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中文摘要：
分析了目标机场到场容量和到场需求的随机特性,以所有航班总的延迟费用最小为目标函数,以先到先服务原则、机场到场容量限制、地面等待和空中延迟的关系为约束条件,建立了机场流量管理中地面等待问题的数学规划模型和事件驱动模型。运用基本的遗传算法求解模型,得出了优化后航班的具体到场时间。计算结果表明：单位时间的空中延迟和地面等待费用比越大,空中延迟越容易被转化为地面等待;当单位时间的空中延迟和地面等待费用比为3∶1时,优化后的航班延迟总费用下降50%;当单位时间的空中延迟和地面等待费用比为1∶1时,空中延迟和地面等待时间的比值约为1.058;当单位时间的空中延迟和地面等待费用比为6∶1时,空中延迟只有地面等待时间的4.77%。优化后,航班的到场分布更加均衡,优化结果将更为精确。
英文摘要：
The stochastic features of arrival capacity and arrival demand for target airport were analyzed.The minimum total flight delay cost was taken as objective function,the principle of first come first service,the limits of airport arrival capacity and the relation between groundholding and air-delay were considered as constraint conditions,and the mathematical programming model and event-driven model of grounding-holding problem in airport flow management were built.The basic genetic algorithm was designed to solve the models,the concrete arrival times after optimization were calculated.Calculation result shows that the bigger the ratio of unit air-delay cost to unit ground-holding cost is,the more easily the air-delay turns to ground-holding.When the ratio of unit air-delay cost to unit ground-holding cost is 3∶1,the total delay costs reduce by 50%after optimization.When the ratio of unit air-delay cost to unit ground-holding cost is 1∶1,the time ratio of air-delay to ground-holding is about 1.058.When the ratio of unit air-delay cost to unit ground-holding cost is 6∶1,the time ratio of air-delay to ground-holding is about 4.77%.After optimization,the flight arrival distribution is more statuesque,and the optimized result is more accurate.4tabs,19figs,19refs.
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