Granulating linguistic information in decision making under consensus and consistency
Cabrerizo, Francisco Javier
Morente-Molinera, Juan Antonio (UNIR)
Tipo de Ítem:Articulo Revista Indexada
This study is concerned with group decision making contexts in which linguistic preference relations are used to provide the evaluations of results. On the one hand, granulation of linguistic terms, which are used as entries of the preference relations, is carried out for the purpose of dealing with the linguistic information. Formally, the problem is expressed as a multi-objective optimization task in which a performance index composed of the weighted averaging of the criteria of consensus and consistency is maximized via an appropriate association of the linguistic terms with information granules formed as intervals. On the other hand, once the linguistic terms are made operational by mapping them to the corresponding intervals, a selection process, in which the consistency achieved by each agent is also considered, is employed with intent to construct the solution to the decision problem under consideration. An experimental study is reported by demonstrating the main features of the proposed approach. Furthermore, some drawbacks and advantages are also analyzed.
Este ítem aparece en la(s) siguiente(s) colección(es)
Mostrando ítems relacionados por Título, autor o materia.
Cabrerizo, Francisco Javier; Morente-Molinera, Juan Antonio (UNIR); Perez, Javier Ignacio; Urena, Raquel; Herrera-Viedma, Enrique (Aggregation Functions in Theory and in Practice, 2018)A Group decision making process is carried out when human beings jointly make an election from a possible collection of alternatives. Here, a question of importance is to avoid winners and losers, in the sense that the ...
Solving multi-criteria group decision making problems under environments with a high number of alternatives using fuzzy ontologies and multi-granular linguistic modelling methods Morente-Molinera, Juan Antonio (UNIR); Kou, G; González-Crespo, Rubén (UNIR); Corchado, J M; Herrera-Viedma, Enrique (Knowledge-Based Systems, 12/2017)Classic multi-criteria group decision making models that have a high amount of alternatives are unmanageable for the experts. This is because they have to provide one value per each alternative and criteria. In this paper, ...
Improving supervised learning classification methods using multi-granular linguistic modelling and fuzzy entropy Morente-Molinera, Juan Antonio (UNIR); Mezei, Jozsef; Carlsson, Christer; Herrera-Viedma, Enrique (IEEE Transactions on Fuzzy Systems, 10/2017)Obtaining good classification results using supervised learning methods is critical if we want to obtain a high level of precision in the classification processes. The training data used for the learning process plays a ...