Integrated Optimization of Aircraft Surface Operation and De-Icing Resources at Multi De-Icing Zones Airport

Since the surface operation of hub airports was facing severe congestion and aircraft delay under the de-icing mode, some practical problems of improving aircraft operation and support efficiency are put forward. A two-phase model is constructed to coordinate the scheduling of aircraft surface operation (ASO) and de-icing support resources operation (DSRO). An optimized method is used to schedule the aircraft surface operation. On the basis of the scheduling results of surface operation, an aircraft and de-icing resource collaborative scheduling (ADCS) mechanism is established to optimize the assignment of aircraft and de-icing resources. The algorithm combining receding horizon control strategy and CPLEX solver (RHC-CPLEX) is designed to solve the model. Computational experiments performed on case studies of Beijing DaXing airport show some potential improvements: Firstly, for the ASO model, the RHC-CPLEX algorithm can reduce the objective function value by more than 20% compared with the FCFS algorithm. And the results shows that not only the delay distributions under different snow conditions are reasonable, but the spatial distributions of the de-icing zones of aircraft are closer to the location of their apron and allocated runway. Secondly, for the DSRO model, the RHC-CPLEX algorithm can reduce the objective function value by more than 6% compared with the algorithm based on the principle of proximity and availability. The de-icing vehicles are used efficiently and the number of refilling de-icing fluid and the free time of the de-icing vehicles can be significantly reduced.