Multiple Criteria Decision Making: Proceedings of a Conference Jouy-en-Josas, France May 21–23, 1975

419 Pages·1976·9.518 MB·English-French

by  Bernard Roy (auth.), Hervé Thiriez, Stanley Zionts (eds.)

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continuation on page 411
Lecture Notes
in Economics and
Mathematical Systems
Managing Editors: M. Beckmann and H. P. KUnzi
Operations Research
130
Multiple Criteria Decision Making
Proceedings of a Conference
Jouy-en-Josas, France
May 21-23, 1975
Jointly sponsored by:
Centre d'Enseignement Superieur des Affaires (C.E.S.A.)
and European Institute for Advanced Studies
in Management (E.I.A.S.M.)
Edited by H. Thiriez and S. Zionts
Springer-Verlag
Berlin Heidelberg GmbH 1976
Editorial Board
H. Albach · A. V. Balakrishnan · M. Beckmann (Managing Editor)
P. Dhrymes · J. Green · W. Hildenbrand · W. Krelle
H. P. Kunzi (Managing Editor) · K. Ritter · R. Sato · H. Schelbert
P. Schănfeld
Managing Editors
Prof. Dr. M. Beckmann Prof. Dr. H. P. Ki.inzi
Brown University Universităt Zi.irich
Providence, Rl 02912/USA 8090 Zurich/Schweiz
Editors
Herve Thiriez
Chambre de Commerce et d'lndustrie de Paris
Centre d'Enseignement Superieur des Affaires
78350 Jouy-en-Josas/France
Stanley Zionts
State University of New York at Buffalo
School of Management
Buffalo, N. Y. 14214/USA
Library of Congress Cataloging in Publication Data
Conference on Multiple Cri teria Decision-Making, Jouy-en
Josas, France, 1975.
Multiple criteria decision-ma.king.
(Lecture notes in economica and mathematical systems
130)
Includea bibliographical references and index.
1. Decision-ma.king--Mathematical models--Congresses.
I. Thiriez, Herve, 1944- IL Zionts, Stanley,
1937- III. Centre d' enseignement supE!rieur des
af:faires. IV. European Institute for Advanced Studies
in Management. JI. Title. VI. Series.
HD69.D4C597 1975 658.4'03 76-24791
AMS Subject Classifications (1970): 90A05, 90A15
ISBN 978-3-540-07794-7 ISBN 978-3-642-87563-2 (eBook)
DOI 10.1007/978-3-642-87563-2
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© by Springer-Verlag Berlin Heidelberg 1976
Originally published by Springer-Verlag Berlin · Heidelberg in 1976
PREFACE
The conference was organized in order to assemble a group of researchers and
practitioners in the area of Multiple Criteria Decision Making. The purpose was
to discuss the current state of the art with respect to both theory and practice.
This conference considered such points as recent t_heoretical developments in terms
of models, the behavioral aspects of multiple criteria decision making, as well as
practical applications already realized and 1n progress. In addition, there was
interest in the problems of implementation of multiple-criteria methods, and the
interface between theory and practice,
Approximately 78 participants from 15 different countries attended the
conference - both theorists and practitioners. A list of participants and their
addresses is found on page 411 • Because of the relatively large number of
papers presented, large morning sessions followed by smaller parallel afternoon
sessions were employed'. In general a discussant commented on each paper. In
addition, considerable time was reserved for small-group discussion and interaction.
In addition to expressing our gratitude to the participants for their
enthusiastic reception and participation in the conference, we want. to thank
particularly the speakers, session chairmen and discussants. We also wish to
thank the C.E.S.A. and the European Institute for their support, as well as Mrs.
Randee Pomerantz and Miss Dina Nagler.~oth of the E.I.A.S.M.,for their active role
in the organization and arrangements for the conference, and Mrs. Jessie Goveas,
E.I.A.S.M. for typing the conference proceedings.
31 November, 1975. Herve Thiriez
Stanley Zionts
TABLE OF CONTENTS
BERNARD ROY
From Optimisation to Multi-Criteria Decision
Aid: Three Main Operational Attitudes
JOHAN PHILIP
An Algorithm for Combined Quadratic and
Multiobjective Programming 35
PIERRE HANSEN, MARTINE ANCIAUX-MUNDELEER and PHILIPPE VINCKE
Quasi-Kernels of Outranking Relations 53
HEINZ ISERMANN
Existence and Duality in Multiple
Objective Linear Programming 64
V. JOSEPH BOWMAN Jr.
On the Relationship of the Tchebycheff
Norm and the Efficient Frontier of
Multiple-Criteria Objectives 76
BERNARD BEREANU
Large Group Decision Making with Multiple
Criteria 87
HERV£ THIRIEZ and DANIEL HOURI
Multi-Person Multi-Criteria Decision
Making: A Sample Approach 103
RAINER HASENAUER
Theoretical Analysis and Empirical Application
of Goal Programming with Preemptive Priority Structures 120
S.L. SCHWARTZ, I. VERTINSKY and W.T. ZIEMBA
R&D Project Selection Behavior:
Study Designs and some Pilot Results 136
W.L. PRICE
An Interactive Objective Function Generator
for Goal Programmes 147
RALPH E. STEUER
A Five Phase Procedure for Implementing
a Vector-Maximum Algorithm for Multiple
Objective Linear Programming Problems 159
JEREMY F. SHAPIRO
Multiple Criteria Public Investment Decision Making
by Mixed Integer Programming 170
BERTIL TELL
A Comparative Study of Four Multiple-Criteria
Methods 183
WILLIAM K. BRAUERS
Multiple-Criteria Decision Making with a
Special Application on Defense Problems 199
VI
TOM TOGSVERD
Multi-Level Planning in the Public Secto~ 201
G. FANDEL and J. WiLHELM
Rational Solution Principles and Information
Requirements as Elements of a Theory of
Multiple Criteria Decision Making 215
JEAN-LOUIS GOFFIN and ALAIN HAURIE
Pareto Optimality with Nondifferentiable
Cost Functions 2]2
GEORGES HIRSCH
The Notion of Characteristic Set and Its Implication
for the Analysis and Development of Multicriterion
Methods 247
L.F. PAU
Two-Level Planning with Conflicting Goals 263
BOND SCHIEMENZ
Possibilities to Consider Multiple Criteria
in Decision Situations 274
RALPH L. KEENEY
Quantifying Corporate Preferences for Policy
Analysis 293
JACQUES BOEBION and LUCAS PUN
A Series-Parallel Multiple-Criteria Model
for a Scheduling Problem in the Dress-Making Industry 305
JYRKI WALLENIUS and STANLEY ZIONTS
Some Tests of an Interactive Programming Method for
Multicriterion Optimization and an Attempt
at Implementation 319
TOM HEMMING
A New Method for Interactive Multiobjectiye Optimization:
A Boundary Point Ranking Method 333
PHILIPPE VINCKE
A New Approach to Multiple Criteria Decision-Making 341
J.W.C. TOMLINSON and I. VERTINSKY
Selecting a Strategy for Joint Ventures in
Fisheries: A First Approximation 351
A.R. CHARPENTIER and E. JACQUET-LAGRtZE
La Promotion de l'electricite dans l'industrie
et l'utilisation de methodes multicriteres 364
S.L.SCHWARTZ, I. VERTINSKY, W.T. ZIEMBA and M. BERNSTEIN
Some Behavioural Aspects of Information Use in
Decision Making: A Study of Clinical Judgements 378
P.W. SIZER
A Behavioural Model of Company Development 392
PROGRAM 402
LIST OF PARTICIPANTS 405
FROM OPTIMISATION TO MULTICRITERIA DECISION AID:
THREE MAIN OPERATIONAL ATTITUDES
*
Bernard Roy
* Universite de Paris IX, Conseiller Scientifique a la SEMA, France
ABSTRACT
The intent of this paper is to develop a conceptual framework for a normative
theory of "decision-aid". Here the word normative does not apply to the decision
maker, for whom aid is provided, but to the scientist and to his work of analysis
and modelling. This framework is appropriate to multicriteria problems dealing
with either fixed or evolutive sets of potential actions not necessarily pairwise
incompatible. The classical optimization on a fixed set of exclusive actions is
included as a particular case.
Amongst others, the concepts of a consistent family of criteria, pure
criteria, precriteria, quasi-criteria or pseudo-criteria are introduced. Reasons
for which multicriteria decision aid may not fit in with the assessment of a
unique criterion are discussed. Several situations callinR for modelling of global
preferences so as to "extract" "good" actions from a given set, otherwise than by
optimizing a value function, are considered. Finally, a new interactive procedure
called "evolutive target procedure" leading to compromise facing n conflicting
criteria and flexible constraints is proposed.
1. PRELIMINARIES
The notions of Model, Decision Maker and Decision Aid warrant several preliminary
precisions so as to avoid any misunderstanding of their meaning within the course of
this paper.
At the start, every data collecting activity is founded on preconceived ideas
which frequently bring to light others, all playing the role of raw materials
for a more or less formalised structure, which presents itself as the interface
between concrete phenomena and abstract reasoning: this is precisely the model. It
occupies a central position, in so far as it conditions the data collection and
directs the deduction.
It is even so outside of all mathematical formalisation. Consider, for
example, a discussion about the decentralisation of a factory. Suppose that one of
the interlocutors brings to light, in connection with a particular site, the absence
of qualified manpower in the area, and the difficulty of dispatching finished and
semi-finished goods. If he concludes that these reasons alone are sufficient to
reject a priori this site~ this implies that by reference to a formalised or non
formalised model, he is convinced that these inconveniences are of such imp0rtance
2
that they cannot be counterbalanced by all the advantages, no matter how great they
are. In another sphere, consider the case of so~eone responsible for desir-ning a
questionnaire to be completed before allowing credit. Neglecting a certain aspect,
or contrarily treating another with caution, whilst formulating the questions
within the given terms, has hardly no meaning outside a schema establishing the
relations, although imprecise, between the reality and the replies which can be made
to these questions. As for the deductions made by anyone charged with a study of
the dossier, taking into account the replies made to these questions, it is quite
clear that they can only be used within the framework of an even more complex
model.
Whoever conducts an analysis destined to acquire an organised vision of
a class of phenomena, whether the aim is to build a formal representation delibera
tely left implicit, must consider a multitude of choices, often delicate, which
require a deep understanding of the concept of a model, and the ties between models
and reality.
A model can be defined as a schema which, for_ a field of questions, is taken
as an abstract representation of a category of phenomena, more or less skillfully
disengaged from their original context. For dominating interaction between analysis,
modelling and decision aid, it is essential to have this definition in mind.
As a resume, I will say that decision aid has for objective, by means of
more or less formalised models, to improve the control (this word having its
cybernetical connotation} of the decision process. To improve in this context
signifies to increase the coherence between the different objectives intervening
in the process just in that they shall be reached; this presumes amongst other
things to clarify the antagonisms and to find solutions which exceed them. ill this
perspective modelling has firstly a passive role in helping to comprehend, by
mastering the various possibilities, and by reflections it gives to pre-existing
preferences, and secondly an active role in the sense that the model contributes to
forming and evolving the preferances of the different actors on stage so as to
make acceptable or discover possibilities previously refused or not considered.
Whenever a decision making problem comes on stage, it 1s understood that there
is a decision maker, for whom the scientist is working, waiting in the wings. To
say that there is a decision aid intimates that the objective of this work is to shed
light on the decision and not to fix it and, by that, to suppress all tre activity
and free will of the decision maker. Finally, between the scientist and the decision
maker (whom the scientist never, so to speak, meets), it is convenient to introduce
a third person, almost always present, whom I will call the "demander". Generally it
is he who poses the problem, and who is confused at times, but wrongly, with the
decision maker, for it is he who commands and finally judges the report.
3
It is well to bear in mind that a decision is very rarely the reflection of
preferences of an isolated man, nor even of a well defined group of people. In the
factory siting example given above, the managing director will, in general, be
obliged to consider governmental preferences or even the pressure of public opinion.
Similarly, the person who accepts or rejects a demand for credit is often influenced
by the impression his subordinates may have of the client who asks for credit, never
the less trying to conform to the company's policy for this type of service. The
decision is an important stage in the evolution of a process and providing decision
aid means to take part in this process. This implies the identification of the one
among those actors who play a terminating role in the achievement of the process and
for whom or in whose name decision aid is provided. In my eyes it is this, more or
less circled entity, which covers the concept of the decision maker.
It must be stressed that above all it is the demander's duty to furnish the
scientist with the means of acquiring as good an understanding as possible, within
the framework of the available means, of the class of phenomena and question field.
In particular it is up to him not to imprison the scientist by an ill-defined pro
blem, i.e. an out of context problem or one formulated in such a way that it cannot
be incorporated in the decision process. The model, no matter how life-like it is,
is never the reality but a substitute only appropriate to a specific field of ques
tions, about which it is destined to give an insight, or rather an idea, by studying
such a fragment of reality, this latter remaining always merely coftnlex and broader.
To be aware of the reality in its essential aspects, to isolate the correct fragment
with respect to the question field, it is necessary to have a just and exhaustive
perception. In this, the intermediary the demander plays a determining role.
Finally the scientist's function is to build the model and to draw from it
conclusions intelligible to the decision maker and susceptible to orient his
actions. His success in this depends very much on the way in which in relation to
the demander, he defines the set of potential actions, refines the problem formula
tion, models and selects appro~riate criteria and finally chooses the operational
attitude according to the three stages of modelling described in Table 1. It is not
uncommon that, having reached stage III, the scientist is led to modify work pre
viously accomplished in stage I and stage II, either because his first deductions
incite him to do it, or that he places himself at a different level of insertion in
the decision process.
Part 1 and part 2 introduce a certain number of fundamental concepts res
pectively related to the stages I and II; part 3 is devoted to a central concept
in multicriteria decision aid that of consistent family of criteria. Part 4
finally is a short guide line to help the scientist in answering questions such as
the following. Will he progress from the set A embracing the only feasible ex
clusive actions to a statement of the "best" action or of a group of dominating
actions? If the particular formulation chosen (for example in the credit demand)