Multicriteria Decision Aid Classification Methods
The book discusses a new approach to the classification problem following the decision support orientation of multicriteria decision aid. The book reviews the existing research on the development of classification methods, investigating the corresponding
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Applied Optimization Volume 73 Series Editors: Panos M. Pardalos University of Florida, U.S.A. Donald Hearn University of Florida, U.S.A.
The titles published in this series are listed at the end of this volume.
Multicriteria Decision Aid Classification Methods by
Michael Doumpos and
Constantin Zopounidis Technical University of Crete, Department of Production Engineering and Management, Financial Engineering Laboratory, University Campus, Chania, Greece
KLUWER ACADEMIC PUBLISHERS NEW YORK, BOSTON, DORDRECHT, LONDON, MOSCOW
eBook ISBN: Print ISBN:
0-306-48105-7 1-4020-0805-8
©2004 Kluwer Academic Publishers New York, Boston, Dordrecht, London, Moscow Print ©2002 Kluwer Academic Publishers Dordrecht All rights reserved No part of this eBook may be reproduced or transmitted in any form or by any means, electronic, mechanical, recording, or otherwise, without written consent from the Publisher Created in the United States of America Visit Kluwer Online at: and Kluwer's eBookstore at:
http://kluweronline.com http://ebooks.kluweronline.com
To my parents Christos and Aikaterini Doumpos To my wife Kleanthi Koukouraki and my son Dimitrios Zopounidis
Table of contents
PROLOGUE
xi
CHAPTER 1: INTRODUCTION TO THE CLASSIFICATION PROBLEM 1. 2. 3. 4.
Decision making problematics The classification problem General outline of classification methods The proposed methodological approach and the objectives of the book
1 4 6
10
CHAPTER 2: REVIEW OF CLASSIFICATION TECHNIQUES 1. Introduction 2. Statistical and econometric techniques 2.1 Discriminant analysis 2.2 Logit and probit analysis 3. Non-parametric techniques 3.1 Neural networks 3.2 Machine learning 3.3 Fuzzy set theory 3.4 Rough sets
15 15 16 20 24 24 27 30 32
CHAPTER 3: MULTICRITERIA DECISION AID CLASSIFICATION TECHNIQUES 1. Introduction to multicriteria decision aid 1.1 Objectives and general framework 1.2 Brief historical review 1.3 Basic concepts 2. Methodological approaches 2.1 Multiobjective mathematical programming 2.2 Multiattribute utility theory
39 39 40 41 43 45 48
viii 2.3 Outranking relation theory 2.4 Preference disaggregation analysis 3. MCDA techniques for classification problems 3.1 Techniques based on the direct interrogation of the decision maker 3.1.1 The AHP method 3.1.2 The ELECTRE TRI method 3.1.3 Other outranking classification methods 3.2 The preference disaggregation paradigm in classification problems
50 52 55 55 55 59 64 66
CHAPTER 4: PREFERENCE DISAGGREGATION CLASSIFICATION METHODS 1. Introduction 2. The UTADIS method 2.1 Criteria aggregation model 2.2 Model development process 2.2.1 General framework 2.2.2 Mathematical formulation 2.3 Model development issues 2.3.1 The piece-wise linear modeling of marginal utilities 2.3.2 Uniqueness of solutions 3. The multi-group hierarchical discrimination method (MHDIS) 3.1 Outline and main characteristics 3.2 The hierarchical discrimination process 3.3 Estimation of utility functions 3.4 Model extrapolation Appendix: Post optimality techniques for classification model development in
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