TOPSIS method for multiple attribute decision making under fuzzy environment

The aim of this paper is to investigate the multiple attribute decision making problems with triangular fuzzy information, in which the information about attribute weights is completely unknown, and the attribute values take the form of triangular fuzzy numbers. In order to get the weight vector of the attribute, we establish an optimization model based on the maximum deviation, by which the attribute weights can be determined. Then, based on the traditional TOPSIS method, calculation steps for solving fuzzy multiple attribute decision-making problems with completely unknown weight information are given. The weighted distances between every alternative and positive ideal solution and negative ideal solution are calculated. Then, according to the weighted distances, the relative closeness degree to the positive ideal solution is calculated to rank all alternatives. Finally, a numerical example is provided to illustrate the proposed method. The result shows the approach is simple, effective and easy to calculate.