Soft Computing-Based Cutter Layout Design of Rock Tunnel Boring Machine

As a complex design issue, the cutter layout design is one of the key technologies of rock tunnel boring machine (TBM). The expert experience rule knowledge is important for the quality and innovation of the cutter layout scenario. On the basis of summing up the related basic research, engineering practice and domain expert experience for TBM, this paper gives the multiobjective optimization model of the cutter layout. Then a cutter layout design method based on soft computing is studied. In this method, fuzzy logic reasoning is used to express expert experience rule knowledge, imitate the expert reasoning process and obtain the layout districts of the allocated objects. The reasoning outcome corresponds to a rough layout scheme and is input into evolutionary algorithm to evolve with the evolutionary computing program so as to obtain better design scenarios. Finally, an example is given to verify the proposed approach. The obtained results show the inclusion of expert experience knowledge effectively improves the quality of the evolutionary algorithm.