A preference learning framework for multiple criteria sorting with diverse additive value models and valued assignment examples

no code implementations • 12 Oct 2019 • Jiapeng Liu, Milosz Kadzinski, Xiuwu Liao, Xiaoxin Mao, Yao Wang

We propose an optimization model for constructing a preference model from such valued examples by maximizing the credible consistency among reference alternatives.

Data-driven preference learning methods for value-driven multiple criteria sorting with interacting criteria

no code implementations • 21 May 2019 • Jiapeng Liu, Milosz Kadzinski, Xiuwu Liao, Xiaoxin Mao

We also propose a few novel methods for classifying non-reference alternatives in order to enhance the applicability of our approach to different datasets.

Using a Segmenting Description approach in Multiple Criteria Decision Aiding

no code implementations • 5 Mar 2019 • Milosz Kadzinski, Jan Badura, Jose Rui Figueira

We discuss the favorable characteristics of the Segmenting Description approach which enhance its suitability for use in Multiple Criteria Decision Aiding.