An Integrated Fuzzy Topsis Method for Ranking Alternatives and Its Application

The main purpose of this paper is to develop an integrated fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method to improve the quality of decisionmaking for ranking alternatives. The proposed fuzzy TOPSIS method mainly accounts for the classification of criteria, the integrated weights of criteria and sub-criteria, and the performance values of decision matrix. In this model, the criteria are classified into subjective criteria and objective ones. The fuzzy analytic hierarchy process approach and the entropy weighting method are used to solve the subjective weights and objective ones. In addition, the adjusted integration weights are measured by combining these two methods. The performance values of subjective criteria and of objective ones will be obtained by linguistic expressions and objective evaluation values, respectively. Furthermore, the graded mean integration representation method and the modified distance method are employed to the integrated fuzzy TOPSIS method. Finally, a hypothetical example of partner selection of a shipping company is designed to demonstrate the computational process of this fuzzy TOPSIS algorithm.