Aiming at the operation conflict problem of multi-objective, multi-path and multi-vehicle relay during mine locomotive operation under complex geological conditions, a mine operation of locomotive modeling method based on an object-oriented stratified timed Petri net is proposed. In order to load and transport materials as object oriented, which are combined with the mine operation of locomotive rules and time constraints, stratified modeling of an underground roadway route is carried out. In addition, given token time parameters to describe the dynamic behavior of the locomotive, through the model to analyze the operation of a mine transport locomotive, the correlation matrix and accessibility tree analysis are used to study the conflict. Taking the actual operation of a locomotive in a complex mine in Guizhou as an example, the operation of locomotive behavior model was established to detect the interval and time of operation conflicts. The experimental results show that the proposed operation of locomotive modeling and conflict analysis method are effective and feasible, and have important application value to the safe operation of a mine production system.

In an attempt to solve the problems of the low intelligent distribution degree and high working intensity of auxiliary transportation systems in underground coal mines, an intelligent distribution strategy of materials in the whole mine is put forward. Firstly, combined with the characteristics of materials and standard containers, a three-dimensional loading model is established with the goal of maximizing the space utilization of standard containers, and a three-dimensional space segmentation heuristic algorithm is used to solve the material loading scheme. Then, the multi-objective optimization model of distribution parameters is established with the goal of the shortest delivery distance, the shortest delay time, and the fewest number of delivery vehicles, and the dual-layer genetic algorithm is used to solve the distribution scheme. Finally, the spatiotemporal conversion coefficient is designed to solve the task list by hierarchical clustering, and the solution time is reduced by 30%. The results show that the dual-layer genetic algorithm based on hierarchical clustering has good adaptability in complex material scheduling scenarios.