Descriptive Profiles for Sets of Alternatives in Multiple Criteria Decision Aid
Author(s) -
AlexandruLiviu Olteanu,
Patrick Meyer,
Raymond Bisdorff
Publication year - 2013
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
DOI - 10.1007/978-3-642-41575-3_22
Subject(s) - computer science , task (project management) , sorting , decision maker , set (abstract data type) , context (archaeology) , representation (politics) , operations research , artificial intelligence , decision problem , decision analysis , machine learning , data mining , algorithm , mathematics , mathematical economics , politics , political science , programming language , management , economics , law , paleontology , biology
International audienceIn the context of Multiple Criteria Decision Aid, a decision-maker may be faced at any time with the task of analyzing one or several sets of alternatives, irrespective of the decision he is about to make. As in this case the alternatives may express contrasting gains and losses on the criteria on which they are evaluated, and while the sets that are presented to the decision-maker may potentially be large, the task of analysing them becomes a difficult one. Therefore the need to reduce these sets to a more concise representation is very important. Classically, profiles that describe sets of alternatives may be found in the context of the sorting problem, however they are either given beforehand by the decision-maker or determined from a set of assignment examples. We would therefore like to extend such profiles, as well as propose new ones, in order to characterize any set of alternatives. For each of them, we present several approaches for extracting them, which we then compare with respect to their performance
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