Informatica

This paper presents a multiple-criteria choice model, the circular intuitionistic fuzzy (C-IF) ELECTRE, designed to resolve C-IF ambiguities through built-in circular functions. Joint generalized scoring functions establish contrast relationships between C-IF evaluation values, facilitating concordance and discordance analyses for option ranking. The efficacy of C-IF ELECTRE I and II—leveraging tools such as the prioritization Boolean matrix, average outflows and inflows, and overall net flow—is validated through a multi-expert supplier evaluation, with outcomes benchmarked against alternative methods. A comparative analysis explores the impact of parameter variations, underscoring how integrating C-IF sets with ELECTRE enhances decision-making in complex, multifaceted environments.

In multi criteria Decision Making, the decision maker wants to find the best alternative among a set of alternatives in order to satisfy a set of criteria. Traditionally, decision making models are based on crisp data. The shortcoming of these data in capturing the reality and lack of information persuaded researchers to develop decision making methods with uncertain data. In this paper, the ELECTRE method is extended with black numbers, under ambiguous environment. The proposed method is applied in a supplier selection problem. It's an outstanding method that can be used in real world problems with ill-defined and incomplete data.