## 2 Literature Review  
### Research Status  
The main direction of the existing multimodal transport route optimization research is to consider the quality of service and carbon emissions. Considering the cost objective function, the literature used to focus on finding the optimal path considering quality from the perspective of multimodal transport operators, paying attention to the cost of the transportation process, and improving service quality and user satisfaction [11; 12; 13; 14]. [PERSON] [11] proposed a model for calculating the internal and external comprehensive costs of intermodal transport and highway freight transport networks. Considering other consumption in the process of transportation, [PERSON] [12] comprehensively considered factors such as the transportation cost, transportation safety, transportation route, and transportation mode and established a multimodal transportation route selection model with the lowest transportation cost as the objective function. [PERSON] [13] considered a discrete multimodal transport network design problem, established or extended a path to minimize the total operating cost, and summarized the multi-cost problem into a total operating cost, which greatly reduces the computational complexity. [PERSON] [14] considered the transportation and purchase costs of soybeans under the background of the global containerized transportation of soybeans, and a multimodal transport network model was established to optimize the transportation route of soybeans. Most of the above studies only considered the factor of transportation cost, but the evaluation of the route in the operation plan often considered many factors such as transportation time and transportation cost, so it lacked comprehensiveness. [PERSON] [15] constructed an opportunity-constrained programming model for a class of vehicle routing problems considering customer classification, random travel time, random service time, and time window constraints. In addition to pursuing the minimization of transportation time and cost from the perspective of the shipper and from the perspective of the customer, [PERSON] [16] used the dynamic programming method to solve the transportation path. [PERSON] [17] considered all the consumption time in the transportation process to establish a time-related multi-objective optimal path optimization model and gave a variety of adaptive decision preference suggestions, which were more comprehensive. [PERSON] [18] took into account the vehicle routing problem of simultaneous pickup under the condition of time-varying road speed and soft time windows. The path optimization model was established with the goalof minimizing the sum of vehicle dispatching cost, time window penalty cost, and vehicle transportation cost. It added more constraints and emergencies that may be encountered during transportation. Although most of the above studies have conducted research on route integration and considered many factors in route optimization, most of them only considered a single mode of transportation and did not consider the comprehensive optimization of transport routes from the perspective of multimodal transport in combination with the current situation. The existing literature on multimodal transport path optimization mainly focuses on the model and algorithm of a single-task problem with time window constraints [19; 20; 21]. However, the problem of carbon emissions in the transportation process is generally ignored, and most existing studies do not consider the multimodal transport path optimization under multi-task conditions. With the development of science and technology and the demand for green sustainable development, the goal of multimodal transport has changed from considering costs to paying attention to the impact of transportation on the environment. With the development of smart cities, new requirements have been put forward for the control of carbon emissions (CEs) in the transportation system [22; 23; 24].