Research On The Method Of Probability Uncertain Multitple Attribute Decision Making

Stochastic multiple attribute decision-making problems (SMADM) with attribute values as trapezoidal fuzzy number or linguistic variables gives a description of fuzzy information in a more general form. Compare to general decision making, SMADM problem includes randomness and ambiguity of attribute, so that it can meticulously denote the decision information and avoid the loss of it.For probability is interval number and attribute is trapezoidal fuzzy number, probability is interval number and attribute is linguistic variables, probability and attribute both are trapezoidal fuzzy number, probability is trapezoidal fuzzy number and attribute is linguistic variables, and probability and attribute both are linguistic variables, this paper researches respectively.First, under condition of probability is interval number and attribute is trapezoidal fuzzy number, transform interval probability to point probability and transform SMADM matrix to no-risk multiple attribute decision-making matrix, and obtain optimum solution using ideal point method. Second, under condition of probability is interval number and attribute is trapezoidal fuzzy linguistic variables, develop interval probability to trapezoidal fuzzy number probability, transform SMADM matrix to no-risk multiple attribute decision-making matrix, and obtain optimum solution using TFLWA method. Third, under condition of both probability and attribute are trapezoidal fuzzy numbers, according to algorithms of trapezoidal fuzzy numbers, transform SMADM matrix to no-risk multiple attribute decision-making matrix, and obtain optimum solution using ideal point method. Forth,under condition of probability is trapezoidal fuzzy numbers and attribute is trapezoidal fuzzy linguistic variables, according to algorithms of trapezoidal fuzzy linguistic variables, transform SMADM matrix to no-risk multiple attribute decision-making matrix, and obtain optimum solution using TFLWA method. Finally, under condition of both probability and attribute are trapezoidal fuzzy linguistic variables, according to algorithms of trapezoidal fuzzy linguistic variables, transform RMADM matrix to no-risk multiple attribute decision-making matrix, and obtain optimum solution using TFLWA method.