UTA Plus

This method may be used to solve problems of choice or of multi criteria classification on set A of actions. It constructs a utility function from a preorder defined by the user on a subset A’ of the reference actions. The procedure, based on a principle of ordinal regression, consist in solving a small linear program. The program provides piecewise linear functions of marginal utility that are as compatible as possible with the given preorder. The user can modify the marginal utility functions within limits given by a sensitivity analysis of the ordinal regression problem. There is a friendly user interface in which to make these changes. The utility function given by the user is then used to define a preorder on the set A of actions.

References in zbMATH (referenced in 137 articles )

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  1. Angelopoulos, Dimitrios; Siskos, Yannis; Psarras, John: Disaggregating time series on multiple criteria for robust forecasting: the case of long-term electricity demand in Greece (2019)
  2. Dias, Luis C.; Vetschera, Rudolf: On generating utility functions in stochastic multicriteria acceptability analysis (2019)
  3. Belahcène, K.; Labreuche, C.; Maudet, N.; Mousseau, V.; Ouerdane, W.: An efficient SAT formulation for learning multiple criteria non-compensatory sorting rules from examples (2018)
  4. Costa, Ana Sara; Figueira, José Rui; Borbinha, José: A multiple criteria nominal classification method based on the concepts of similarity and dissimilarity (2018)
  5. Hu, Jian; Bansal, Manish; Mehrotra, Sanjay: Robust decision making using a general utility set (2018)
  6. Ishizaka, Alessio; Siraj, Sajid: Are multi-criteria decision-making tools useful? An experimental comparative study of three methods (2018)
  7. Karakaya, G.; Köksalan, M.; Ahipaşaoğlu, S. D.: Interactive algorithms for a broad underlying family of preference functions (2018)
  8. Özpeynirci, Selin; Özpeynirci, Özgür; Mousseau, Vincent: An interactive algorithm for multiple criteria constrained sorting problem (2018)
  9. Sobrie, Olivier; Gillis, Nicolas; Mousseau, Vincent; Pirlot, Marc: UTA-poly and UTA-splines: additive value functions with polynomial marginals (2018)
  10. Trdin, Nejc; Bohanec, Marko: Extending the multi-criteria decision making method DEX with numeric attributes, value distributions and relational models (2018)
  11. Wang, Haichao; Lahdelma, Risto; Salminen, Pekka: Complementary judgment matrix method with imprecise information for multicriteria decision-making (2018)
  12. Yousfi-Halimi, Naouel; Radjef, Mohammed Said; Slimani, Hachem: Refinement of pure Pareto Nash equilibria in finite multicriteria games using preference relations (2018)
  13. Argyris, Nikolaos; French, Simon: Nuclear emergency decision support: a behavioural OR perspective (2017)
  14. Belahcene, Khaled; Labreuche, Christophe; Maudet, Nicolas; Mousseau, Vincent; Ouerdane, Wassila: Explaining robust additive utility models by sequences of preference swaps (2017)
  15. Benabbou, Nawal; Perny, Patrice; Viappiani, Paolo: Incremental elicitation of Choquet capacities for multicriteria choice, ranking and sorting problems (2017)
  16. Branke, Juergen; Corrente, Salvatore; Greco, Salvatore; Gutjahr, Walter: Efficient pairwise preference elicitation allowing for indifference (2017)
  17. Ciomek, Krzysztof; Kadziński, Miłosz; Tervonen, Tommi: Heuristics for selecting pair-wise elicitation questions in multiple criteria choice problems (2017)
  18. Ghaderi, Mohammad; Ruiz, Francisco; Agell, Núria: A linear programming approach for learning non-monotonic additive value functions in multiple criteria decision aiding (2017)
  19. Kadziński, Miłosz; Ghaderi, Mohammad; Wąsikowski, Jakub; Agell, Núria: Expressiveness and robustness measures for the evaluation of an additive value function in multiple criteria preference disaggregation methods: an experimental analysis (2017)
  20. Qi, Xiuli; Yin, Chengxiang; Cheng, Kai; Liao, Xianglin: The interval cognitive network process for multi-attribute decision-making (2017)

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