VisualUTA

Ordinal regression revisited: multiple criteria ranking with a set of additive value functions. VisualUTA is the first implementation of the UTA^GMS method for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. The preference information provided by the decision maker is a set of pairwise comparisons on a subset of alternatives A^R, called reference alternatives. The preference model built via ordinal regression is a set of all additive value functions compatible with the preference information. Using this model, one can define two relations in the set A: the necessary weak preference relation (strong outranking) which holds for any two alternatives a, b from set A if and only if for all compatible value functions a is preferred to b, and the possible weak preference relation (weak outranking) which holds for this pair if and only if for at least one compatible value function a is preferred to b. These relations establish a necessary (strong) and a possible (weak) ranking of alternatives from A, being, respectively, a partial preorder and a strongly complete and negatively transitive relation. The UTA^GMS method is intended to be used interactively, with an increasing subset A^R and a progressive statement of pairwise comparisons. When no preference information is provided, the necessary weak preference relation is a weak dominance relation, and the possible weak preference relation is a complete relation. Every new pairwise comparison of reference alternatives is enriching the necessary relation and it is impoverishing the possible relation, so that they converge with the growth of the preference information. Moreover, the method can support the decision maker also when his/her preference statements cannot berepresented in terms of an additive value function.


References in zbMATH (referenced in 43 articles , 1 standard article )

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  1. Greco, Salvatore (ed.); Ehrgott, Matthias (ed.); Figueira, José Rui (ed.): Multiple criteria decision analysis. State of the art surveys. In 2 volumes (2016)
  2. Kadziński, Miłosz; Ciomek, Krzysztof; Rychły, Paweł; Słowiński, Roman: Post factum analysis for robust multiple criteria ranking and sorting (2016)
  3. Deparis, Stéphane; Mousseau, Vincent; Öztürk, Meltem; Huron, Caroline: The effect of bi-criteria conflict on matching-elicited preferences (2015)
  4. Giarlotta, Alfio: Normalized and strict NaP-preferences (2015)
  5. Kadziński, Miłosz; Ciomek, Krzysztof; Słowiński, Roman: Modeling assignment-based pairwise comparisons within integrated framework for value-driven multiple criteria sorting (2015)
  6. Roszkowska, Ewa; Wachowicz, Tomasz: Application of fuzzy TOPSIS to scoring the negotiation offers in ill-structured negotiation problems (2015)
  7. Spyridakos, Athanasios; Yannacopoulos, Denis: Incorporating collective functions to multicriteria disaggregation-aggregation approaches for small group decision making (2015)
  8. Cailloux, Olivier; Tervonen, Tommi; Verhaegen, Boris; Picalausa, François: A data model for algorithmic multiple criteria decision analysis (2014)
  9. Corrente, Salvatore; Figueira, José Rui; Greco, Salvatore: Dealing with interaction between bipolar multiple criteria preferences in PROMETHEE methods (2014)
  10. Corrente, Salvatore; Figueira, José Rui; Greco, Salvatore: The SMAA-PROMETHEE method (2014)
  11. Giarlotta, Alfio: A genesis of interval orders and semiorders: transitive NaP-preferences (2014)
  12. Giarlotta, Alfio; Watson, Stephen: The pseudo-transitivity of preference relations: strict and weak $(m,n)$-Ferrers properties (2014)
  13. Greco, Salvatore; Mousseau, Vincent; Słowiński, Roman: Robust ordinal regression for value functions handling interacting criteria (2014)
  14. Hurson, Christian; Siskos, Yannis: A synergy of multicriteria techniques to assess additive value models (2014)
  15. Kadziński, Miłosz; Corrente, Salvatore; Greco, Salvatore; Słowiński, Roman: Preferential reducts and constructs in robust multiple criteria ranking and sorting (2014)
  16. Montes, Ignacio; Miranda, Enrique; Montes, Susana: Decision making with imprecise probabilities and utilities by means of statistical preference and stochastic dominance (2014)
  17. Podinovski, Vladislav V.: Decision making under uncertainty with unknown utility function and rank-ordered probabilities (2014)
  18. Spliet, Remy; Tervonen, Tommi: Preference inference with general additive value models and holistic pair-wise statements (2014)
  19. van Valkenhoef, Gert; Tervonen, Tommi; Postmus, Douwe: Notes on “Hit-and-run enables efficient weight generation for simulation-based multiple criteria decision analysis” (2014)
  20. Vetschera, Rudolf; Weitzl, Wolfgang; Wolfsteiner, Elisabeth: Implausible alternatives in eliciting multi-attribute value functions (2014)

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