2-order additive fuzzy measure identification method based on diamond pairwise comparison and maximum entropy principle

Fuzzy measures can flexibly describe the relative importance of decision criterion as well as their interactions in multicriteria decision making. Based on the diamond pairwise comparison, a new identification method of 2-order additive fuzzy measure is proposed. The relative weight and the interaction degree can be obtained simultaneously for every pair of criteria in the diamond pairwise comparison. The Choquet integral-based equivalent alternative curve can help the decision maker estimate the interaction degrees between criteria. The overall importance of each criterion is obtained by the maximum eigenvector method of AHP. According to the maximum fuzzy measure entropy principal, a nonlinear programming is constructed to identify the interaction indices among criteria. Finally, an illustrative example shows the feasibility and validity of the proposed identification method.