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What is Aggregation and Ranking Alternatives nearby the Multi-Attribute Ideal Situations (ARAMIS)

Encyclopedia of Decision Making and Decision Support Technologies
ARAMIS is the method for group ordering multi-attribute objects represented as multisets by their closeness to any “ideal” objects in a multiset metric space. The ranking of all objects is found without building many different expert arrangements by many criteria, and without an aggregation them into a common ranking. The object arrangement takes into account various inconsistent and contradictory expert estimates without forcing one to find a compromise among them.
Published in Chapter:
Group Verbal Decision Analysis
Alexey Petrovsky (Institute for Systems Analysis – Russian Academy of Sciences, Russia)
DOI: 10.4018/978-1-59904-843-7.ch048
Abstract
Ordering and classification of objects by their properties are among the typical problems in multiple criteria decision aiding (MCDA). The difficulties of choice problems increase when the same object may exist in several copies with different attributes’ values, and values of different attributes may be repeated within the object description. For example, such situation arises when several experts estimate alternatives upon multiple criteria. In this case, individual expert assessments may be similar, diverse, or contradictory. Various techniques for classification of alternatives or their ranking have been developed. But most of the methods do not pay a serious consideration to contradictions and inconsistencies in decision makers’ (DM) preferences and a problem description. Group verbal decision analysis (GroupVDA) is a new methodological approach in the MCDA area, which enlarges verbal decision analysis (VDA) approach to a group decision. GroupVDA deals with choice problems where preferences of several decision makers may be discordant, and alternatives are described with manifold repeating quantitative and qualitative attributes. New GroupVDA methods are based on the theory of multisets or sets with repeating elements, and represent multi-attribute objects as points in multiset metric spaces.
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