Bilevel Programming Model for Joint Scheduling of Arrival and Departure Flights Based on Traffic Scenario

In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of arrival and departure flights is studied systematically.According to the matching degree of capacity and flow,it is determined that the traffic state of arrival/departure operation in a certain period is peak or off-peak.The demands of all parties in each traffic state are analyzed,and the mathematical models of arrival/departure flight scheduling in each traffic state are established.Aiming at the four kinds of joint operation traffic scenarios of arrival and departure,the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established,respectively,and the elitism genetic algorithm is designed to solve the models.The results show that:Compared with the first-come-firstserved method,in the scenarios of arrival peak&departure off-peak and arrival peak&departure peak,the departure flight equilibrium satisfaction is improved,and the runway occupation time of departure flight flow is reduced by 38.8%.In the scenarios of arrival off-peak&departure off-peak and departure peak&arrival off-peak,the arrival flight equilibrium delay time is significantly reduced,the departure flight equilibrium satisfaction is improved by 77.6%,and the runway occupation time of departure flight flow is reduced by 46.6%.Compared with other four kinds of strategies,the optimal scheduling method can better balance fairness and efficiency,so the scheduling results are more reasonable.

Sectorization Model of Terminal Airspace with Arrival and Departure Separation

Terminal airspace(TMA)is the airspace centering several military and civil aviation airports with complex route structure,limited airspace resources,traffic flow,difficult management and considerable airspace complexity.A scientific and rational sectorization of TMA can optimize airspace resources,and sufficiently utilize the control of human resources to ensure the safety of TMA.The functional sectorization model was established based on the route structure of arriving and departing aircraft as well as controlling requirements.Based on principles of sectorization and topological relations within a network,the arrival and departure sectorization model was established,using tree based ant colony algorithm(ACO)searching.Shanghai TMA was taken as an example to be sectorizaed,and the result showed that this model was superior to traditional ones when arrival and departure routes were separated at dense airport terminal airspace.

Three-Dimensional Planning of Arrival and Departure Route Network Based on Improved Ant-Colony Algorithm

In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.

A Combined Arrival and Departure Scheduling for Multi-airport System

A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport system is defined through in-depth analysis of the characteristics of arrival and departure operations.Then,several constraints are taken into account,such as wake vortex separation,transfer separation,release separation,and separation in different runway operational modes.Furthermore,the scheduling model is constructed and simulated annealing algorithm is proposed by minimizing the total delay.Finally,Shanghai multi-airport system is chosen to conduct the simulation and validation.And the simulation results indicate that the proposed method is able to effectively improve the efficiency of arrival and departure operations for multi-airport system.

Optimization study of station track utilization in high-speed railroad based on constraints of control in random origin and process

Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.

考虑Pareto最优的列车运行图与维修天窗协调优化

列车运行图与维修天窗之间的冲突始终无法避免,且维修天窗开设时间的长短显著影响列车总运行时间。针对此问题,综合考虑维修天窗对列车运行造成的限速约束、车站到发线数量约束等,建立列车总运行时间最小,以及维修天窗实际开设时长与理想时长总偏差最小的双目标混合整数规划模型;对困难约束设置中间辅助变量将模型线性化以提高求解效率,并设计约束转换算法求解双目标模型的Pareto最优;微观化处理铁路线,将站内资源和站间资源细化为一系列行车资源单元,得到更加符合实际旅客运输需求的运行图。以某地区铁路线夜间开行列车及维修天窗开设计划为研究背景,调用商业软件求解双目标函数模型的Pareto最优,并对双目标模型的最小支配解和最优支配解进行对比分析;针对最优支配解下的列车进入、离开行车资源单元的时间、停站作业时间及维修天窗的开始时间及开设时长,绘制列车运行图。求解结果表明:模型在满足维修天窗最小开设时长的同时,能够兼顾列车运行总时间最小和维修天窗开设时长更充裕。基于最优支配解绘制的列车运行图表明:微观路网下的列车运行时刻表优化结果更符合实际旅客运输生产作业需要。研究结果可为铁路运营管理部门进一步优化列车运行图编制与维修天窗开设提供参考。

基于VMD和GA-SVM的矿井地震自适应噪声压制方法

煤矿井下地震信号往往呈现出复杂的波场特性且伴随着大量噪音干扰,导致地震信号的初至拾取精度降低,从而影响地震数据的反演与解释。针对复杂干扰环境下采集的低信噪比地震信号,提出了基于变分模态分解(VMD)和遗传算法优化支持向量机(GA-SVM)的地震噪声压制与初至提取方法,以提高煤矿井下复杂噪声条件下的地震信号质量。采用变分模态分解对含噪地震信号进行自适应分解,得到数个的变分模态分量(IMF);对VMD分解得到的IMF分量进行特征提取,将提取所得的信号特征作为信号有效性判别的依据;利用遗传算法对支持向量机模型进行优化,得到最优的惩罚因子c与核函数参数g;利用优化后的支持向量机模型对IMF分量进行有效性判别并将有效分量重构成高信噪比信号;通过对人工加噪的地震信号应用噪声压制算法,煤矿井下常见的不同类型噪声被有效地压制,验证了算法的可行性;对矿井巷道实采的地震记录进行噪声压制处理,有效地压制了数据中的干扰噪声,极大程度地提高了地震记录的信噪比,使初至拾取得更加准确。结果表明,基于VMD和GA-SVM的地震噪声压制方法可以很好地提取含噪地震记录中的有效信号,提高初至拾取精度,在矿井复杂干扰条件下具有显著的应用潜力,对解决矿井复杂干扰条件下的地震勘探问题有重要意义。

双高铁路集装箱办理站列车作业模式仿真

以上下装载两层高箱为特点的双层高集装箱具有装载能力更强、成本更低的优势,是未来铁路货运的重要发展方向。为提高我国首个双高集装箱办理站——苏溪双高铁路集装箱办理站的作业效率,在传统“调机调车”列车作业模式的基础上提出了“直到直发”作业模式,建立FlexSim仿真模型,基于多项影响办理站列车到发作业效率的重要评价指标分析和比较两种装卸作业模式的优劣。两种作业模式的流程分析及仿真结果显示,“直到直发”作业模式相比于“调机调车”作业模式,具有作业时间短、成本低、效率高的明显优势,是未来铁路双高集装箱办理站的重要推广方向。

信控交叉口借道左转设计的延误优化研究

为准确分析交叉口借道左转设计的左转延误,针对现有的延误模型的不足,建立一个合适的延误优化模型,并提升其设置的科学性。先对逆向车道长度进行优化;再通过分析左转车辆的累计到达驶离曲线,以左转总延误最小为优化目标,建立一种新的考虑预信号延误的优化模型;最后,以长沙市芙蓉中路一个交叉口为实例,进行验证,分析左转到达流率对借道左转设计延误的影响及逆向车道长度对左转车均延误的影响。研究结果表明:左转流率越大,越能充分发挥借道左转设计的优势,该模型的左转延误下降可达59.21%;当左转流量偏低时,预信号位置的延误占比较大,随着左转流量的增大,传统车道和逆向车道的延误占比逐步增加。该研究可以准确评价借道左转设计的实用性和优劣程度,对借道左转设计的推广与应用具有重要意义。

高速铁路区间完全中断场景双向到发线运用优化

针对高速铁路区间完全中断场景下的列车运行调整问题,提出了双向到发线运用优化策略。从宏观角度将列车运行过程抽象为由事件和活动构成的网络,对提出的双向到发线运用策略进行建模,建立高速铁路区间完全中断场景下列车运行调整混合整数线性规划(MILP)模型。根据现场实时性要求,采用自编算法与商业优化软件Gurobi相结合的方式对模型进行求解。运用模型和算法对构建的9个现场中断案例进行算例测试。结果表明,双向到发线运用优化策略可以有效减少中断事件对列车运行的影响,相比于目前到发线运用策略,最多可减少10%的列车延误时间。

考虑动车组周转和到发线运用的高铁列车运行多计划协同调整

随着我国高速铁路快速发展,“八纵八横”高铁路网加密成型,呈现出运行环境复杂、行车密度高及长交路跨线运营等典型特征.一旦遭受大风、红光带、接触网挂异物和设备故障等突发事件,则将导致列车偏离运行计划,进而影响到发线运用和动车组(Eletric multiple units,EMU)周转计划.如何在调整运行图的同时保证动车组和到发线运用的可行性是提高列车运行调整效率的关键.针对区间双向中断场景下到发线运用冲突和动车组接续计划失效问题,采用取消列车、变更列车到发时刻、更换到发线、备用动车组接续等策略对运行图、动车组和到发线运用计划进行调整.基于事件−活动网络建立考虑动车组接续和到发线运用的列车运行协同调整模型,设计两阶段求解方法对模型求解.运用京津城际实际数据对模型和方法进行仿真验证,结果表明相比于先到先服务(First come,first served,FCFS)策略,多计划协同调整策略能有效降低列车晚点时间.与整体求解方法相比,两阶段求解方法能够保证模型求得解的质量且有效提高模型求解效率.

始增时间差在肺周围型病变良恶性鉴别中的应用价值

目的:探讨始增时间差(T_(AT))在肺周围型病变良恶性鉴别中的应用价值。方法:选取CT发现肺周围型病变且行超声造影检查的50例患者,按病理结果分为恶性组29例及良性组21例。观察2组病变的二维超声图像及超声造影图像,TIC对造影定量参数进行分析。结果:①单因素分析示,2组病变始增时间(AT_(2))、T_(AT)及造影增强模式差异均有统计学意义(均P<0.05);②logistic回归模型示,T_(AT)与肺周围型病变的良恶性密切相关,且呈正相关(β=0.316,P<0.05);③绘制T_(AT)及AT_(2)的ROC曲线,AUC分别为0.750、0.710,最佳截断值分别为2.0、12 s,敏感度分别为93.1%、82.8%,特异度分别为61.9%、66.5%。结论:T_(AT)在鉴别肺周围型病变的良恶性方面具有较高的敏感度,当T_(AT)<2.0 s时倾向诊断为良性病变,而≥2.0 s时倾向诊断为恶性病变,值得临床推广。

基于时间聚类推理的立体车库车位分配策略研究

采用立体车库车辆到达-离去时间数据,通过k-means聚类方法依据不同时段存取车到达频率对车辆进行类别划分,以立方聚类标准为评价指标对划分可信度进行评估。以车辆到达-离去时间划分推理结果及I/O至待存取车位的设备总服务时间与停留时间长短关系,建立立体车库车位分区分配数学模型。定义顾客平均等待时间为立体车库效率评价指标,仿真对比分析就近分配与本文设计聚类推理分区分配的效率指标。仿真结果表明:本文设计的分配策略相较于就近分配策略能有效缩短顾客等待时间,表现为顾客等待时间减少9.5%。研究结果为此类车库车位分配过程提供参考,为提高车库运行效率提供决策支持。

深圳枢纽西丽站站场平面布置方案研究

研究目的:西丽站衔接4条高标准铁路,具有客流量大、车站规模大、车流结构复杂等特点。其站场布置对于确保列车高效顺畅到发、实现点线能力协调起着关键作用。对西丽站站场方案的研究,旨在探讨大型客站站场平面布置的设计方法和技术路线,为类似项目的设计提供借鉴和参考。研究结论:(1)研究大型客站的站场平面布置,首先,应该根据车站作业量和列车开行方案,分析确定车站性质和站场规模;其次,在考虑引入线路特点和车站运营特征的基础上,通过多方面的综合比选,选择出最合理的站型方案;然后,对咽喉布置进行优化,确保配备足够的平行进路,并制定合理的到发线分工,以提高车站的作业效率;最后,通过进行车站能力适应性分析,验证所选方案的合理性;(2)作为深圳枢纽的主要客站,西丽站主要办理各引入线路动车组列车的始发终到和立折作业,采用线路别合场布置方案是合适的,车站的设计能力也能够满足运输的需求;(3)本文技术路线和研究成果可为类似项目中大型客运站站型及站场平面布置的研究提供参考借鉴。

铁路客运站占线程序图自动化推演系统的开发与应用

为改善铁路客运站基于计算机手动绘制占线程序图的现状,提高客运站日常工作绘图效率,确保客运站到发线运用方案编制的合理性,设计了铁路客运站占线程序图自动化推演系统。构建占线程序图动态绘制算法及仿真流程,实现占线程序图动态绘制、到发线运用方案实时评价及机车车辆作业过程推演。在中国铁路沈阳局集团有限公司大连站的仿真应用表明,该系统简化了占线程序图绘制过程,可实时判断并量化评价方案中存在的冲突,为客运站工作人员编制、优化到发线运用方案提供参考。

考虑铁路旅客偏好差异的离站方式选择行为分析

为探究铁路旅客对离站方式的行程费用、在车时间、候车时间和车厢拥挤度等服务水平因素的偏好差异及其原因,运用混合Logit模型和潜在类别条件Logit模型从个体和群体层面展开分析。首先,基于铁路旅客出行特点和离站交通方式服务水平,以同行人数、行李负载、行程费用、在车时间、候车时间和车厢拥挤度作为情景变量,通过正交设计法生成意愿调查问卷;然后,在线上和线下开展调查;最后,采用极大似然估计标定模型参数。结果表明:行程费用、在车时间、候车时间和车厢拥挤度是影响离站方式选择的关键因素。混合Logit模型标定结果显示,旅客对行程费用和在车时间具有不同于样本均值的个体偏好差异。潜在类别条件Logit模型将旅客划分为3类:类别1的旅客对在车时间、候车时间和车厢拥挤度最为敏感,而类别3的旅客对这3项服务水平因素的敏感性最低。两模型从不同角度证实了旅客对离站交通方式服务水平的偏好差异及其对离站方式选择的影响,为铁路客运枢纽接驳交通方式配置和服务水平优化提供了参考。

不确定跑道入侵情景下的进离场航班排序优化模型

假设可估计各个跑道入侵事件持续时间的出现概率,考虑专机、要客、普通航班等不同航班类型对延误和备降处理的优先级差异,建立不确定情景下的多跑道运行模式进离场航班排序优化模型,选择部分普通进场航班去备降机场,将剩下的航班分配给相对应跑道,计算这些进离场航班的实际起飞或降落时间,在优先保障专机和要客航班进离场情形下,尽可能减少普通航班的延误成本。根据问题特征,设计求解问题的多阶段并行分布式启发式算法。最后,结合一个真实案例,给出了最佳方案,并揭示入侵事件、不同优先级类型的航班数量和航班延误之间的内在关系,从而验证模型的正确性。

双基地米波MIMO雷达低空目标俯仰维DOD和DOA联合估计方法

对于双基地米波多输入多输出(MIMO)雷达低空目标俯仰维测向场景,受多径效应影响,发射接收导向矢量因存在耦合现象而与噪声子空间失去正交性,导致以多重信号分类(MUSIC)为主的子空间类算法在该场景下不可用,而基于空间平滑预处理的子空间类算法由于阵列孔径损失存在角度估计精度不高的问题。为解决上述难题,建立了双基地米波MIMO雷达单目标和非相干多目标镜面反射信号模型,在信号模型数学变换和分析的基础上发现了一种仍旧与噪声子空间正交的导向矢量矩阵,然后利用新的导向矢量矩阵结合广义MUSIC和最大似然算法提出了双基地米波MIMO雷达低空目标俯仰维波离方向和波达方向联合估计方法,最后通过仿真验证了所提方法的有效性和俯仰维测向性能的优越性。

考虑计划分配优先级与干扰条件的编组站阶段计划自动编制研究

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基于起降场漏斗形空域分层结构的无人机进离场程序设计

无人机在城市物流、智慧城市建设等多场景取得成功应用,在城市区域的高密度运行已成趋势。考虑空域结构、无人机性能、起降场特征、外围衔接航路等因素,针对城市场景无人机起降场,提出一种满足可悬停、进离场混合运行的漏斗形起降场空域及相应的进离场程序设计方法。首先,根据国内外研究现状,参考有人机成熟经验,结合无人机特征提出漏斗形空域结构设计的方法,给出进离场程序设计中的关键因素;接着以某市无人机物流配送应用场景为仿真工况,设计其典型起降场空域进离场程序,评价结果显示该程序具有较低的延误水平和安全风险。基于空域分层结构设计的无人机进离场程序可以适应起降场的高密度运行,并具有较高的效率和安全系数。