Airliner stowage is a key step in aircraft service. With the industrial Internet development and the higher requirements of the aviation industry for its own service, the efficiency of manual stowage operations has decreased, and the airport operation businesses will inevitably develop towards automation and intelligence, so will the digitalization of airliner stowage. Some of the existing algorithms cannot adapt to the multi-constraint and variable environment of airliner stowage and rely on the manual adjustments by ground staff. Therefore, the structural analysis of the constraints involved in the stowage environment and the stowage process is carried out in this study, and the constraint compensation dynamic scoring solution is proposed based on the genetic algorithm. The test results show that different stowage results can be obtained according to different constraints, so as to optimize the center of gravity shifts and real-time stowage calculation. On the basis of this, the scalability of the system structure is ensured, so the system can adapt to various new models and new requirements.