. Kacprzyk, Warsaw, Poland
For further volumes: http://www.springer.com/series/2941
Deng-Feng Li
Decision and Game Theory in Management with Intuitionistic Fuzzy Sets
123
Deng-Feng Li Fuzhou People’s Republic of China
ISSN 1434-9922 ISBN 978-3-642-40711-6 DOI 10.1007/978-3-642-40712-3
ISSN 1860-0808 (electronic) ISBN 978-3-642-40712-3 (eBook)
Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2013948365 Springer-Verlag Berlin Heidelberg 2014 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)
To my wife, Wei Fei and to my son, Wei-Long Li
Foreword
Fuzzy decision and game theory have been extensively studied and achieved great success in the last two or three decades. The fuzzy set theory introduced by L. A. Zadeh in 1965 is an important tool to deal with fuzziness appearing in management decision and game problems. The concept of fuzzy sets is a cornerstone of the fuzzy set theory. Zadeh used single index (i.e., membership degree or function) to define the fuzzy set. Namely, the single membership degree (or function) was used to express two opposite aspects (or states) of
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