关键词: 航空运输, 航路资源分配优化, Benders分解算法, 协同航迹选择计划, 多目标优化

Abstract: To improve the participation between control and airlines in collaborative decision-making and reduce flight delays, this paper proposes a multi-objective trajectory slot allocation model considering airline preferences to solve the problem of route resource allocation with multiple restricted zones. The model aims to meet capacity constraints, minimize flight delays, and minimize the associated costs of rerouting as efficiency and fairness objectives. The study applied the model to a domestic route instance data and used the Benders decomposition algorithm to analyze and solve the model. The results show that compared with traditional ground waiting methods, the total delay cost per minute of flights was significantly reduced by 6.2%. Due to the reduction of ground delay caused by diversion allocation, the total delay time of flights was reduced by 29.3%. This result emphasizes the importance of increasing rerouting (except for ground waiting) to avoid airspace restricted areas. In addition, the model allows airlines to flexibly choose original or alternative routes based on their own preferences, and analyzes the impact of airline preferences on individual and system delay levels. At last, the trade-off between efficiency and fairness in multi constrained resource allocation under different fairness schemes was discussed. The proposed Min-Max method can improve airspace operational efficiency by 5.4% and airline fairness by 70.8% compared to existing RBS (Ration-By-Schedule) methods. It can be seen that the proposed multi-objective collaborative route allocation optimization method is effective in solving the problem of collaborative route resource allocation, taking into account the fairness of various airlines while reducing the total delay cost.

Key words: air transportation, optimization of route resource allocation, Benders decomposition algorithm, collaborative trajectory options program, multi-objective optimization