Multiattribute Decision Making Based on Entropy under Interval-Valued Intuitionistic Fuzzy Environment

Abstract EN

Multiattribute decision making (MADM) is one of the central problems in artificial intelligence, specifically inmanagement fields.

In most cases, this problem arises from uncertainty both in the data derived from the decisionmaker and the actions performed in the environment.

Fuzzy set and high-order fuzzy sets were proven to be effectiveapproaches in solving decision-making problems with uncertainty.

Therefore, in this paper, we investigate theMADM problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy(IVIF) set (IVIFS).

We first propose a new definition of IVIF entropy and some calculation methods for IVIF entropy.

Furthermore, we propose an entropy-based decision-making method to solve IVIF MADM problems with completelyunknown attribute weights.

Particular emphasis is put on assessing the attribute weights based on IVIF entropy.

Instead of the traditional methods, which use divergence among attributes or the probabilistic discrimination of attributesto obtain attribute weights, we utilize the IVIF entropy to assess the attribute weights based on the credibilityof the decision-making matrix for solving the problem.

Finally, a supplier selection example is given to demonstratethe feasibility and validity of the proposed MADM method.