Linear Programming Computational Procedures for Ordinal Regression
Journal of the ACM (JACM)
Decision Support and Expert Systems: Management Support Systems
Decision Support and Expert Systems: Management Support Systems
The Possible and the Necessary for Multiple Criteria Group Decision
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
Consensus models for AHP group decision making under row geometric mean prioritization method
Decision Support Systems
Selection of a representative value function in robust multiple criteria sorting
Computers and Operations Research
Selection of a representative set of parameters for robust ordinal regression outranking methods
Computers and Operations Research
Multiple Criteria Hierarchy Process in Robust Ordinal Regression
Decision Support Systems
Dominance-based rough set approach for groups in multicriteria classification problems
Decision Support Systems
Stochastic ordinal regression for multiple criteria sorting problems
Decision Support Systems
Robust ordinal regression in preference learning and ranking
Machine Learning
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We introduce the principle of robust ordinal regression to multiple criteria group decision, and we present two new methods using a set of additive value functions as a preference model, called UTA^G^M^S-GROUP and UTADIS^G^M^S-GROUP. With respect to the set of decision makers (DMs), we consider two levels of certainty for the results. The first level is related to the necessary or possible consequences of indirect preference information provided by each DM, whereas the other refers to the subset of DMs agreeing for a specific outcome. In this way, we investigate spaces of consensus and disagreement between the DMs. The proposed methods are illustrated by examples showing how they can support real-world group decision.