Abstract:

In view of the triangular fuzzy number-based uncertain multi-attribute decision making problem with unknown attribute weights, firstly, the new definitions of the similarity degree of the regular triangular fuzzy number and decision-making alternative are given, the similarity degree relation theory of the triangular fuzzy number is presented and some related results are obtained. Secondly, learning the idea of maximizing deviations algorithm rules, a similarity programming model is established to determine the attribute weight based on the similarity degree relation of the triangular fuzzy number. Thirdly, the relative ratio of the similarity degree value between decision-making alternative and the ideal standard is utilized to sort and pick over all decision-making alternatives, then the algorithm of the similarity degree relation for triangular fuzzy number-based uncertain multiple attribute decision making is presented. Finally, the characters between the maximizing deviation algorithm and the proposed algorithm are compared and analyzed by a numerical example, to illustrate the feasibility and effectiveness of the algorithm.