In this paper, a modified TOPSIS (techniques for order preference by similarity to ideal solution) approach for
solving bi-level multi-objective programming (BL-MOP) problems with fuzzy parameters is presented. These fuzzy
parameters are assumed to be characterized by fuzzy numerical data, reflecting the experts' imprecise or fuzzy understanding
of the nature of the parameters in the problem formulation process. Firstly, the corresponding non-fuzzy bi-level programming
model is introduced based on the
-level set. Secondly, a modified TOPSIS approach is developed, in which the fuzzy goal
programming (FGP) approach is used to solve the conflicting bi-objective distance functions instead of max-min operator. As
the FGP approach utilized to achieve the highest degree of each membership goal by minimizing the sum of the unwanted
deviational variables. Finally, an algorithm to clarify the modified TOPSIS approach, as well as Illustrative numerical example
and comparison with the existing methods, are presented.