A Large Neighborhood Search Algorithm with Simulated Annealing and Time Decomposition Strategy for the Aircraft Runway Scheduling Problem

The runway system is more likely to be a bottleneck area for airport operations because it serves as link between the air routes and ground traffic. As key problem of traffic flow management, aircraft scheduling (ARSP) great significance improve utilization runways reduce delays. This paper proposes large neighborhood search algorithm combined with simulated annealing receding horizon control strategy (RHC-SALNS) which used solve ARSP. In framework annealing, process embedded, including breaking, reorganization local processes. could expand range building in solution space. A divide original into several subproblems further solving efficiency. proposed RHC-SALNS solves ARSP instances taken from actual operation data Wuhan Tianhe Airport. parameters were determined by parametric sensitivity analysis. Moreover, compared existing algorithms excellent performance large-scale ARSP, showing that model are correct efficient. achieves better optimization results problems.