机场流量管理中地面等待问题优化模型

王来军; 胡大伟; 高扬; 史忠科

机场流量管理中地面等待问题优化模型

1.
长安大学汽车学院, 陕西西安 710064
2.
西北工业大学自动化学院, 陕西西安 710072

基金项目:

国家自然科学基金项目 60134010

陕西省自然科学基金项目 2012JM8036

中央高校基本科研业务费专项资金项目 CHD2010JC032

中央高校基本科研业务费专项资金项目 CHD2011TD015

中央高校基本科研业务费专项资金项目 CHD2012JC015

详细信息

作者简介:
王来军(1976-), 男, 陕西兴平人, 长安大学副教授, 工学博士, 从事交通规划研究

中图分类号: V355
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- 被引次数: 0
出版历程
- 收稿日期: 2014-01-07
- 刊出日期: 2014-06-25

Optimization model of ground-holding problem in airport flow management

1.
School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China
2.
School of Automation, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China

More Information

Author Bio:
WANG Lai-jun (1976-), male, associate professor, PhD, +86-29-82334426, 54506314@qq.com

摘要

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。
- 机场流量管理 /
- 地面等待 /
- 到场容量 /
- 到场需求 /
- 遗传算法
Abstract: 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.
- airport flow management /
- ground-holding /
- arrival capacity /
- arrival demand /
- genetic algorithm

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图 1 求解流程

Figure 1. Solution flow

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图 2 工况1下到场航班数量

Figure 2. Arrival flight amounts under condition 1

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图 3 工况2下到场航班数量

Figure 3. Arrival flight amounts under condition 2

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图 4 工况3下到场航班数量

Figure 4. Arrival flight amounts under condition 3

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图 5 工况4下到场航班数量

Figure 5. Arrival flight amounts under condition 4

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图 6 工况5下到场航班数量

Figure 6. Arrival flight amounts under condition 5

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图 7 工况6下到场航班数量

Figure 7. Arrival flight amounts under condition 6

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图 8 工况1下的延迟

Figure 8. Delays under condition 1

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图 9 工况2下的延迟

Figure 9. Delays under condition 2

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图 10 工况3下的延迟

Figure 10. Delays under condition 3

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图 11 工况4下的延迟

Figure 11. Delays under condition 4

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图 12 工况5下的延迟

Figure 12. Delays under condition 5

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图 13 工况6下的延迟

Figure 13. Delays under condition 6

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图 14 工况1下的到场时间

Figure 14. Aarrival times under condition 1

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图 15 工况2下的到场时间

Figure 15. Aarrival times under condition 2

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图 16 工况3下的到场时间

Figure 16. Aarrival times under condition 3

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图 17 工况4下的到场时间

Figure 17. Aarrival times under condition 4

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图 18 工况5下的到场时间

Figure 18. Aarrival times under condition 5

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图 19 工况6下的到场时间

Figure 19. Aarrival times under condition 6

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表 1 到场容量样本量

Table 1. Arrival capacity samples

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表 2 到场需求样本量

Table 2. Arrival demand samples

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表 3 延迟时间与费用对比

Table 3. Comparison of delay cost

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表 4 优化结果

Table 4. Optimization results

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参考文献(19)

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