Intuitionistic Fuzzy PROMETHEE II Technique for Multi-criteria Decision Making Problems Based on Distance and Similarity measures

In multi-criteria decision making (MCDM) methods, if decision makers (DMs) are not able to treat the precise data in order to define their preferences, the intuitionistic fuzzy set (IFS) theory enables them. Therefore, the IFS attributes are connected with the degree of membership and non-membership functions. In this work we propose a new version of the intuitionistic fuzzy PROMETHEE II (IF-PROMETHEE II) method aiming and solving the MCDM problems. A distance and similarity measures are employed to measure the deviations between alternatives on intuitionistic fuzzy sets. We propose to apply the distance and the similarity measure between alternatives to determine the preference matrix. Then, a ranking algorithm is applied to indicate the order of superiority of alternatives. Finally, a practical example is provided for an application of organization evaluations.