Genetic Algorithm-Based Intelligent Selection Method of Universal Shield Segment Assembly Points

Abstract

The proportion of universal segment in tunnel construction is constantly increasing. A key factor affecting the quality of tunnel construction is the selection of the shield segment assembly points. Nevertheless, the quality and efficiency of the current manual selection method cannot be guaranteed. To realize a high correct rate, high efficiency and intelligence of universal segment assembly points selection, an intelligent selection method of assembly points is proposed. First, the objective function is established by considering the thrust cylinder stroke and shield tail gap differences. Second, to adaptively optimize the weights of the objective function, the working conditions are divided into 81 intervals, and a genetic algorithm is proposed to optimize weights in each interval. Third, a Monte-Carlo-based method is proposed to generate an example dataset, which is used for the genetic algorithm to optimize the weights. Finally, the proposed method was applied to the segment assembly points selection for Line 8 of the Zhengzhou rail transit in China. The results show that the method of assembly segment selection can reach a 90.6% correct rate in the field. The research results of this paper can be used for the selection of the universal shield segment assembly points.