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 complexi...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.展开更多
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 proces...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.展开更多
近年来,中国民航持续高速发展,预计“十四五”末期中国民航运输机场数量将达到270个以上,逐步实现运输机场网络化覆盖。然而,由于机场之间空间分布过于密集而形成的机场集群式效应,造成邻近空域之间存在着复杂的耦合作用关系,若不能在...近年来,中国民航持续高速发展,预计“十四五”末期中国民航运输机场数量将达到270个以上,逐步实现运输机场网络化覆盖。然而,由于机场之间空间分布过于密集而形成的机场集群式效应,造成邻近空域之间存在着复杂的耦合作用关系,若不能在空间和时间上对机场群内各资源进行充分解耦,则难以提升整体运行安全和效率。当前运行优化技术主要侧重于各自局部单一资源的优化,并没有统筹考虑内部跨区域的约束条件以及跨业务的运行环境,因此仅能得到局部最优化管制策略。为解决机场群全局集中式运行协同规划的实际需求,对集成进离场与场面运行(integrated arrival and departure and surface operations,IADS)技术展开综述。首先,从进场、离场和场面局部运行优化技术出发,分析中外研究近况并指明现存问题及研究局限;其次,创新性地对集成进离场与场面运行概念与技术总-分结构进行阐述,系统性说明IADS内在成分和逻辑关联;最后,分别从宏-微观尺度详细描述IADS所涉及的联合进场-离场调度排序问题、机场场面运行管理问题、进-离场航线选择问题以及基于时间的过点时序管控问题的算法框架和模型,并对未来研究方向进行展望。为推动中国机场群空地一体化运行、全局精细化管控提供理论基础,为“世界级机场群”及“智慧空管”等建设提供技术支撑。展开更多
基金supported by the National Natural Science Foundation of China(Nos.U1233101,71271113)the Fundamental Research Funds for the Central Universities(No.NS2016062)
文摘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.
文摘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.
文摘近年来,中国民航持续高速发展,预计“十四五”末期中国民航运输机场数量将达到270个以上,逐步实现运输机场网络化覆盖。然而,由于机场之间空间分布过于密集而形成的机场集群式效应,造成邻近空域之间存在着复杂的耦合作用关系,若不能在空间和时间上对机场群内各资源进行充分解耦,则难以提升整体运行安全和效率。当前运行优化技术主要侧重于各自局部单一资源的优化,并没有统筹考虑内部跨区域的约束条件以及跨业务的运行环境,因此仅能得到局部最优化管制策略。为解决机场群全局集中式运行协同规划的实际需求,对集成进离场与场面运行(integrated arrival and departure and surface operations,IADS)技术展开综述。首先,从进场、离场和场面局部运行优化技术出发,分析中外研究近况并指明现存问题及研究局限;其次,创新性地对集成进离场与场面运行概念与技术总-分结构进行阐述,系统性说明IADS内在成分和逻辑关联;最后,分别从宏-微观尺度详细描述IADS所涉及的联合进场-离场调度排序问题、机场场面运行管理问题、进-离场航线选择问题以及基于时间的过点时序管控问题的算法框架和模型,并对未来研究方向进行展望。为推动中国机场群空地一体化运行、全局精细化管控提供理论基础,为“世界级机场群”及“智慧空管”等建设提供技术支撑。
