A new ranking method based on TOPSIS and possibility theory for multi-attribute decision making problem

Abstract This paper presents a new ranking method to deal with asymmetric uncertainty information for multi-attribute decision making problem. The uncertainty information of the multi-attribute decision making can be expressed by possibility distribution, and it can be measured to the profit and investment on an organization. In the new ranking method, three coefficients of possibilistic distribution are introduced in order to incorporate a measurement of the uncertainty information firstly. Then the possibilistic mean matrix, possibilistic standard variance matrix and possibilistic skewness matrix are constructed, and the positive ideal solution and the negative ideal solution of decision matrix are determined. Finally, a composite closeness coefficient of each alternative is calculated by separation measure between each alternative in order to rank the preference order of all alternatives and select the most suitable one. Two case studies of tailings dam have been shown to demonstrate the feasibility and efficiency of the presented method.