For cargo airlines, in the face of a large number of complicated air cargo demands, formulating reasonable route planning and distribution schemes can reduce transportation costs and improve transportation effciency. We established a mixed integer programming model that integrates transport capacity allocation and cargo flow distribution and took Air China Cargo as an example to solve the model, in which airlines can use their self-owned cargo aircraft or outsourcing service for transportation. We proposed two data processing ways: pre-allocating cargo flow according to different transportation distances and pre-specifying transit airports according to OD pairs, which not only reduces the search space, but also saves 85.12% of the calculation time compared to the situation without data processing. The total length of freight transportation path and the turnover of transit freight flow are also reduced by 17.19% and 28.99% compared with non-preprocessing, which reduces a large number of detours. Compared with the model without outsourcing, the integrated model saves 4.87% of the cost. Then the outsourcing price coeffcient was introduced for sensitivity analysis. As the outsourcing price coeffcient decreases from 1.2 to 0.8, the outsourcing cargo volume increases. At the same time, the flight segments operated by small aircraft decrease, and the flight segments allocated to large aircraft do not change. Finally, we analyzed the curves of unit transportation cost varying with transportation volume on the same flight segment for different modes of transportation, which provides a reference for airlines to respond to the temporary segment demand, and provides a better solution according to curves and residual transport capacity without changing the overall plan.