Abstract: An outranking approach for hybrid multiple attribute decision making based on cumulative prospect value and membership is presented. Firstly, the psychological behavioral factors of decision makers are considered, and the expectation of each criterion is chosen as the reference point. Then, the hybrid decision matrix with clear numbers, interval numbers and linguistic assessment terms is transformed into the decision matrix of gains or losses relative to the decision maker's expectation. Furthermore, a fuzzy pattern recognition model is built based on weighted euclidean distance between each alternative solution and decision maker's expectation. In order to obtain the optimal membership and weight vector, a Lagrange relaxation function is proposed by using cross iterative computations. By synthesizing the comprehensive prospect value and membership, a ranking of each alternative solution is determined. Finally, an oil pipeline route selection example is used to demonstrate how to apply the proposed procedure and comparative studies show its overall ranking consistency.

Key words: multiple attribute decision making, prospect theory, fuzzy pattern recognition, membership