Ordinal regression revisited: multiple criteria ranking with a set of additive value functions

We present a new method (called UTAGMS) for multiple criteria ranking using strongly and weakly established weak preference relations which result from an ordinal regression. The preference information supplied by the decision maker is a set of pairwise compar- isons of reference alternatives. The preference model built via ordinal regression is a set of general additive value functions. The method provides two final rankings: a strong ranking identifying "sure" preference statements, and a weak ranking identifying "possi- ble" preference statements. In order to build these two rankings, the method takes into account all value functions compatible with the preference information. The UTAGMS method is intended to be used interactively, with progressive statement of pairwise com- parisons. Moreover, the method can support the decision maker also when his/her pref- erence statements cannot be represented in terms of an additive value function. The method is illustrated by an example solved using the UTAGMS software. Some extensions of the method are also presented.

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Field Value
Source https://hal.science/hal-00957531
Author Greco, Salvatore, Mousseau, Vincent, Slowinski, Roman
Maintainer CCSD
Last Updated May 6, 2026, 02:20 (UTC)
Created May 6, 2026, 02:20 (UTC)
Identifier hal-00957531
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Università degli studi di Catania = University of Catania (Unict)
creator Greco, Salvatore
date 2005-09-09T00:00:00
harvest_object_id 13e057d2-979c-4a46-95d9-582454760a74
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-06-13T00:00:00
set_spec type:UNDEFINED