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This paper presents a hybrid method to tackle multiple criteria decision making problems with incomplete weight information in the context of fuzzy soft sets. In order to determine the weights of criteria, we develop a comprehensive two-stage framework. Stage One: We first define the distance between two fuzzy soft numbers. Next, we establish an optimization model based on ideal point of attribute values, by which the attrib-ute weights can be determined. Stage Two: To get the global weights, we use fuzzy cognitive maps to depict the dependent and feedback effect among criteria. Next, we require constructing fuzzy soft set to decide the desirable alternative. Finally, a case study is given to clarify the proposed approach of this paper.