The main research content of this paper is an assistant decision-making system for emergency handling of traffic accidents in urban rail. The system is to further improve the ability of rail transit control departments to deal with emergencies through its design and application. The system can automatically judge the accident parameters and analyze the main information of the accident during the application process to put forward a systematic solution to traffic accidents, and thus reasonably arranging for urban rail train dispatching during the accident. Besides, combined with the train's normal operation, the system will collect train emergency prediction data during its application, and visualize the predicted information to provide references for the adjustment of emergency plans, further reducing possible hazards. Meanwhile, this article demonstrates the system's application with the combination of metro line 3, which ends with a satisfying result. It can be considered that the designed assistant decision-making system has practical value and can adjust train operation plans and predict passenger flow.

Aiming at the optimization problem of dangerous goods distribution routes in multi-distribution centers with time windows under uncertain environment. Proposes a robust optimization method with robust control parameters comprehensively considers the transportation risks of dangerous goods. Transportation expenses and service time windows, Constructs a multi-objective double-layer robust optimization model of dangerous goods distribution routes, Upper layer model tracing for minimizing transportation risks and transportation costs, the lower model adopts the user equilibrium traffic allocation model; According to Bert Simas-Sim and Robust Optimization Theory. Robust Equivalence Transformation of Upper Model with Uncertain Parameters; Joint Enhancement, Pareto, Genetic Algorithm and Frank-Wolfe Algorithms, a multi-objective solution is constructed. The hybrid algorithm of standard double-layer robust optimization model, adopts 3 segment coding and decoding method allele matching crossover operation and inversion mutation genetic operation method to solve the upper layer model, adopts frank-Wolfe algorithm to solve the lower layer user equilibrium model; take classic sioux-falls and traffic network as an example XZ80 16 Case Analysis of Dangerous Goods Distribution Route Optimization Problem with 3 Distribution Centers 7 Demand Points, to Verify Rationality of Model and Its Algorithm. Research results show that the hybrid algorithm: when the robust control parameters are 0 30 and 60 and, can quickly obtain 32 and 3 groups of robust optimal solutions respectively, and all solutions are distribution schemes including specific transportation sections and departure times, instead of delivery order; compared with traditional two-stage heuristic algorithm saves 54 in operation time 74%. The hybrid algorithm is better than two-stage heuristic algorithm, in solving efficiency, and expression form of solution. It can better complete multi-objective and double-layer robust optimization task of dangerous goods distribution path in uncertain environment 

Co-delivery can effectively improve the utilization of logistics resources and reduce logistics costs. Under this environment, this paper proposes a vehicle routing problem with order selection. Transportation companies can entrust transportation orders to cooperative enterprises or accept orders issued by cooperative enterprises. At the same time, order selection and vehicle path optimization are needed. In order to optimize the economic benefits of the enterprise, a mixed integer programming model is established. A genetic algorithm is designed to solve this NP-Hard problem, and the chromosome coding of the problem is proposed. An accurate segmentation algorithm to obtain the structure of feasible solutions. This paper constructs examples of different scales and uses Matlab to carry out numerical experiments. The results show that the transportation enterprises can effectively reduce the driving distance of vehicles and improve the enterprise through the two-way entrustment of orders. The economic benefits provide a theoretical basis for the analysis of individual behavior in the common distribution system.