Improved max-min algorithm of fuzzy synthetic

To overcome the disadvantages of max-min algorithm of fuzzy synthetic evaluation and to enhance its quality. An improved maxmin algorithm of fuzzy synthetic evaluation was propsoed. By adjusting the total sum of the weights of index, the more data of the relation matrix were used than the oringal max-min algorithm widely used before, the reliability rised, and the application scope enlarged. The mathmetical model of determination of the total amount of the weight was presented. The examples show the validity of the model at the rule of hamming distance, Euclidean distance and Cbcbyshev dsitance of the evaluation results of the improved and original max-min algorithm. The six general models with the problem were given in the end, which mainly considered the originality or varidation of the date of the evaluation results, or the distances such as hamming, Euclidean and Cbcbyshev of the evaluation results of the weight average algorithm to the given algorithm.