Evaluating environmental quality in Tunisia using Fuzzy CODAS SORT method

COmbinative Distance-based Assessment (CODAS) method, which is relatively a new MCDM technique, aims to select the alternative having the largest Euclidean and Taxicab (Hamming) distances to the negative-ideal point. CODAS-Sort, a recently introduced sorting variant, uses crisp class-assignment of alternatives. This can sometimes be misleading, especially for alternatives near the border of two classes. This paper aims at making the class assignment process in CODAS-Sort more flexible by using fuzzy sets theory, it can facilitates, soft transitions between classes and provide additional information about the membership of alternatives in each class that can be used to fine-tune actions beyond the crisp sorting process. This essentially complements the ordinal information of its crisp variant with cardinal information as the degree of membership of an alternative to each class. We use linguistic variables and trapezoidal fuzzy numbers to extend the CODAS method. The applicability of the proposed approach is illustrated in a case study that regards the classification of Tunisian towns according to their quality of environment.