Expressiveness and robustness measures for the evaluation of an additive value function in multiple criteria preference disaggregation methods: an experimental analysis
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Publication:1652412
DOI10.1016/j.cor.2017.05.011zbMath1394.90348OpenAlexW2615126436MaRDI QIDQ1652412
Mohammad Ghaderi, Núria Agell, Miłosz Kadziński, Jakub Wąsikowski
Publication date: 11 July 2018
Published in: Computers \& Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cor.2017.05.011
decision analysisadditive value functionpairwise comparisonexperimental studydiscretization procedurespreference disaggregation
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Cites Work
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- Multiple criteria decision analysis. State of the art surveys. In 2 volumes
- Using Choquet integral as preference model in interactive evolutionary multiobjective optimization
- Levels of incomplete information in group decision models -- a comprehensive simulation study
- Learning criteria weights of an optimistic Electre Tri sorting rule
- Scoring procedures for multiple criteria decision aiding with robust and stochastic ordinal regression
- Learning non-monotonic additive value functions for multicriteria decision making
- Can a linear value function explain choices? An experimental study
- A multi-criteria sorting procedure with Tchebycheff utility function
- Multicriteria decision model for outsourcing contracts selection based on utility function and ELECTRE method
- ACUTA: a novel method for eliciting additive value functions on the basis of holistic preference statements
- Simple procedures of choice in multicriteria problems without precise information about the alternatives' values
- Assessing a set of additive utility functions for multicriteria decision- making, the UTA method
- A linear programming approach for learning non-monotonic additive value functions in multiple criteria decision aiding
- Selection of a representative set of parameters for robust ordinal regression outranking methods
- A PROMETHEE-based approach to portfolio selection problems
- Resolving inconsistencies among constraints on the parameters of an MCDA model
- Robust ordinal regression in preference learning and ranking
- Preference inference with general additive value models and holistic pair-wise statements
- Building a set of additive value functions representing a reference preorder and intensities of preference: GRIP method
- On the concept of decision aiding process: an operational perspective
- NON-NORMALITY AND TESTS ON VARIANCES
- Preference disaggregation: 20 years of MCDA experience.
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