【作者】 王宇；

【导师】 钟翠萍；

【作者基本信息】 吉林大学 ， 管理科学与工程， 2021， 硕士

【摘要】 改革开放四十年来,中国民航业破除体制束缚,重新焕发生机与活力,助力新中国经济社会发展。航空运输市场的高质量发展推动着空中交通流量的持续增长。然而,我国现有的空管系统不再适应日益增加的流量管理工作,出现终端区空域拥挤,空中交通秩序失灵等问题。单跑道机场的容量已经达到饱和状态,并且很多不具备增设跑道的资源条件。同时,在恶劣天气(如雷雨、暴雪、冻雾等)的影响下,某些航班无法在目标机场正常降落,只能备降到相关机场。这要求机场要具备一定的备降航班保障能力,切实保障备降到该机场的航班安全降落。当前空中交通管制员指挥航班起降作业时,多依靠自身的主观经验,或者传统的先到先服务规则,具有片面性和不准确性,容易造成航班大规模延误。所以,采取科学合理的方法来安排航班起降顺序具有十分重要的意义。文章将研究对象扩展为本机场正常起降航班和非紧急备降航班。在航班排序过程中,考虑时间窗、尾流安全间隔、降落优先级约束条件,以最小化航班加权滞后和为研究目标,设计进离场航班的排程方法。对比已有的航班调度文献,可以证明本文的研究问题是NP-hard问题。文章首先介绍了民航领域的专业知识点,加深读者理解。然后将混合整数线性规划公式与航班调度联系在一起,构建基本的线性规划数学模型。但是在合理时间内,数学模型不具有求解大规模现实问题的能力,需要利用有效的智能算法。因此,本文将Metropolis接受准则与标准的分布估计算法结合,提出改进的分布估计算法(IEDA)。在查阅与本问题相似研究成果的基础上,文章选择模先到先服务规则(FCFS)、模拟退火算法(SA)、局部搜索算法(CGLS)与本文所提算法作比较,通过大量实验验证IEDA算法的有效性。文章的实验数据来自两方面:一方面是产生于计算机仿真的800组模拟数据,另一方面是采集自长春进近管制区的1组实验数据。对于随机生成的模拟数据,文中设计了两种不同的场景做对比实验:飞机数量规模较小的场景和飞机数量规模较大的场景。这是因为基本的数学模型能在限定时间内求得小规模问题最佳解,可以与其他三种方法(IEDA、SA、CGLS)的求解结果做差值比较,正确评价算法的求解效果。实验结果表明,无论是小规模还是大规模数据实验,改进的分布估计算法都能高效解决进离场航班调度问题,不仅能有效改进目标函数值,还具有较强的整体性能。更多还原

【Abstract】 Over the past 40 years of reform and opening up,China’s civil aviation industry has broken free of institutional constraints,regained its vigor and vitality,and helped the economic and social development of New China.The high-quality development of the air transport market is driving the continuous growth of air traffic flow.However,my country’s existing air traffic control system no longer adapts to the ever-increasing flow management work,and there are problems such as congestion in the airspace of the terminal area and failure of air traffic order.The capacity of single-runway airports has reached saturation,and many do not have the resource conditions for additional runways.At the same time,under the influence of severe weather(such as thunderstorms,blizzards,freezing fog,etc.),certain flights cannot land normally at the target airport and can only alternately land to the relevant airport.This requires the airport to have a certain ability to guarantee alternate flights,and effectively guarantee the safe landing of alternate flights to the airport.Air traffic controllers currently rely on their own subjective experience when directing flight take-off and landing operations,or the traditional first-come,first-served rule,which is one-sided and inaccurate,and is likely to cause large-scale flight delays.Therefore,it is very important to adopt a scientific and reasonable method to arrange the flight sequence.The article expands the research object to normal take-off and landing flights and non-emergency alternate flights at the airport.In the flight sequencing process,considering the time window,wake safety interval,maximum allowable transition displacement,and landing priority constraint conditions,with the research goal of minimizing the weighted lag of the flight,the scheduling method of incoming and outgoing flights is designed.Compared with the existing flight scheduling literature,it can be proved that the research problem in this paper is an NP-hard problem.The article first introduces the professional knowledge points in the field of civil aviation to deepen readers’ understanding.Then the mixed-integer linear programming formula is linked with flight scheduling to construct a linear programming mathematical model.However,within a reasonable time,mathematical models do not have the ability to solve large-scale real-world problems,and effective intelligent algorithms are needed.Therefore,this paper combines the Metropolis acceptance criteria with the standard distribution estimation algorithm,and proposes an improved distribution estimation algorithm(IEDA).Based on the research results similar to this problem,the article selects the first-come,first-served rule(FCFS),simulated annealing algorithm(SA),and local search algorithm(CGLS)to compare with the algorithm proposed in this paper.A large number of experiments verify the effectiveness of the IEDA algorithm.The experimental data of the article comes from two aspects: on the one hand,800 sets of simulated data generated by computer simulation,and on the other hand,a set of experimental data collected from the Changchun approach control area.For the randomly generated simulation data,two different scenarios are designed for comparison experiments: a scenario with a smaller number of aircraft and a scenario with a larger number of aircraft.This is because the basic mathematical model can obtain the optimal solution for a small-scale problem within a limited time,and can be compared with the solution results of the other three methods(IEDA、SA、CGLS)to correctly evaluate the solution effect of the algorithm.The experimental results show that whether it is a small-scale or large-scale data experiment,the improved distribution estimation algorithm can efficiently solve the problem of inbound and outbound flight scheduling.It can not only effectively improve the objective function value,but also has a strong overall performance.更多还原