Control in Transportation Systems 1986. Proceedings of the 5th IFAC/IFIP/IFORS Conference, Vienna, Austria, 8–11 July 1986

371 Pages·1987·33.45 MB·English

by  M. M. Etschmaier, T. Hasegawa, Robert Genser, H. Strobel

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CONTROL IN
TRANSPORTATION
SYSTEMS (1986)
Proceedings of the 5th IFACIIFIPIIFORS Conference
Vienna, Austria, 8—11 July 1986
Edited by
R. GENSER
Bundesministerium für öffentliche Wirtschaft und Verkehr,
Vienna, Austria
M. M. ETSCHMAIER
University of Lotoell, Lowell, MA, USA
T. HASEGAWA
Kyoto University, Kyoto, Japan
and
H. STROBEL
Hochschule für Verkehrswesen Friedrich List, Dresden, GDR
Published for the
INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL
by
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Copyright © 1987 IFAC
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First edition 1987
British Library Cataloguing in Publication Data
Control in transportation systems 1986: proceedings of the 5th IFAC/IFIP/IFORS
conference, Vienna, Austria, 8-11 July 1986—(IFAC Proceedings series; 1987, no. 6)
1. Transportation 2. Automatic control
1. Genser, R. II. International Federation of Automatic Control III. Series
380.5 HE336.A/
ISBN 0-08-033438-5
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The Editors
Printed in Great Britain by A. Wheaton &f Co. Ltd., Exeter
5TH IFAC/IFIP/IFORS CONFERENCE ON CONTROL IN
TRANSPORTATION SYSTEMS
Sponsored by
International Federation of Automatic Control (IFAC)
Technical Committee for Systems Engineering (SECOM)
Cosponsored by
IFAC Technical Committees of
Applications (APCOM)
Biomedical Engineering (BIOMED)
Computers (COMPUT)
Developing Countries (DECOM)
Education (EDCOM)
Economic and Management Systems (EMSCOM)
Manufacturing Technology (MANTECH)
International Federation for Information Processing (IFIP)
International Federation for Operational Research Societies (IFORS)
Organized by
Austrian Center for Productivity and Efficiency (ÖPWZ), Vienna
International Programme Committee
R. Genser, Austria (Chairman) H. Kopetz, Austria
A. Artynov, USSR M. Koshi, Japan
M. Cremer, FRG P. M. Larsen, Denmark
J . P. Crestin, France P. Martens, Belgium
H. J . De Norwall, Belgium Y. Ohno, Japan
W. D. Ehrenberger, FRG K. Pierick, FRG
H. V. Ellingsen, Norway P. Rabischong, France
M. M. Etschmaier, USA L. Skyva, Czechoslovakia
P. Faller, Austria K. Spera, Austria
R. E. Fenton, USA W. Schaufelberger, Switzerland
H. Frey, Switzerland G. Schweizer, FRG
A. Hmamed, MA B . J . Sterner, Sweden
T. Hasegawa, Japan A. Straszak, Poland
J . J . Henry, France H. Strobel, GDR
G. Johannsen, FRG D. Tabak, Israel
H. Knoflacher, Austria
P. Kopacek, Austria
National Organizing Committee
P. Kopacek (Chairman)
J . Hähnel (Secretary)
G. Becker
R. Genser
M. Horvath
W. Stejskal
Copyright © IFAC Control in Transportation
Systems, Vienna, Austria, 1986
PREFACE
The fifth of a series of conferences by was also recognized in the interface bet-
the international federations on Automatic ween the human and the various machines
Control (IFAC), Information Processing and facilities used in transportation.
(IFIP), and Operational Research Societies Specifically, it was concluded that users
(IFORS) was held on July 8 - 1 1 , 1986 in and operators of transportation systems
Vienna, Austria. 110 delegates from a to- are often not considered adequately. It
tal of 23 countries met to discuss a broad was suggested that the sponsor organiza-
range of topics. tions of the conference might be in a po-
sition to fill the void, as is already
In addition to the challenges and opportu- done through the IFAC Workshops on Safe
nities posed by the rapid developments in Computer Systems (Safecomp).
microelectronics and information techno-
logies, the subject of national transporta- The use of robotics in transportation is
tion systems planning was given particular seen to be concentrated in the manufacture
attention. One of the motivating factors of equipment. Only to a limited extent is
for emphasizing the subject of national robotics being used in maintenance. A con
transportation systems planning is the siderable potential for the application of
fact that the General Transportation Sy- robotics is recognized in the operational
stems Plan of the host country, Austria, area of a transportation system. The fea-
is now in its final phase of development. tures of a robot considered most important
The plan has reached a state in which in- in such applications are mobility and the
teresting results could be reported in the ability to recognize visual images.
form of a case study and of several indi-
vidual research reports. Reports on simi- At the round table on the use of Videotex
lar endeavors completed or under way in (BTX) for logistics and passenger services
other countries were sollicited by the In- it was pointed out that mulitfunctional
ternational Program Committee to round out use of infrastructure already available
the discussions. Also sollicited were re- might be more beneficial than new systems
ports on more limited projects of model- which, even at large expense, would offer
ling for management and decision making less access than does the available infra-
regarding environmental, social, and eco- structure. Also, it was suggested that,
nomic aspects of transportation systems. even if videotex systems are designed in a
Survey papers and round table discussions user-friendly manner, infrequent users or
were organized to illustrate the potential users with more complicated needs might
benefits which transportation community not be able to use the system entirely on
can derive from such fields as logistics, their own. Hierarchies of systems might
robotics, and telecommunications. be used to maintain the role of the trans-
portation professional as an intermediary
The view of logistics suggests that for a to the user in these situations.
shipper transportation efficiency is secon-
dary as an objective to the overall effi- The presentation of a psychologist working
ciency of the logistics system. Conver- in the field of highway safety showed the
sely, it may not be possible to justify limitations of learning and training. In
expensive new transportation systems un- the subsequent discussion it was pointed
less the shippers can be motivated to out that electronic equipment already
change their logisitcs system so that they available might be used to a greater ex-
can take best advantage of the opportuni- tent to make traffic more safe and human.
ties it presents. Similarly, a shippers
needs are rarely satisfied by just one The emphasis of the series of conferences
transportation link or one mode of trans- on control in transportation has been on
portation. A mulit-modal approach to the transfer of knowledge about transpor-
transportation is therefore called for. tation between researchers and developers,
and between users and scientists. This
conference points at the great need for
Standardization is recognized as an im- further work.
portant prerequisite for effective multi-
modal transportation. While in the past
M.M. Etschmaier
standardization efforts were mostly direc-
R. Genser
ted towards physical aspects of the modal
T. Hasegawa
interfaces, the current need is seen most-
H. Strobel
ly in the areas of information processing
and informatics. A lack of standardization Editors
vi
Copyright IQ 1FAC Control in Transportation TUTORIAL
Systems, Vienna, Austria, 1986
INTERACTIVE ALTERNATIVE ORIENTED
DECISION SUPPORT SYSTEM FOR
COMMITTEE DECISION MAKING
A. Lewandowski
International Institute for Applied Systems Analysis, Laxenburg, Austria
Abstract. The concept of Decision Support System is presented in the paper. One of the most impor-
tant problems in decision analysis relates to the situation, where the committee (group of decision
makers) has to select the best alternative from a given, finite set. In most cases, alternatives are
evaluated on the basis of several quality factors. In the paper, the author presents the new
approach, based on the principle of aspiration-led decision making. This approach ensures proper
structuralization of the decision process and allows proper balance of opinions of the group
member. The methodological principles of the approach as well as problems relating to computer
implementation and applications are presented in the paper.
Keywords. Decision analysis; decision theory; utility function; achievement function; scalarizing
function; decision support system; group decision making.
INTRODUCTION
some discussions abut the understanding of this term and
Decision Making is one of the most complicated form
its relation to other fields of Operations Research (OR)
of the manager's or designers (since engineering design
and Management Science (MS), especially to Management
can be also interpreted in the decision- making context)
Information Systems (MIS). Rather deep analysis of this
activity. The following elements of the decision making
problem was recently performed by Parker and Ai- Utabi
process cause certain difficulties:
(1986). The authors reviewed about 350 papers relating to
- certain (rather high) knowledge about the problem this subject trying to find the most appropriate
being analyzed is necessary, characterization of Decision Support Systems. The follow-
- the effects of the decision on the system outcome ing set of characteristics was defined by the authors:
and performance must be predicted by the decision The DSS should:
maker; this is a rather difficult task, because the quality
- assist managers in their decision processes in semi
of the decision can be characterized by many perfor-
structured tasks,
mance criteria,
support and enhance rather than replace
- certain level of uncertainty occurs during the deci-
managerial judgment,
sion making process, this uncertainty must be taken into
- improve the effectiveness of decision making rather
account when making decision,
the efficiency,
- complex structural and logical relationships exist
- to combine the use of models or analytical tech-
between the elements of the system being analyzed, deci-
niques with traditional data access and retrieval func-
sion undertaken, system outcome and behavior,
tions,
- decision making process is in the fact the informa-
- specifically focus on features which make them easy
tion processing task; therefore the decision maker must
to use by non-computer people in interactive mode,
handle large amount of information of different nature
and usually of poor quality. - emphasize flexibility and adaptability to accommo-
date changes in the environment and the decision making
Due to the facts listed above, decision making pro-
approach of the user.
cess requires certain amount of time and resources;
moreover, frequently the decision made is rather far from Following the same source, we should consider the
optimal, or even satisfactory. Usually, the complexity of characterization of the decision process formulated by
the decision making process does not allow to analyze all Simon. According to his qualification, the decision pro-
possible options - only a small subset can be effectively cess consists of the following three steps:
analyzed. Because of the lack of a'priori knowledge and
- Intelligence: searching the environment for oppor-
the presence of uncertainty, it can happen, that a poten- tunities calling for a decision,
tially good decisions are rejected on a very early stage of
- Design: inventing, developing and analyzing possi-
the decision process.
ble courses of action,
The informational and logical aspect of the decision
- Choice: selecting a particular course of action from
making process suggests, that the computer with its abil-
those available.
ity of handling and processing large amounts of informa-
tion and analyzing complex logical relations could be a Applying the above characterization it is possible to
proper tool to support this activity. conclude, that the MIS have made major contributions to
the intelligence phase; MS/OR have been useful mostly for
There are many commonly accepted definitions of the
the choice phase. The design phase could be one of the
decision support system - all these definitions agree, that
primary contributions of DSS. It should be pointed out,
such system must aid a decision maker in solving unstruc-
that in the case of MIS the design stage starts from the
tured (or "semistructured"), complex problems.
data available from the data processing system and moves
The term "decision support system" (DSS) became upwards to the decision maker. The DSS in the contrary,
rather popular during several years. There are currently starts with the problem to be solved and and works down
1
2 A. Lewandowski
with the computer selecting the appropriate subsets of The main differences between various approaches to
data and information stored in the computer, necessary to interactive decision support are concerned with the way
find the solution. The other aspects of decision support in which the decision maker specifies hies information and
systems was specified by Keen and Scott-Morton (1978). requirements about the problem which could be used for
According to their specification, the main area of impact estimation the complete preordering, as well as with the
of DSS related to the decision problems, in which ".. assumptions about the preordering, its properties and
there is sufficient structure for computer and analytic interpretations.
aids to be of value, but where managers judgment is
The most strongly established framework is based on
essential". The main payoff to organization caused by
the value function or utility function maximization.
application of DSS is "... the extending the range and
Under some very general assumptions the ordering can be
capacity of manager's decision process to help them to 1
represented by the utility function u: Ey -* R such that
improve their effectiveness". Finally, the main relevance
by maximizing this function over χ € J S Ç , we can select the
for managers in decision making process was specified as
decision which is most preferable to the decision maker.
"creation of supportive tools, under their own control,
The only difficulty relates to the identification of the util-
which does not atempt to automate the decision
ity function - this function is determined nonuniquely, is
process, predefine objectives or impose solutions".
affected by uncertainty of the decision making environ-
The last statement requires special attention - the ment an of the decision maker behavior, and what consti-
role of the decision support system is to provide support;
tutes the most esential trouble, is non stationary in
the human is still the most important element of the deci-
time due to the learning and adaptive nature of the
sion making process and the final decision is in his hands.
decision making process. Recently, some more detail
The only purpose of the DSS is to increase the under-
analysis of the relevance of this approach was performed
standing of the decision problem being solved through
- see, for example Fisher (1979), Horsky and Rao (1984).
deep analysis of the possible consequences of the decision
According to the results of the research presented in this
made, as well as simplifying the access to all information
paper, the utility function approach can be used in a
and knowledge necessary to find satisfactory solution.
rather simple, laboratory environment, but can fail in
Rather deep discussion of other aspects of the role and
more complex situations. The same opinion was justified by
principles of DSS and comparison of DSS methodology and
Eriandson (1981).
other ones in the field of MS and OR can be found in the
The second framework for rational decision making is
quoted above book.
the principle of satisficing decisions. This approach
Discussion related to methodological and organiza-
was firstly formulated by Simon (1969) and further
tional concepts of DSS was also performed by Naylor
extended by Wierzbicki (1982, 1983, 1984). Deep formali-
(1982), Watson and Hill (1983), Vazsonyi (1982) and Wynne
zation of this concept was recently done by Eriandson
(1982). Similarly to the definitions of the DSS specified
(1981).
above, the conclusion which follows from these papers are
The basic methodological assumptions of this princi-
the following:
ple are as follows:
- DSS, unlike OR/MS, does not replace decision mak-
- the decision maker evaluates possible decisions on
ers, but supports them; hence DSS is a mind supporting
the basis of set (or vector) of performance factors. These
system,
factors can be expressed in numerical scale
- DSS allows for the introduction of judgment, while
(quantitatively) or in verbal scale (qualitatively), like
OR/MS are normative/prescriptive,
"bad", "good" or "excellent",
- DSS deals with unstructured problems, while OR/MS
- for each performance factor the decision maker
applies mostly to structured problems,
specifies his aspiration levels; this is a value of the fac-
- OR/MS comes up with solutions and recommenda- tor, which can be accepted as reasonable or satisfactory.
tions, while DSS does not. In more complex situations the decision maker can specify
two levels for each performance factor - aspiration level
Very deep analysis of various organizational and
as defined above, and reservation level. The last one
methodological aspects of DSS was recently published by
describes the lowest acceptable level for a given perfor-
Sage (1981). The analysis of the concept of DSS from the
mance factor.
point of view of various disciplines - including psychology,
organizational behavior and design, information science, On the basis of the information specified by the deci-
management science and computer science. The basis for sion maker (i.e. set of performance factors, aspiration
investigation is the critical revue of over 400 up to date and preservation levels) the satisficing decision principle
publications relating to decision support systems. can be formulated as follows:
Case 1: the decision maker overestimated the system
possibilities - there exists no decision ensuring values of
THE SATISFYING DECISION PRINCIPLE all performance factors exactly equal to the aspiration
levels. In this case it is possible to propose the decision,
BASIC ASSUMPTIONS
for which values of performance factors are as close to
the aspiration levels, as possible.
The most important problems related to the develop-
ment of a decision support system are the assumptions Case Z\ the decision maker underestimated the sys-
about the mathematical structure of the class of problems tem possibilities - there exists the decision which ensures
the values of performance factors exactly equal to the
to which the DSS will apply. Such structure usually con-
specified aspiration levels. In this case it is possible to
sists of the following elements (see Wierzbicki, 1984):
propose the decision, which improves all the components
- a space of decisions (alternatives, options, con-
of performance vector as much as possible.
trols, designs etc.) denoted by Ex,
If the decision specified as the outcome of the pro-
- a constraint set X0 c Ex,
cess is not satisfactory, the aspiration levels are
- space of outcomes (attributes, objectives, perfor-
corrected and the whole process repeats. The technical
mance indices, etc.) denoted by Eyt
question arises - how to provide a proper formalization of
- an outcome mapping / : Ex -» Ey, which also defines the specified above methodological concept. This can be
the set of attainable outcomes Y0 = / (x0 ) c Ey done in the following way: let the decision making be
guided by aspiration levels, and let these levels be speci-
- a partial preordering that is usually implied by the
fied by the decision maker. The aspiration level w will be
decision problem and usually has some obvious interpreta-
used as the parameter for certain special utility function
tion, like maximization of profit etc. The standard assump-
called achievement function. This function is of the form
tion is that this preordering is transitive and can be
u(y) = s(y,w). This approach provides an explicit and
expressed by a positive cone D c Εχ.
constructive means of expressing the dependence on the
- a complete preordering, which is usually not given decision environment and proper handling of the nonsta-
in any precise mathematical form, but is specified by the tionarity of the decision's maker's preferences.
decision maker.
Committee Decision Making 3
The theory of achievement function was developed linear optimization problem, when by suitable transforma-
and further extended by Wierzbicki (see Wierzbicki, 1986 tion of variables it can be reduced to the single objective
for references and detail discussion of the problem). linear optimization problem with additional constraints
with Aanr gaucmheienvtem eyn-wt , funwcthioenr e yi s eaE y funcitsi oann s:a tEty ai-n*a bRl1e, at(hcsehieir eL vpeerwmoaepnnedtrot wfisuenksci tc iaaonnnd sb Getr ofagiuenetdrh ie,nr 1 t 9wh8iet2 h,m ed1ne9t8ia4io)ln.e dOdt dahiebsroc vufseos rpimoasnp eofrf
objective and w is the aspiration level. An achievement by Wierzbicki (1986).
function should satisfy the following requirements:
Practical experiments with this approach (see, for
a. It should be strictly order preserving with respect to example, Lewandowski at all., 1985) have shown, that the
y: language of aspirations coincides very well with the deci-
y2-y1tintD -» s (y ± - w) < s {y 2 - w)
rsieoqnu imraekde rf'rso ms thyilme iosf etahsiyn ktion ge.x pTrhees si,n fionr tmhaeti coonn twrhaircyh tios
or, if possible, strongly order preserving other approaches based on pairvise comparisons, utility
V2"Vi ^D/{D η -D) ·* s(yx-w) < s(y2~w) theory, explicit weighting factors etc.
b. It should be order representing:
\y ε Ey: s(y - w) & 0 1= w +D ALTERNATIVE BASED COMMITTEE DECISION
SUPPORT SYSTEM
or, at least, order approximating for small ε:
w + D c ( y e Ey: s {y - w) j cw +D€ Due to certain fuziness of the concept of decision
where sdeutpapiolretd styasxtoenmo,m yit o ifs t rhaet vhaeri oduifsf iccounlcte tpot sp roofv DiSdeS oar gmaonrie-
Dc= \y <=.Ey: dist(y, 2» < ε \\ y ]|) zation. Moreover, such a taxonomy could be performed
from various points of view - assumptions according to the
c. If w € Ey - D, then the maximization of s(y-w) over decision maker's behavior, formulation of the decision
y e Ey should represent a concept of either allocation or problem, methods of handling the uncertainty etc. The
maximization of the surplus y — w Ε D; if w j£Ey -D, most extensive comparison of various methods and
then the same maximization should represent the concept approaches can be found in book by Bonczek (1981).
of distance minimization between w and the set The most important criterion for distinguishing
\y ZEy:Ey π {y -hD) = φ J
pboestew eoefn vthairsi opuasp aerp,p rtohaec hmeest hfodr DoSfS g ewnilelra btien,g for thael tperunra--
The most important property of such function is the tives. Practically, two situations can occur:
following: a. the set of alternatives is generated by the team of
If s(y,w) is strongly order preserving then its maxi- specialists, on the basis of their knowledge about the
mal points in y e Ey satisfy the following condition: decision problem being solved, but without taking into
consideration all the possible quality factors and without
y = ar
yge Emay x s(y - w) * Ε.,y π (q - D) - φ emviatltuedat itnog thes ed efcaicstioorns . mTahikse rs et( orf aglrtoerunpa tiovfe sd eicsi suibon-
where makers) for evaluation and selection. After performing
D — D/ (J) η —D) tbhlye, e nveawlu saettio ins, g seonmeer aatletde.r nSautcihv eas daercei srieojne cstuepdp oarntd spyostseim-
We wil not discus the properties of achievement func- can be caled alternative oriented.
tions in detail. The usefulness of the achievement func- b. The integral part of the decision support systems
tion in building the interactive decision support systems constitutes the mathematical model of the decision situa-
follows from the following properties: tion. The primary input to the decision support system are
- maximization of the achievement function results in decision maker's aspirations; the system computes the
Pareto optimality, decision which in some sense corresponds to the these
- if the decision χ e Ex and the corresponding objec- aspirations. Such a decision support systems can be called
tives y e Ey are such, that s =s(y — w) = 0 then w is model oriented.
attainable and Pareto optimal, Evidently, in the case of alternative oriented DSS the
- if s < 0 then w is not attainable, mathematical model can be used by experts to generate
alternatives or evaluate the objectives. This, what differs
- if s > 0 then w is attainable, but not Pareto both approaches is the organization of feedback loop
optimal. between the decision maker and the mechanism for gen-
Therefore, this function can be used for computing Pareto erating alternatives.
optimal decisions as well as for checking for Pareto Currently, both approaches have been implemented
optimality and attainability of given w €.Ey. Moreover, and tested. The family of model oriented systems, named
value of the achievement function can be meaningfully DIDAS (Dynamic Interactive Decision Analysis and Sup-
interpreted - this can be treated as a kind of qualitative port) have been successfully applied to many practical
distance between a given decision y and aspiration level problems - see for example Grauer at all. (1984). The
w. alternative oriented system, named SCDAS (Selection Com-
The general form of the achievement function pro- mittee Decision Analysis and Support) for supporting
posed and analyzed by Wierzbicki for the case, when all decision making in group environment will be described in
performance factors should be minimized is as follows sequel (for more detailed presentation see Lewandowski at
—ν (w —y ) if y —w e D all., 1986).
( dist(7/-u>, Z>) otherwise ( 1 ) Many major decisions in management and engineering
where ν : R m -* R 1 is a strongly monotone function with the Tahre dienlsetgiattuteido nt o ocfo mmai tctoememsi otrte ger,o urpesm aoifn dse ciasni oinm mpaokretranst.
a
apnrbyo pvneor rtfmyo rimtnhu RaltaT O vDc{ awnd-y eb)n eo tea=sk e0tn h fteoo r nd eagflalitn iey v te-h ecw od niese t DaD/ni cn=etD . -InR at+nhmde. ataespep erdcoetpcr ioisfai tmoean -ndmyea ckdieiscniigos nim osunus ptp rotorhcteirsnesgfe otsor;oe lt shb.e pirmopcreosvse odf tchormomuigth-
lAinnoetahre cra nfo brem eoxfp raecshsiedv ebmye ntth ef fuoncrtmiuolna,: which is piecevise set ofT hael tperronbalteivme sof p sreelseecnttinegd otnoe a a cltoemrmniatttievee ifsr omn ea offin tihte
s(y,w) = m (2) most basic and classical decision problems and has
received much attention in the decision-theoretical
max(/o max (yt - wt), (1/m) J] (yt - wt)) literature (Mirkin, 1979, Kuzmin, 1982, Pankova, at all.
1984). There are many variants of such a problem; here,
The above function is especially useful when applied to we will consider the following formulation:
A. Lewandowski
4
Procedural Framework
A committee consists of several members (denoted
here by k = 1,...,K)\ each member can have either equal
or different voting power (denoted here by a voting One of the basic assumptions of the presented metho-
power coefficient v(k)), specified a priori by the commit- dology is structuralization of the decision process. We
tee charter. In addition to the committee structure, the assume, that the process consists of several well defined
committee charter might specify the purpose of the phases or stages. According to the procedure or the com-
committee's work, further procedural details, etc. mittee charter it is possible to advance the decision pro-
cess forward only if all committee members successfully
The problem faced by the committee is to jointly rank
completed all the previous phases. Details of the pro-
or select one or a few from a set of available decision
cedure must be defined during the initial stage of the
alternatives (these might be candidates for a job, propo-
decision process. Let us consider in detail all phases of
sals for R&D projects, alternative transportation routes,
the decision making process.
proposed sites of an industrial facility, alternative
computer systems, etc.). The list of alternatives need not The first point on the agenda is to define the pro-
be complete at the beginning of the committee's work; cedures by which the committee will operate. The ques-
during the decision-making process, new alternatives may tions addressed here should include the following:
be generated and subsequently evaluated.
(a) What is the expected product of the committee's
Evaluation of alternatives is performed by the com- work and how does it influence the appropriate pro-
mittee by first specifying decision attributes (such as a cedure? The answer to this question depends on the
candidate's age, experience, professional reputation, committee's charter and its perceived role. For example,
etc.) and then assessing each alternative with respect to if the expected product is a short list of significantly dif-
each of these attributes. The list of decision attributes ferent alternatives, procedural rules will be different
(denoted by ,7=1,...,«/) might be specified in the from the case when the expected product is a consensus
committee's charter or decided upon by the committee. In opinion on the "best" alternative.
any case, decision attributes must be specified before
(b) What aggregation rules should be adopted, and in
alternatives can be evaluated and compared.
particular, should outlying opinions be included in or
Each alternative (denoted by i =1,...,/) must be excluded from aggregation?
evaluated by the committee or its individual members. The
(c) Should the committee be allowed to divide and
problem consists of proposing a decision process which
form coalitions that might present separate assessments
together with assessment of various attributes of the
of aspirations, attribute scores and thus final rankings of
alternatives and aggregation of evaluations across both
alternatives?
attributes and committee members, leads to a final rank-
The second point on the agenda is the problem
ing or selection of an alternative(s) in a way that is
specification. Neither the list of alternatives, nor their
rational, understandable and acceptable to the committee
descriptions need be complete at this stage and moreover
members.
this information should be not known to the committee
Several approaches to this problem have been members to avoid the bias in specifying the aspiration
developed; most of them are based on the classical multi- levels required in this phase. The most important part of
attribute utility theory (see e.g. Keeney and Raiffa, this process that requires discussion and specification by
1976), but there are also alternative approaches, such as the entire committee is the definition of the attributes of
the analytical hierarchy of Saaty (1982), the orderings of the decision and their scales of assessment.
Roy (1971) or aggregation principle by Jacquet-Lagreze
Various studies in decision theory suggest that a rea-
(1982). Some of these approaches have been also imple-
sonable number of attributes should not exceed seven to
mented as microcomputer-based decision support systems:
nine (see e.g. Dinkelbach, 1982); if more attributes are
an interesting implementation is that of analytical hierar-
suggested, they should be aggregated. For example,
chy (EXPERT CHOICE, 1983) or the non-procedural pack-
there might be a large number of qualitative indicators
age DEMOS (1982) used for probabilistic evaluation of
that are all related to the ecological impacts of the
alternatives. Another commercially available implementa-
planned investments; instead of using all these indicators,
tion (LIGHTYEAR, 1984), based on utility theory and
it is better to ask committee members to evaluate subjec-
weighting coefficients specified by the user, employs a
tively the attribute "ecology", that is, to translate the
rather primitive decision process and is restricted to
information about all these indicators into one assess-
only one user, hence it is not applicable in committee
ment, given originally on a verbal scale from "unaccept-
decisions.
able" to "excellent", into a quantitative scale, say from 0
Most of these approaches rely on either user- to 10. The other possible option is to introduce the
supplied rankings of attributes and alternatives for each hierarchy in the set of objectives. This makes however
attribute, pairvise comparisons of alternatives, or some the procedure much more complicated and the
uncertainty equivalence principle (e.g. comparisons to a corresponding theory and software is currently not fully
lottery). This information is rather difficult to obtain dur- developed.
ing discussions with the committee members, therefore the
During the third point on the agenda, aspiration
proposed approach utilizes the principle of satisfaction
and/or reservation levels for all attributes are deter-
decision making based on the concept of achievement
mined separately by each committee member. After these
function.
values are entered into the system, all necessary indica-
Additionally to the aspiration level which expresses tors (disagreement indicators, dominant weighting fac-
the satisfactory (or acceptable) values of all objectives,
tors) can be computed.
members of the committee can specify the reservation
The fourth point is the analysis and discussion of
level. The reservation level represents a minimum accept-
aspirations by the entire committee. These discussions
able level for each attribute (e.g. investment cost should
are supported by the computed indicators and their
not exceed some given a'priori value) whereas an aspira-
graphic interpretations.
tion level reflects a higher desired level of expertise. If
In these discussions, the committee might address the
an alternative is evaluated below the reservation level on
following questions:
even one attribute, it is considered unacceptable, and if it
is evaluated at least equal to aspiration levels for all (a) Do the dominant weighting factors accurately
attributes, it is considered highly desirable. The exten- reflect the perceptions of individual committee members
sion of aspiration-led decision process to committee deci- about the relative importance of various attributes (if
sion making was first proposed by Johnson (1984); details not, should the aspirations or reservations be
of the procedure, theoretical background and principles corrected)?
of implementation are presented in more details in the
(b) What are the relevant differences and do they
paper by Lewandowski at all. (1986).
represent an essential disagreement about decision prin-
ciples?
5
Committee Decision Making
Formalization of the Decision Process
(c) Does the entire committee agree to use joint,
aggregated aspirations (reservations), or will there be
several separate sub-group aggregations? In the previous section we presented the general
structure of the decision making process. The decision
The fifth point on the agenda is a survey of alterna-
support system supervises the progress of the discussion
tives. Discussions might center on the following:
within the committee - its role is to process all the infor-
(a) Are the available descriptions of alternatives
mation necessary to perform the discussion, compute all
adequate for judging them according to the accepted list
necessary informative indicators, display graphic infor-
of attributes? If the answer is negative, additional infor-
mation and ensure proper structuralization of the pro-
mation should be gathered by sending out questionnaires,
cess. In the sequel we will consider in detail all the
consulting experts etc.
actions undertaken by the system during each phase of
(b) Which of the available alternatives are irrelevant the process.
and should be deleted from the list? This kind of cursory
screening can be done in various ways. The committee
might define some screening attributes and reservation
Setting and discussing aspirations
levels for them (of a quantitative or simple logical
structure): for example, we do not accept investments
Most judgmental decision processes require a choice
which are more expensive than a given limit.
of scales of evaluation for each decision attribute. The
The sixth point on the agenda is the individual
scales are often qualitative, such as unacceptable, bad,
assessment of alternatives. The assignment of scores for
acceptable, good, very good, excellent, though they can
each attribute to each alternative is the main input of be transformed into quantitative scales for computational
committee members into the system. Each member speci- purposes. When asked to specify aspiration and reserva-
fies scores; the system supports this by displaying those tion levels on these scales at an early stage of the deci-
assignments already made and those still to be entered. sion process, the decision maker is better prepared to
The seventh point on the agenda is individual make consistent evaluations across alternatives. How-
analysis of alternatives, based on calculations of the ever, we cannot expect and we should not require full
achievement function which lead to a ranking of ail alter- consistency in any judgmental decision process, since not
natives for each committee member. This ranking is the all relevant attributes might be evaluated and the
main source of learning about the distribution of alterna- relevant information an alternatives is never completely
shared by all committee members. If each committee
tives relative to aspirations.
member is asked independently to specify his aspiration
The questions addressed by each member at this point
and (or) reservation levels for each attribute, a com-
might be as follows:
parison of such results across the committee and across
(a) Do the rankings along each attribute correctly attributes serves several purposes:
represent the individual's evaluations of alternatives;
(a) the relative importance of each attribute for
does the achievement ranking, based on individual aspira-
each committee member and across the committee, as
tions, correctly represent the aggregate evaluation (if
implied by the more or less attainable levels, becomes
not, should the scores be modified)?
apparent, as discussed below.
(c) If the committee member agrees with the indivi-
(b) the division of opinions among the committee
dual achievement ranking proposed by the system, what
members can be discussed: if a significant subset of the
are the differences between this ranking and that based
committee has high aspirations (reservations) for an
on individual scores but related to committee aggregated
attribute and another subset has low aspirations (reser-
aspirations? Are these differences significant, or can he
vations), it is a case of a clear disagreement on decision
accept them as the result of agreement on joint decision
principles. The committee might then discuss this
principles?
disagreement and come to a consensus; or agree to
The eighth point on the agenda is a committee dis-
disagree by allowing the formation of coalitions that rally
cussion of the essential differences in scoring and
for the importance of various attributes (for example,
disagreements about the preliminary ranking of alterna-
when deciding on siting an industrial facility, a part of the
tives aggregated across the committee. These discussions
committee might be more concerned with environmental
are supported by the system; the system computes indica-
impacts, another more concerned with economic impacts).
tors of differences of opinion and prepares a preliminary
(c) if the discussion shows that the reason for
aggregated ranking.
disagreement stems from different perceptions by various
The questions addressed by the committee at this
committee members about the exact meaning of a particu-
point might be the following:
lar attribute and its scale of evaluation, the result might
(a) On which attributes are the largest differences in be a better specification of, or at least corrections in,
scoring between committee members observed? Do these the list of attributes.
differences represent essential differences in information
(d) if the committee (or a coalition inside the commit-
about the same alternative?
tee) agrees to use averaged aspiration and (or) reserva-
(b) What is the essential information (or uncertainty tion levels, each committee member has a better percep-
about such information) that causes these differences? tion of the anchor points to be used when evaluating alter-
Should additional information be gathered, or can certain natives.
committee members supply this information?
In order to support these discussions, a number of
(c) Would the results of these discussions and possi- indicators can be computed. Denote the individually
ble changes of scoring influence the preliminary aggre- specified aspiration levels for attribute j by the commit-
gated ranking list proposed by the system? This can be tee member k by p(j,k) and the corresponding reserva-
tested by applying simple sensitivity analyses. tion levels by r(j,k). Then the committee "voting" pro-
(d) Does the preliminary ranking proposed by the cedure might specify an averaging of individual inputs,
system correctly represent prevalent committee prefer- weighted by the voting power coefficients as follows:
ences?
Κ Κ
After these discussions, a return to any previous
PU) = Σ v{k)p(j,k)/ Σ v{k) (3a)
points on the agenda is posible. If the comite decides k =1 k=\
that the decision problem has ben suficiently clarified, Κ Κ
3b
it can proced to the final, ninth point on the agenda: rU) = Σ w<*)r(j\*)/ Σ <>
agreement on the aggregated ranking or selection of one k. =1 k =1
or more alternatives. It is important to stress again that
Such an average is subject to manipulations by com-
the committee need not stick to the ranking proposed by
mittee members who have an incentive to distort their
the system, since the purpose of this ranking - as well as
true aspirations in order to influence the entire commit-
of all information presented by the system - is to clarify
tee. A classical remedy, successfully used in subjective
the decision situation rather than to prescribe the action
evaluations of certain sport performances (e.g. ice skat-
that should be taken by the committee.