Collaborative Aircrafts Scheduling Strategy in Metroplex Terminal Area Based on FS-MOPSO

To solve the collaborative scheduling problem for arrival aircrafts in metroplex terminals, a discrete optimization model was proposed under ration-by-schedule (RBS). The model focuses on improving scheduling fairness between airlines based on collaborative decision-making (CDM) to seek a best scheduling strategy. By analyzing the fix and runway double restraints and keeping the RBS order as far as possible by minimizing the number of each flight's reversals, the model realized the muilt-objectives of improving the scheduling fairness and minimizing the total delay and the total amount of flights overtaking. In addition, fuzzy self-correction multi-objectives particle swarm optimization (FS-MOPSO) was used to solve the model. As a case study, the scheduling problem for arrival aircrafts in Shanghai metroplex was simulated by the proposed method to verify its effectiveness. The results show that the collaborative scheduling strategy can reduce the total delay time by 22.53% compared to the traditional strategy, and the decrease the variance of reversals by 26.31% compared to the genetic algorithm aimed at minimizing the delay time only.