A multiple objective optimization model for aircraft arrival and departure scheduling on multiple runways

Area of Science:

• Operations Research
• Aviation Management
• Computer Science

Background:

• Air traffic management faces challenges in optimizing runway assignments and flight schedules.
• Minimizing flight delays and maximizing runway utilization are critical objectives.
• The complexity of flight scheduling problems (NP-hard) requires advanced optimization techniques.

Purpose of the Study:

• To develop a multi-objective mixed integer linear programming (MOMILP) model for flight-to-runway assignment and time determination.
• To simultaneously minimize flight delays and maximize runway utilization.
• To account for unique runway operational modes and inter-runway interference.

Main Methods:

• Formulation of a multi-objective mixed integer linear programming (MOMILP) model.
• Development of a heuristic-based non-dominated sorting genetic algorithm II (NSGA-II) to solve the NP-hard problem.
• Definition of coding structure and heuristic algorithms for initial population generation in NSGA-II.

Main Results:

• The proposed MOMILP model effectively balances flight delays and runway utilization.
• The NSGA-II algorithm provides Pareto-optimal solutions for complex scheduling scenarios.
• A real-world example validated the model's correctness and demonstrated trends between flight delays and runway idle times.

Conclusions:

• The developed MOMILP model and NSGA-II algorithm offer an effective approach to air traffic flow management.
• Optimizing runway operations and flight scheduling can significantly improve airport efficiency.
• The study provides valuable insights for enhancing air traffic control systems.