The intermodal express network of high-speed railways and highways can fully utilize the flexibility of highways and the advantages of high-speed railways, such as low cost, high efficiency, and low carbon emission. This paper studies the hub location and flow assignment problem in the intermodal express network of high-speed railways and highways, which can not only increase the transportation efficiency but also provide door-to-door service. Considering the characteristics of multiple modes, flow balance, carbon emission, capacity constraints, and time constraints in the intermodal express network, a mixed-integer linear programming model is proposed with the objective of minimizing the total cost by determining the hub locations, allocations, mode selections, and flow assignments. Owing to the NP-hard computational complexity, an improved genetic algorithm with local search is designed by combining the genetic operators and two optimization strategies to solve the problem effectively. Lastly, numerical experiments are conducted to validate the feasibility of the model and the effectiveness of the algorithm.