Discrete choice models with Atanassov-type intuitionistic fuzzy membership degrees

In the real word, due to the existence of uncertainty in decision-making information, it is often difficult to accurately evaluate utility values of alternatives. Recently, a series of discrete choice models based on fuzzy subjective utility have been proposed. Specifically, utility evaluation of each alternative has been expressed by fuzzy membership grades. However, traditional fuzzy membership function has only considered supporting degree, but has not considered the degrees of opposition and indeterminacy involved in decision makers' evaluations. In this paper, a series of novel discrete choice models based on Atanassov-type intuitionistic fuzzy set are proposed, in which membership degrees, non-membership degrees, and hesitation degrees are simultaneously taken into account to jointly express the utility evaluations. Moreover, the attitudinal character of decision mak-ers and relative weights of attributes are also considered to further extend the proposed models. Compared with existing discrete choice models, these new models are more flex-ible and general, which increase the applicability of discrete choice models for decision -making under an uncertain and imprecise environment. Two real-world case studies are given to illustrate the effectiveness and rationality of the new models.(c) 2022 Elsevier Inc. All rights reserved.

Automated summary

A series of novel discrete choice models based on Atanassov-type intuitionistic fuzzy set are proposed in this paper, which consider membership degrees, non-membership degrees, and hesitation degrees simultaneously to express utility evaluations. The proposed models also take into account the attitudinal character of decision makers and relative weights of attributes to enhance their applicability in decision-making under uncertain and imprecise conditions. Two real-world case studies are presented to demonstrate the effectiveness and rationality of the new models.