Passenger transport safety evaluation plays a very important role in the development of China’s railway. In order to obtain the optimal indicator weight in railway passenger transport safety evaluation, firstly, fuzzy theory and analytic hierarchy process are combined in this study to provide the change interval of each evaluation Indicator weight and generate different weights in every interval. Then it will generate evaluation results for different indicator weights through the simulation experiment of Monte Carlo Simulation and get the variance of evaluation results through quantitative methods. At last, the variance will be treated as the fitness function of genetic algorithm to do backward feedback to realize the optimization of indicator weight, and optimized weight will be used in the calculation of passenger safety evaluation result of all kinds of China’s railway companies. The experimental results show that the method can fine tune the weights on the basis of full respect of the experts’ evaluation of the index weights, and make the evaluation results more actually reflecting the safety management level of the railway company.
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