Aiming at the problem of express freight scheme decision under multiple uncertain factors, the express freight scheme decision model and decision rule based on intuitionistic fuzzy rough set over two universes were proposed. Based on the intuitionistic fuzzy rough set theory over two universes, a fuzzy approximate space over two universes for express freight scheme decision was determined. The consumption degrees of fixed cost, transportation cost, transfer cost, carbon emission, transfer time and other transportation indices were regarded as intuitionistic fuzzy numbers, and the intuitionistic fuzzy relation between evaluation indices and transportation schemes were used to calculate the lower approximation set and upper approximation set, and the maximum intuitionistic index and Hamming closeness degree were introduced to determine the transportation scheme decision rules. Taking an express freight transportation line from Lanzhou to Beijing as the example, the optimal transportation scheme was selected from the 9 modes of transportation combined by road, ordinary speed railway and air according to the decision rules. Sensitivity analysis of transportation cost and transfer cost was performed to verify the accuracy of the results. The two optimal transportation schemes finally selected show the applicability of the intuitionistic fuzzy rough set over two universes on such problems.

A stochastic optimization method was proposed in order to solve the vehicle number allocation problem of the minimum autonomous vehicle fleet driven by spatio-temporal multi-tasks of terminal delivery. Firstly, the influence of service time and waiting time on the route planning of autonomous vehicle fleet was analyzed to build the shortest route model, and the service sequence network was constructed based on the two-dimensional spatio-temporal network. Then, the vehicle number allocation problem of the minimum autonomous vehicle fleet was converted into a network maximum flow problem through the network transformation, and a minimum fleet model was established with the goal of minimizing the vehicle number of the fleet. Finally, the Dijkstra-Dinic algorithm combining Dijkstra algorithm and Dinic algorithm was designed according to the model features in order to solve the vehicle number allocation problem of the minimum autonomous vehicle fleet. Simulation experiments were carried out in four different scales of service networks, the results show that:under different successful service rates, the minimum size of autonomous vehicle fleet is positively correlated with the scale of service network, and it decreases with the increase of waiting time and gradually tends to be stable, the One-stop operator introduced into the proposed algorithm greatly improves the search efficiency, and the proposed model and algorithm are suitable for the calculation of the minimum vehicle fleet in large-scale service network.