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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