Transactions of Nanjing University of Aeronautics & Astronautics
Multi-objective Collaborative Optimization for Scheduling Aircraft Landing on Closely Spaced Parallel Runways Based on
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Abstract:
A scheduling model of closely spaced parallel runways for arrival aircraft was proposed, with multiobjections of the minimum flight delay cost, the maximum airport capacity, the minimum workload of air traffic controller and the maximum fairness of airlines′ scheduling. The time interval between two runways and changes of aircraft landing order were taken as the constraints. Genetic algorithm was used to solve the model, and the model constrained unit delay cost of the aircraft with multiple flight tasks to reduce its delay influence range. Each objective function value or the fitness of particle unsatisfied the constrain condition would be punished. Finally, one hub of a domestic airport was introduced to verify the algorithm and the model. The results showed that the genetic algorithm presented strong convergence and timeliness for solving constraint multiobjective aircraft landing problem on closely spaced parallel runways, and the optimization results were better than that of actual scheduling.
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