Download Document

WINGDSS
Group Decision Support System
under MS-Windows
M. Biró, P. Csáki, M. Vermes
Computer and Automation Institute
Hungarian Academy of Sciences
Budapest, Kende u. 13-17, H-1111, Hungary
Supported by OMFB contract no G1-16-138.
1
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
1. Introduction
WINGDSS is a group decision support system based on multiattribute
utility decomposition. The basic purpose of a group decision process
is
the
coordination
of
the
decision
related
activities
of
the
involved individuals or subgroups who may have different perspectives
or priorities.
WINGDSS supports the consideration of a complex system of criteria
for
the
approach
evaluation
helps
in
of
a
set
overcoming
of
the
alternatives.
cognitive
Its
hierarchical
psychological
barrier
caused by a large number of relevant criteria. At the same time, the
use of an objective method for aggregating the partial evaluations
may result in a significant relief for the decision makers as far as
the objectivity of the decision is concerned.
The distinctive features of WINGDSS are related to both the form, and
the content of the system. Form means the style and quality of
man-machine interaction, content means the level of support provided
by the system.
2. Man-Machine Interaction Features
WINGDSS is equipped with a new generation interface based on the
standard Microsoft Windows operating environment. This permits the
raising of the user-friendliness of the IBM PC/AT based system to a
workstation level.
The window based multitasking graphics environment allows a
*
simultaneous,
*
visual,
*
active,
*
object-oriented
access to all necessary information and multiple parallel processes.
2
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
2.1.
Access to All Necessary Information
Typical
information
which
the
user
can
simultaneously
overview
without losing any visual or even active contact are the following
for example:
*
decision makers and their spheres of authority,
*
*
hierarchy of the criteria and their relative significance,
alternatives and their evaluations with respect to the
criteria,
*
graphical representations (charts, maps).
The MS-Windows software technology would allow even more parallelism.
In order to avoid screen clutter, WINGDSS takes however care of
removing any unnecessary information from the screen before a new
function is invoked.
The professional version of WINGDSS includes a feature which can be
called UIMS (User Interface Management System). If the user is in
possession of the Microsoft Windows development tool kit, then the
style and content of the dialog boxes, through which information is
entered, can be defined or altered by mostly graphical manipulations
using a dialog box editor. The new dialog boxes can be readily
assigned to the entities of the system in the appropriate stage of
the decision process.
The normal versions of WINGDSS include predefined dialog boxes which
are sufficient in most decision problems. The choice between these
dialog boxes is the task of the supervisor, system facilitator or any
authorized user.
3
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
2.2.
Access to Multiple Parallel Processes
Some of the parallel processes to which simultaneous access may be
highly desirable are:
*
a calculator (Microsoft Windows),
*
a spreadsheet (Microsoft Excel),
*
a calendar with personal notes and alarm function (Microsoft
Windows),
*
any dependently or independently implemented method.
User
controlled
supported
data
through
the
exchange
between
clipboard
of
the
above
Windows.
The
processes
is
possibility
of
automatically activated dynamic data exchange is also open using the
DDE protocol [Biró,M. (1990)].
3. Decision Support Features
The fundamental entities in WINGDSS are the decision makers, the
alternatives,
and
the
criteria.
The
users
of
the
system
enter
information related to these entities or any combination of these
entities, then retrieve derived information also related to these.
The decision makers, a facilitator or supervisor, and even invited
experts can be users of the system.
The entities themselves are entered into a hierarchical structure
using
the
autonomous
AggRegated
Object
MAnagement
system
AROMA
incorporated into WINGDSS.
The type and instance of information assigned by the users of the
system to the entities at various stages of the decision making
process
is
characterized
by
a
well
defined
construct
called
operational context. An operational context
is a list. The elements
of
specific
the
list
are
unique
identifiers
of
alternatives,
4
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
criteria,
decision
makers,
and
possibly
other
identifiers.
Any
combination of these elements defines an operational context.
We use this notion at the same time as a vehicle for explaining the
results of actions taken at various stages of the process, and as a
data base key for actually saving and accessing information. The
stages
of
the
decision
making
process
are
highlighted
from
the
operational context point of view in the following sections.
These stages are initiated by the user through the choice of the
desired function, which at the same time determines a part of the
operational context. The operational context is completed when the
user selects an entity. This action usually results in the appearance
of
a
dialog
box
(frame)
containing
information
assigned
to
that
entity in the current operational context.
The
selection
of
an
entity
is
supported
with
two
different
techniques. The first is the choice from a list box containing the
names of the entities. The second is the "point and click" style
selection from simple windows whose titles are the names of the
entities.
The
following
sections
correspond
to
the
functions
the
user
can
select in WINGDSS. After eventual introductory discussions, the last
three paragraphs of each of them have specific roles. The first gives
the purpose of the function. The second describes the characteristics
of the operational contexts related to the the function. The third
specifies the style of entering information.
3.1.
Decision makers' entry and assignment of authorities
New decision makers are entered using AROMA, and their individual
spheres of authority are assigned in this stage by the supervisor.
5
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
The only relevant part of this context is the identifier of the
decision maker himself. This part is finalized when the user selects
a decision maker. At this time, a dialog box appears.
The dialog box contains check boxes which authorize the entrance of
various stages for the selected decision maker.
3.2.
Entry of the alternatives
The purpose of any decision is a choice between alternatives whose
following categorization is defined by the nature of the decision
making problem.
- Naturally Given Alternatives
There is no need for expert involvement in the determination of the
alternatives if they are naturally given. This is the case of bid
evaluation for example, and of any selection from a predefined finite
set in general.
This is the only case supported by many systems.
- Generated Alternatives
If the alternatives are not predefined then they must be generated by
experts or the decision makers themselves.
If a problem is structured enough to lend itself to modeling, then
efficient solutions to the model may yield valuable alternatives. The
construction of a model is a task that requires special expertise.
The use of mathematical models for generating alternatives is usually
not
integrated
with
group
decision
support
systems.
Ideas
and
techniques related to this topic are discussed in [Biró,M., Maros,I.
(1991)].
6
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
The
direct
involvement
of
a
modeling
expert
is
the
immediate
solution. The task of partly replacing modeling experts by so called
modeling support systems is the subject of intensive study nowadays.
The knowledge of modeling experts must be captured and incorporated
into the system. Related ideas are discussed in [Biró,M., Mayer,J.,
Rapcsák,T., Vermes,M. (1991)].
If
a
problem
is
not
structured
then
the
decision
alternatives proposed by the decision makers.
must
rely
on
While the optimality
of these alternatives is not guaranteed, the data requirements of
this approach are lower than those of a mathematical model.
The
decision
makers
may
invite
experts
for
the
generation
of
efficient alternatives which they can choose from afterward. A more
advanced approach is the use of an expert system developed for the
specific problem domain under consideration.
- Dynamic Alternatives
We call the alternatives dynamic if their attributes change over
time, are dependent on choices or random events related to other
alternatives.
The idea of integrating the handling of dynamic alternatives into a
general purpose group decision support system is original. The models
that
can
be
used
in
this
case
are
related
to
the
fields
of
simulation, decision analysis and project management.
7
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
3.3.
Entry of the criteria and assignment of frame types for
qualifying
The decision making process usually begins with the definition of the
problem, which, besides the verbal description, essentially consists
of
the
development
of
criteria
used
in
evaluating
any
relevant
alternatives. This creative development is supported by the hierarchy
building tool AROMA.
The
following
are
the
fundamental
reasons
for
the
hierarchical
structure of complex systems as discussed in [Simon,H.A. (1977)]:
(1) Hierarchical systems are most apt for evolution among systems
with given size and complexity, since the components of a hierarchy
are themselves hierarchies which are stable structures.
(2) The information transfer requirement between the components of a
hierarchical systems is less than in other systems.
(3)
The
local
complexity
of
a
hierarchical
system
is
highly
independent on its size.
In addition, it is a well-known psychological fact that humans cannot
take much more than seven concepts simultaneously into consideration.
The use of hierarchies
helps in this respect as well, since the
number of direct descendents of an entry can be restricted to be no
more than the magic number.
Hierarchies
have
been
implemented
in
Expert
Choice
[Forman,E.H.,
Saaty,T.L. (1983-1988)] and Meditator [Gelléri,P., Martinez,F. (1988,
1989)].
The hierarchy of criteria in WINGDSS can be built and extended using
AROMA. Frame types for weighing and qualifying each criterion are
8
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
also assigned in this step.
The contexts for both weighing and qualifying are characterized by a
specific criterion only. They do not depend on either the decision
makers or the alternatives. The contexts are completed when the user
selects a criterion.
The information assigned in these contexts consist of parameters
necessary for some of the functions used for deriving the weights of
the
criteria
and
the
utilities
of
the
alternatives
from
the
information entered by each decision maker during the weighing and
qualifying stages.
3.4.
Assignment of voting powers or competence factors to the
decision makers
The voting power or competence assignment facility can be used to
increase or decrease the influence of specific decision makers with
respect
to
specific
criteria.
In
the
extreme
case
when
the
competences of the decision makers are restricted to disjoint subsets
of criteria, WINGDSS becomes a distributed decision support system.
Distributed
decision
support
systems
have
a
wide
range
of
applications on their own right.
Voting powers or competence factors are assigned in this step for
each decision maker with respect to each criterion both for weighing
and for qualifying.
The
contexts
in
this
case
are
clearly
characterized
by
the
combination of a decision maker and a criterion in addition to an
indicator showing whether the voting power is related to weighing or
to qualifying. A context is built using a dialog box containing a
weighing and a qualifying radio button and a list box containing the
criteria. The context is completed when the user selects a decision
9
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
maker.
The level of competence can be assigned by clicking on a verbally
defined rate of the competence factor.
3.5.
This
Weighing the criteria
step
is
performed
by
each
decision
maker
separately.
They
evaluate the relative importance of the subcriteria of each specific
aggregated criterion. The importance of a hierarchical approach is
apparent here.
The operational context in this step is characterized by the decision
maker and the criterion. It is completed when the user clicks on the
criterion or selects the criterion from a list.
The evaluation is entered into the frame the type of which was
assigned to the given criterion for weighing at an earlier stage. The
frame type determines the type of the information, the style of its
entry and the method of deriving a weight value from it.
3.6.
Qualifying the alternatives with respect to the basic level
criteria
The
qualification
may
be
based
on
objective
data,
subjective
evaluations, or on a combination of both.
The
objective
measurement
data
units.
may
These
represent
values
are
measured
entered
values
only
with
once
given
by
the
supervisor or an expert, and they are automatically accessed by all
other users.
If the availability of objective data induces the application of a
10
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
model as mentioned earlier, then the model provides the utilities of
the alternatives. If the model is already built, then the execution
of model experiments with parameters reset according to the judgement
of
the
decision
maker,
may
yield
more
efficient
or
acceptable
alternatives.
If no objective or detailed data are available then the subjective
judgement of the decision makers must be called upon. A utility value
is subsequently derived from the information entered into a dialog
box in the most appropriate form by each decision maker.
Utility functions are used to normalize evaluations with respect to
incommensurable criteria to a common scale. Utility functions may be
constructed according to the requirements of the users. Some of the
possible forms of the functions are staircase, piecewise linear,
ordered
symbolic,
and
utilities
assigned
to
the
satisfaction
of
rules.
The
qualification
step
is
performed
by
each
decision
maker
separately. They qualify each alternative with respect to each basic
level criterion. The aggregated utilities of the alternatives with
respect to the higher level criteria are
derived by the system
applying the criterion weights assigned at a previous stage.
The
operational
context
in
this
step
is
characterized
by
the
combination of a decision maker, a basic level criterion and an
alternative. It is completed when the user selects an alternative, or
in case one or more alternatives have already been selected, the
context can be changed by choosing a different criterion from a list
box.
The evaluation is entered into the frame the type of which was
assigned to the given criterion for qualifying at an earlier stage.
The frame type determines the type of the information, the style of
11
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
its entry and the method of deriving a utility value from it.
3.7.
Ranking the alternatives
After the qualification of the
alternatives, a ranking of the latter
is advanced first by each individual, then by the whole group of
decision makers.
- Individual ranking
Individual ranking is based on aggregated utilities computed from the
voting powers or competence factors, the relative weights of the
criteria, and the utilities of the alternatives with respect to the
basic level criteria. A critical acceptance level may be set for the
utility of an alternative with respect to any criterion.
- Group ranking
Group
ranking
could
be
considered
theoretically
as
a
special
multicriteria decision making problem, where each member of
the
group has his own set of criteria. A different approach is necessary
however, since a social consensus has to be reached in this case, in
contrast to lifeless criteria which will never protest.
There is theoretical evidence [Arrow,K.J. (1963)] that there is no
single method of aggregation of individual decisions which results in
an
acceptable
group
decision
in
all
cases
under
realistic
requirements (see the Appendix). As a solution, several methods of
aggregation may be offered by the system, including simple average
and the Borda count dating from the 18th century but recently proved
to be the best in some sense. [Saari (1988)]
12
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
References
[Arrow,K.J. (1951)] Social Choice and Individual Values. Wiley, New
York.
[Biró,M.,
Turchányi,P.,
Development
and
Vermes,M.
Operations
(1989)]
Research
tools
CONDOR-GDSS
Group
CONsensus
Decision
Support
System, MTA SZTAKI Report 23/1989.
[Biró,M.
(1990)]
The
Microsoft
Windows
Environment.
In:
Window
Systems (ed. Á.Hernádi), Typotex, Budapest, Hungary. (in Hungarian)
[Biró,M., Maros,I. (1991)] Deep Knowledge for Group Decision Support.
MTA SZTAKI Report 42/1991.
[Biró,M.,
Mayer,J.,
Rapcsák,T.,
Vermes,M.
(1991)]
Mathematical
Programming Expert Systems. In: Proceedings of the Second Conference
on Artificial Intelligence, Budapest, Hungary.
[Forman,E.H., Saaty,T.L. (1983-1988)] Expert Choice, Based on the
Analytic Hierarchy Process. The Decision Support Software Company.
[Gelléri,P.,
Martinez,F.
(1988)]
How
to
handle
differences
in
importance among participants in GDSS. In: Organizational Decision
Support
Systems
(eds.
R.M.Lee,
A.M.McCosh,
P.Migliarese),
North
Holland, pp. 117-126.
[Gelléri,P., Martinez,F. (1989)] Concept of group work with DSS in
network environment. In: Network Information Processing Systems (eds.
K.Bogdanov, R.Angelinov), North Holland, pp. 205-216.
[Saari,D.G.
(1988)]
Symmetry,
Voting,
and
Social
Choice.
The
Mathematical Intelligencer, 10,3,32-42.
[Simon,H.A. (1977)] The New Science of Management Decision. Prentice
Hall, Englewood Cliffs, New Jersey.
13
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
Appendix: The pitfalls of group decision making
The
most
common
form
of
group
decision
making
is
election
or
selection by voting. It is well known that a fundamental difficulty
occurs when none of the candidates receives an absolute majority of
the votes. One usual solution to the problem is a second round, in
which those two candidates run only who have achieved the largest
number of votes in the first round. It may easily happen, however,
that there is one among the beaten candidates who would be elected by
absolute majority on the second round against any one of the two
finally running candidates. The simple example below illustrates this
case.
The
presentation
below
is
based
on
preference
profiles,
that
is
complete rankings of the candidates by the voters, instead of just
votes for the most preferred candidate.
9 voters: {v1,...,v9}, 3 candidates: {c1,c2,c3}.
v1
v2
v3
v4
v5
v6
v7
v8
v9
c1
c1
c1
c1
c2
c2
c2
c3
c3
c3
c3
c3
c3
c3
c3
c3
c2
c2
c2
c2
c2
c2
c1
c1
c1
c1
c1
It can be easily seen that c2 is the winner of the above two round
election even though c3 would clearly win against either c1 or c2
alone.
In
case
of
successfully
the
above
applied.
example,
A
the
candidate
is
simple
majority
rule
can
higher
than
another
ranked
be
candidate with this rule if he is ranked higher by a majority of
voters. Unfortunately, this rule has a inherent
problem illustrated
by the following example also called Condorcet paradox [Marquis de
Condorcet (1785)].
14
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm
3 voters, 3 candidates.
v1
v2
v3
c1
c2
c3
c2
c3
c1
c3
c1
c2
The simple majority rule is immediately seen to be contradictory,
since the induced relation is not transitive. The group ranks c1
above c2, c2 above c3, and c3 above c1.
Another classical rule is due to Jean-Charles de Borda (1781). The
group score of a candidate with this rule is obtained by adding up
the number of candidates ranked below him by all voters. All of the
three candidates of the above example receive an identical (3) score
with this rule. This corresponds to the result expected in the above
case. It can be easily verified that the Borda rule provides a
satisfactory result in the first case above as well. For sake of
completeness however, an example is given below where it is the Borda
rule which fails to satisfy our sense of justice.
5 voters, 6 candidates.
v1
v2
v3
v4
v5
c1
c1
c1
c1
c2
c2
c2
c2
c2
c3
c3
c3
c3
c3
c4
c4
c4
c4
c4
c5
c5
c5
c5
c5
c6
c6
c6
c6
c6
c1
The winner of this voting is c2 obtaining a score of 21 with the
Borda rule. The score of c1 is only 20, even though c1 was elected
first by four out of the five voters (a far absolute majority).
It is Kenneth Arrow, Nobel Prize winner (1972), who gives a formal
approach to the above cases. The essence of his formally proven
impossibility theorem is that there is no voting rule which would
satisfy some natural requirements (axioms) for any profile of voters.
15
Published in: Biró, Miklós; Csáki, P.; Vermes, M. (1991): WINGDSS Group Decision Support System
under MS-Windows. In: Proceedings of the Second Conference on Artificial Intelligence (ed. by
I.Fekete and P.Koch). (John von Neumann Society for Computer Sciences, Budapest, Hungary, 1991)
pp.263-274.
http://mek.oszk.hu/00000/00024/00024.htm