Informatica

Determining criteria importance is a crucial task in multi-criteria decision-making problems, and the Best-Worst Method (BWM) has emerged as an effective weighting technique due to its reduced number of pairwise comparisons. Although BWM has been extended to handle group decision-making and linguistic information, existing approaches do not adequately address disagreements among evaluators, which may lead to dissatisfaction with the resulting criteria weights. To address this limitation, this paper proposes a consensus-based BWM for linguistic multi-criteria group decision-making. The proposed approach obtains consensual collective weights by minimally modifying the evaluators’ initial linguistic preferences. The resulting solution can support moderators and evaluators during consensus-reaching processes by facilitating the identification of disagreements and the generation of appropriate recommendations. The proposal is developed within the 2-tuple linguistic framework and provides both numerical and linguistic representations of the resulting weights. In addition, a novel stochastic consistency index is introduced to assess the reliability of evaluators’ preferences. The feasibility and effectiveness of the proposal are illustrated through a real-world case study and analysed by means of comparative and sensitivity analyses.

A complex spherical fuzzy set (CSFS) is a generalization of the spherical fuzzy set (SFS) to express the two-dimensional ambiguous information in which the range of positive, neutral and negative degrees occurs in the complex plane with the unit disk. Considering the vital importance of the concept of CSFSs which is gaining massive attention in the research area of two-dimensional uncertain information, we aim to establish a novel methodology for multi-criteria group decision-making (MCGDM). This methodology allows us to calculate both the weights of the decision-makers (DMs) and the weights of the criteria objectively. For this goal, we first introduce a new entropy measure function that measures the fuzziness degree associated with a CSFS to compute the unknown criteria weights in this methodology. Then, we present an innovative Complex Proportional Assessment (COPRAS) method based on the proposed entropy measure in the complex spherical fuzzy environment. Besides, we solve a strategic supplier selection problem which is very important to maximize the efficiency of the trading companies. Finally, we present some comparative analyses with some existing methods in different set theories, including the entropy measures, to show the feasibility and usefulness of the proposed method in the decision-making process.

This study introduces a new multi-criteria group decision-making model in organ transplant transportation networks under uncertain situations. A new combined weighting approach is presented to obtain expert weights with various kinds of opinions by integrating similarity measure and subjective judgments of experts. Also, the CRITIC approach is given to obtain transportation criteria weights. Finally, a novel integrated ranking approach is proposed to calculate the rank of each alternative based on ideal point solution and relative preference relation (RPR) methods. This study regards an interval-valued intuitionistic fuzzy set to cope with the vagueness of uncertain conditions in a real case study.