Intermodal transportation, as an efficient form of transport organization, is a key technology and means for the logistics industry to balance transport costs and efficiency. How to deeply analyze the key factors constraining the level of development of multimodal transportation in China, building multimodal transportation development evaluation index system and evaluation model, evaluating comprehensively the multimodal transportation development level in China, and putting forward targeted countermeasures is of great practical significance. Based on the hesitant fuzzy multiattribute decision-making method, this paper analyzes the key factors influencing the level of multimodal transportation development from the perspective of sea-rail intermodal transport and further uses the interval number discretization and likelihood deviation maximization multiattribute decision-making method to construct a mixed-data index evaluation model, which is combined with data from 11 provinces (cities) in China. The study shows that there is a big gap among different provinces (cities) in China concerning the level of multimodal transportation development. Besides, the volume of intermodal container transportation and railway mileage are the core factors affecting the level of multimodal transportation development, and the results of the evaluation model can objectively reflect the level of multimodal transportation development and problems in each province (city). The research results further enrich the theoretical system of intermodal transportation development and provide a reference for the relevant management departments in formulating intermodal transportation plans and policies by putting forward pertinent suggestions in the field of management. In the future, the research direction should include the ecological environment, economic benefits, and other indicators into the evaluation system, expand the research scope of the modes of combined transportation such as public rail transport and public air transport, and improve the applicable scope of the evaluation model and the evaluation capability of specific scenarios.

The optimal intermodal nodes and routes are two of the most challenging issues for intermodal participants. We present a two-phase approach that includes the fuzzy c-means clustering method (FCM) and a multi-objective optimization model to solve intermodal location-routing issues. A weighted sum technique and a genetic algorithm (GA) are designed to address this model. The two-phase approach is beneficial in meeting different market demand preferences of intermodal participants. It also has applications in solving the sustainable intermodal location-routing problems, further solving the network optimization problem in large-scale scenarios. A typical intermodal transport network in the Bohai Rim region is used to verify the effectiveness of this approach. The results provide references for the participants in the Bohai Rim region to choose the optimal intermodal nodes and routes. The findings also offer theoretical insights for optimizing intermodal networks in other regions of China, with goals of improving sustainable transport efficiencies.