Salvatore Greco

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The purpose of this introductory part is to present an overall view of what MCDA<lb>is today. In Section 1, I will attempt to bring answers to questions such as: what<lb>is it reasonable to expect from MCDA? Why decision aiding is more often multi-<lb>criteria than monocriterion? What are the main limitations to objectivity? Section<lb>2 will be devoted to(More)
We consider a sorting (classification) problem in the presence of multiple attributes and criteria, called the MA&C sorting problem. It consists in assignment of some actions to some pre-defined and preference-ordered decision classes. The actions are described by a finite set of attributes and criteria. Both attributes and criteria take values from their(More)
We present the methodology of Multiple-Criteria Decision Aiding (MCDA) based on preference modelling in terms of “if..., then ...” decision rules. The basic assumption of the decision rule approach is that the decision maker (DM) accepts to give preferential information in terms of examples of decisions and looks for simple rules justifying her decisions.(More)
Banker, R.D., Charnes, A., Cooper, W.W., 1984. Some models for estimating technical and scale inefficiencies in Data Envelopment Analysis. Management Science 30 (9), 1078– 1092. Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444. Charnes, A., Cooper, W.W.,(More)
Consideration of preference-orders requires the use of an extended rough set model called Dominance-based Rough Set Approach (DRSA). The rough approximations defined within DRSA are based on consistency in the sense of dominance principle. It requires that objects having not-worse evaluation with respect to a set of considered criteria than a referent(More)