In order to ease congestion and ground delays in major hub airports, an aircraft taxiing scheduling optimization model is proposed with schedule time as the object function. In the new model, the idea of a classical j...In order to ease congestion and ground delays in major hub airports, an aircraft taxiing scheduling optimization model is proposed with schedule time as the object function. In the new model, the idea of a classical job shop-schedule problem is adopted and three types of special aircraft-taxi conflicts are considered in the constraints. To solve such nondeterministic polynomial time-complex problems, the immune clonal selection algorithm（ICSA） is introduced. The simulation results in a congested hour of Beijing Capital International Airport show that, compared with the first-come-first-served（FCFS） strategy, the optimization-planning strategy reduces the total scheduling time by 13.6 min and the taxiing time per aircraft by 45.3 s, which improves the capacity of the runway and the efficiency of airport operations.展开更多
基金Supported by the Basic Scientific Research Projects of the Central University of China(ZXH2010D010)the National Natural Science Foundation of China(60979021/F01)~~
文摘In order to ease congestion and ground delays in major hub airports, an aircraft taxiing scheduling optimization model is proposed with schedule time as the object function. In the new model, the idea of a classical job shop-schedule problem is adopted and three types of special aircraft-taxi conflicts are considered in the constraints. To solve such nondeterministic polynomial time-complex problems, the immune clonal selection algorithm（ICSA） is introduced. The simulation results in a congested hour of Beijing Capital International Airport show that, compared with the first-come-first-served（FCFS） strategy, the optimization-planning strategy reduces the total scheduling time by 13.6 min and the taxiing time per aircraft by 45.3 s, which improves the capacity of the runway and the efficiency of airport operations.
