A novel measure of intuitionistic fuzzy entropy in multi- criteria decision making problem using TOPSIS

Abstract

Multiple Criteria Decision Making (MCDM) is a decision-making method in which we decide the right decision from a range of viable options based on the comparative or context of specific of a defined system of interrelated or impartial parameters. By giving preferred evidence in the form of an actual real number or a range, a suitable solution may be selected. Therefore, given ambiguous or inaccurate facts, desire info in actual life could be analyzed directly. In certain instances, uncertainty is generated by creators who are ambiguous or inaccurate. Such feature provided researchers with a strong incentive to apply MCDM methods in an uncertain environment. In recent times, TOPSIS is often known about MCDM in several areas. The fuzzy TOPSIS (technique for order preference by similarity to ideal solution) approach and several basic principles are discussed in this paper. The major aim of this paper is to create a novel intuitionistic fuzzy set decision-making method based on a novel fuzzy entropy measure. To begin, create a novel intuitionistic fuzzy entropy measure as well as innovative weighting techniques for intuitionistic multi-criterion decision making by using the attribute values based mostly on the fuzzy based measure. In addition, it develops an intuitionistic fuzzy TOPSIS method for ranking options, and a practical example is provided in which we compare the four universities LPU, Amity University, Chitkara University, and Chandigarh University for the purpose of selecting the best one for admission by using the real data.