Fuzzy TODIM for ELICIT Information

Abstract

The available information in some decision situations may be vague or imprecise, and the involvement of human experts, who usually manage qualitative information, results essential to address the underlying uncertainty in such contexts. However, human decision-makers are rationally bounded, particularly when the decision processes involve risk and uncertainty. To model human stakeholders’ behavior in such situations, the TODIM method (Portuguese acronym for Interactive Multi-Criteria Decision-Making) based on the Prospect Theory was developed to address multi-criteria decision-making (MCDM) situations. Even though the classic TODIM method was adapted to manage fuzzy information and, consequently, to model uncertainty by using linguistic labels, that proposal neglected the management of more complex linguistic expressions able to represent the experts’ hesitancy among several linguistic labels, which is quite common due to the increasing complexity of decision problems. Therefore, this contribution introduces a multi-criteria group decision-making (MCGDM) model based on fuzzy TODIM dealing with Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT) values, which were recently proposed to model such hesitancy and perform precise computations without losing the interpretability of linguistic information.

This work is partially supported by the Spanish Ministry of Economy and Competitiveness through the Spanish National Project PGC2018-099402-B-I00, and the Postdoctoral fellow Ramón y Cajal (RYC-2017-21978), the FEDER-UJA project 1380637 and ERDF, by the Spanish Ministry of Science, Innovation and Universities through a Formación de Profesorado Universitario grant (FPU2019/01203) and by the Junta de Andalucía, Andalusian Plan for Research, Development, and Innovation (POSTDOC 21-00461).