【作者】 陈欣；

【导师】 朱金福；

【作者基本信息】 南京航空航天大学 ， 交通运输规划与管理， 2007， 博士

【摘要】 随着航空运输业的飞速发展,航空需求不断增加。处于航班运输系统陆空节点位置的机场也越来越繁忙并面临着越来越大的压力。国内一半以上的枢纽机场和干线机场的设计保障能力已进入超饱和或接近饱和状态。诸多研究表明空中交通网络拥挤的主要原因在于机场空侧容量不足。如何确切把握机场系统的运营规律和交通特性,掌握机场运营管理关键技术,提高机场系统的运营水平,是机场管理当局和空中交通管理部门普遍关心的问题。本论文对机场空侧容量评估和容量优化进行了研究。容量评估是机场规划和设计中的首要步骤,它能够为管理者们正确把握机场系统运行规律和特性提供帮助。容量优化研究就是通过分析飞机在机场的运行特点,建立正确的数学模型,以优化利用现有资源和提高机场容量。在容量评估研究方面,本文将机场空侧看作一个系统,综合考虑各子系统容量的相互影响,通过分析飞机运行流程,建立了空侧容量评估仿真模型。利用ServiceModel开发了某国际机场的容量评估仿真系统,分析了不同航空需求下的机场容量和延误水平,确定了限制容量的瓶颈环节。在容量优化研究方面:一、用区间数表示容量并引入满意度准则,建立了机场空侧容量利用和流量分配的多目标优化模型。实例研究表明,通过对进离港航班流量需求的协调分配,减少了航班延误。给定时段内所有航班需求得到满足,实现了容量的有效利用和流量的合理分配,为机场终端区不同的容量利用和流量调度提供了帮助。二、以减少着陆飞机队列完成时间为优化目标,设计了求解飞机排序问题(ASP)的蚁群优化算法。通过正交试验确定了算法的性能参数组合并验证了ASP蚁群算法求解问题的可行性和求解效果。研究结果表明,ASP蚁群算法得到的优化排序可以使着陆队列完成时间减少约14%,跑道容量和利用率得到有效提高,可以缓解终端区拥堵压力。三、设计了一种针对枢纽机场的停机位指派问题的排序模拟退火算法。首先根据停机位期望偏好值和航班客座率进行排序以得到模拟退火算法的初始解,然后运用经典模拟退火算法求解出最优指派结果。结果表明,排序模拟退火算法的计算精度优于经典模拟退火算法,计算效率优于CPLEX软件且具有较快的收敛速度,为实时解决枢纽机场停机位优化指派问题提供了新思路。四、快速高效地处理机场安全事故对恢复机场容量有较大帮助。通过分析机场空侧滑行道地面网络,创建了描述空侧网络拓扑结构的节点、弧段关系数据库,利用VB和MapX开发了机场飞行区应急救援决策支持系统,为机场安全事故管理的可视化、便捷化提供了支持。更多还原

【Abstract】 With fast development of air transportation industry, the traffic demand has increased greatly. The airports, which are the network nodes of air transportation system connecting land and sky, become busier and busier and get more pressures. The designed capacity of more than half of domestic hub airports and main airports has been over-saturated or nearly saturated. The airside capacity is the main cause of air traffic congestion, which has been proved by many researches. The airport authorities and air traffic management departments have focused mainly on how to master the key techniques of airport operation and management, and how to improve operation level of airport system.This paper studied methods for airport airside capacity evaluation and capacity optimization. Capacity evaluation is the first step for airport planning and design, which can provide help for airport managers to grasp the airport operation rules and characteristics. Capacity optimization is to analyze aircraft activity properties at airport and to build correct mathematical models for optimal utilization of airport resources and airport capacity improvement.With respect to airside capacity evaluation, the airside was regarded as an integrated system and the simulation model of airside capacity evaluation was built by analyzing the process of aircraft at airside. With this model, a simulation system of capacity evaluation was developed for an international airport. Airport capacity and delay level were analyzed under different air traffic demands and the bottleneck was found.With respect to capacity optimization of airside, the contents conclude:Firstly, capacity was described by interval number. Multi-objective model of airside capacity utilization and traffic flow assignment was built by introducing utilization satisfaction level. It was indicated by numerical example research that the traffic delay has been reduced through coordinated assignment of air traffic flow demand. All flight demands were assigned at the given period and an effective capacity utilization and rational assignment were realized, which provide help for different management of capacity utilization and traffic flow assignment at airport terminal.Secondly, With the objective of minimizing the completion time of landing aircraft queue, an ant colony optimization algorithm(ACOA) for aircraft sequencing problem(ASP) was designed. The orthogonal test was employed to study the optimal parameters of ACOA for ASP. The feasibility and effectiveness had been verified. The results showed that completion time of landing queue could be decreased by 14% with the optimal sequence obtained by ACOA for ASP. The runway capacity and utilization was improved efficiently and congestion pressure at airport terminal was alleviated.Thirdly, Gate assignment problem(GAP) at hub airport was investigated by the simulated annealing algorithm integrated with sorting approach. The initial solution of the proposed algorithm was obtained by sorting each gate preference value and flight load factor, then the optimal solution was achieved by the traditional simulated annealing algorithm. It was indicated by the numerical example study that the simulated annealing algorithm integrated with sorting approach had better results precision than that of traditional simulated annealing algorithm, the computation efficiency was better than that of CPLEX and the convergence rate was more acceptable. The proposed algorithm can provide a new way to resolve the GAP at hub airports.Finally, to efficiently and quickly treat airport safety accident is helpful for airport capacity recovery. The network of airport airside was analyzed. A node-arc relation database was built to describe the airside network topology. Based on the above, Visual Basic and MapX were used to develop the Emergency Rescue Decision Support System for a domestic large-scale airport. The system can provide visualization and convenience supports for airport safety accident management.更多还原