Algorithms for fuzzy multi expert multi criteria decision making (ME-MCDM)

Inherent complexity and uncertainty in a business environment necessitate the participation of many experts in multi criteria decision making. However, participation of many experts makes the conflict aggregation process difficult. To handle this difficulty, we propose two algorithms namely possibility measure and averaging conflict aggregation. In possibility measure, we integrate the possibility theory of fuzzy logic with a maximal containment method that is designed based on the decision problem. Possibility measure algorithm for ME-MCDM involves computationally expensive multiple information processing steps. Therefore to test and compare this algorithm, averaging conflict aggregation algorithm is proposed that requires fewer mathematical information processing steps. Based on the proposed algorithms, a decision support system (DSS) is developed. We present a case study of supplier evaluation to compare both of the proposed algorithms with the help of developed DSS.