Rough Set Approach to Multi-Attribute Choice and Ranking Problems

We propose an original way of applying the rough set theory to the analysis of multi-attribute preference systems in the choice (Pa) and ranking (Py) decision problematics. From the viewpoint of rough set theory, this approach implies to consider a pairwise comparison table, i.e. an information table whose objects are pairs of actions instead of single actions, and whose entries are binary relations instead of attribute values. From the viewpoint of multi-attribute decision methodology, this approach allows both representation of decision maker’s (DM’s) preferences in terms of “if …then…” rules and their use for recommendation in Pa and Py problematics, without assessing such preference parameters as importance weights and substitution rates. The rule representation of DM’s preferences is alternative to traditionally decision support models. The rough set approach to (Pα) and (Pβ) is explained in detail and illustrated by a didactic example.

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