Seminario - The Robust Ordinal Regression and the constructive approach of Multiple Criteria Decision Aiding
Venerdì 18 Febbraio alle ore 15:30 il prof. Salvatore Greco, Ordinario
del Dipartimento di Economia e Impresa del nostro Ateneo, e della
Portsmouth Business School, UK, terrà un seminario online dal titolo
"The Robust Ordinal Regression and the constructive approach of
Multiple Criteria Decision Aiding".
Il seminario, della durata di 1h, si svolgerà tramite piattaforma
Teams ed è aperto a tutti gli interessati utilizzando il link sotto
riportato.
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TITLE: The Robust Ordinal Regression and the constructive approach of
Multiple Criteria Decision Aiding
ABSTRACT:
Multiple Criteria Decision Aiding (MCDA) is constituted by a set of
concepts, techniques and procedures aiming to provide a recommendation
in complex decision contexts. MCDA is based on a constructive approach
that aims to build a preference model in cooperation between the
analyst and the Decision Maker (DM). A typical MCDA methodology is the
ordinal regression aiming to define a decision model in a given class
(an additive value function, a Choquet integral, an outranking model
such as an ELECTRE or PROMETHEE method and so on) representing the
preference information provided by the DM. Recently ordinal regression
has been extended and generalized through robust ordinal regression
taking into account the idea that there is a plurality of decision
models in a given class compatible with the preferences expressed by
the decision maker. Originally, the set of compatible decision models
was used to define the necessary and possible preference relations
holding when the preference holds for all compatible decision models
or for at least one compatible decision model, respectively. After, a
probability distribution on the set of compatible decision models was
introduced to define probabilistic preferences. ROR has been also
fruitfully applied to interactive optimization procedures. In this
talk I shall present the basic concepts, the principal models, the
main applications and the recent developments of robust ordinal
regression taking into consideration its advantages in the context of
an MCDA constructive approach.