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Engineering 2022年第5期8卷 202-220页

作者： Yahan Lu lixing yang Kai yang Ziyou Gao Housheng Zhou Fanting Meng Jianguo Qi State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China

Regular coronavirus disease 2019(COVID-19)epidemic prevention and control have raised new require-ments that necessitate operation-strategy innovation in urban rail transit.To alleviate increasingly seri-ous congestion and further reduce the risk of cross-infection,a novel two-stage distributionally robust optimization(DRO)model is explicitly constructed,in which the probability distribution of stochastic scenarios is only partially known in advance.In the proposed model,the mean-conditional value-at-risk(CVaR)criterion is employed to obtain a tradeoff between the expected number of waiting passen-gers and the risk of congestion on an urban rail transit line.The relationship between the proposed DRO model and the traditional two-stage stochastic programming(SP)model is also depicted.Furthermore,to overcome the obstacle of model solvability resulting from imprecise probability distributions,a discrepancy-based ambiguity set is used to transform the robust counterpart into its computationally tractable form.A hybrid algorithm that combines a local search algorithm with a mixed-integer linear programming(MILP)solver is developed to improve the computational efficiency of large-scale instances.Finally,a series of numerical examples with real-world operation data are executed to validate the pro-posed approaches.

关键词： Passenger flow control Train scheduling Distributionally robust optimization Stochastic and dynamic passenger demand Ambiguity set

Future urban transport management

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工程管理前沿:英文版 2023年第3期10卷 534-539页

作者： Ziyou GAO Hai-jun HUANG Jifu GUO lixing yang Jianjun WU School of Systems Science Beijing Jiaotong UniversityBeijing 100044China School of Economics and Management Beihang UniversityBeijing 100191China Beijing Transport Institute Beijing 100073China

The incorporation of disruptive innovations into the transportation industry will inevitably cause major upheavals in the transportation sector.However,existing research lacks systematic theories and methodologies to represent the underlying characteristics of future urban transport systems.Furthermore,emerging modes in urban mobility have not been sufficiently studied.The National Natural Science Foundation of China(NSFC)officially approved the Basic Science Center project titled“Future Urban Transport Management”in 2022.The project members include leading scientists and engineers from Beijing Jiaotong University,Beihang University,and Beijing Transport Institute.Based on a wide range of previous projects by the consortium on urban mobility and sustainable cities,this project will encompass transdisciplinary and interdisciplinary research to explore critical issues affecting future urban traffic management.It aims to develop fundamental theories and methods based on social and technological developments in the near future and explores innovative solutions to implement alongside these emerging developments in urban mobility.

关键词： future urban transport management travel behavior characteristics transportation operations transportation emergency management transportation decision intelligence

FUZZY MULTI-LEVEL WAREHOUSE LAYOUT PROBLEM:NEW MODEL AND ALGORITHM

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Journal of Systems Science and Systems Engineering 2006年第4期15卷 493-503页

作者： lixing yang Yuan FENG School of Traffic and Transportation Beijing Jiaotong University Beijing 100044 China College of Mathematics & Physics Beijing Institute of Petro-chemical Technology Beijing 102617 China

This paper deals with a multi-level warehouse layout problem under fuzzy environment, in which different types of items need to be placed in a multi-level warehouse and the monthly demand of each item type and horizontal distance traveled by clamp track are treated as fuzzy variables. In order to minimize the total transportation cost, chance-constrained programming model is designed for the problem based on the credibility measure and then tabu search algorithm based on the fuzzy simulation is designed to solve the model. Some mathematical properties of the model are also discussed when the fuzzy variables are interval fuzzy numbers or trapezoidal fuzzy numbers. Finally, a numerical example is presented to show the efficiency of the algorithm.

关键词： Multi-level warehouse layout problem fuzzy variable tabu search algorithm

基于计算机视觉的轨道交通站内火灾检测与定位

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交通运输系统工程与信息 2024年第3期24卷 53-63页

作者：张金雷杨健刘晓冰陈瑶杨立兴高自友北京交通大学系统科学学院北京100044 北京交通大学交通运输学院北京100044

为及时有效地处理轨道交通站内火灾事件,本文提出基于计算机视觉的站内火灾检测与精细化火灾定位模型(Fire-Detect)。首先,基于Unity仿真模拟和收集互联网图像数据的方式制作站内火灾图像与视频数据集Fire-Rail,用于训练构建的火灾检测... 详细信息

为及时有效地处理轨道交通站内火灾事件,本文提出基于计算机视觉的站内火灾检测与精细化火灾定位模型(Fire-Detect)。首先,基于Unity仿真模拟和收集互联网图像数据的方式制作站内火灾图像与视频数据集Fire-Rail,用于训练构建的火灾检测算法和精细化火灾定位算法;其次,基于卷积神经网络、残差结构与通道注意力机制构建火灾检测算法,用于检测站内监控视频中每帧分别为“正常状态”或“疑似火灾”状态;最后,在“疑似火灾”状态下,模型启动精细化火灾定位算法,将图像以及后续的每帧图像输入精细化火灾定位算法中,并实时输出火灾发生场景下的精细化火灾定位信息。在Fire-Rail数据集上进行实验,火灾检测算法在测试集的准确率为95.12%;此外,卷积神经网络层级实验平衡了资源消耗和准确率,消融实验验证了各部分的有效性,鲁棒性实验表明,该算法能处理大部分噪声,整体模型的平均火灾定位检测精度mAP为77.3%,可应用于轨道交通站内视频监控设备。

关键词：智能交通火灾检测深度学习轨道交通车站计算机视觉

不确定信息下的灾后道路实时抢修鲁棒优化策略

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系统工程学报 2024年第3期39卷 360-372页

作者：马倩乾李树凯杨立兴杨凯北京交通大学系统科学学院北京100044

针对突发事件后受损道路的抢修问题,建立了以抢修总成本最小为目标的多阶段道路抢修优化模型.进一步,考虑各个受损点抢修时间的不确定性,构建了基于情景集的灾后道路抢修鲁棒优化模型.为满足受损与抢修信息的预测不准确性和动态变化性,... 详细信息

针对突发事件后受损道路的抢修问题,建立了以抢修总成本最小为目标的多阶段道路抢修优化模型.进一步,考虑各个受损点抢修时间的不确定性,构建了基于情景集的灾后道路抢修鲁棒优化模型.为满足受损与抢修信息的预测不准确性和动态变化性,设计了一种基于多周期滚动优化方法的高效求解策略.最后通过数值实验发现,多阶段鲁棒优化抢修策略可以满足灾后道路抢修的不确定性和实时性要求.此外,决策者可根据实际需求选取合适的风险权衡因子,实现解鲁棒和模型鲁棒之间的权衡.

关键词：道路抢修鲁棒优化滚动优化不确定性

大客流场景下列车时刻表与列车容量分配协同优化研究

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交通运输系统工程与信息 2024年第2期24卷 199-207页

作者：龚聪聪杨立兴石俊刚戚建国周厚盛北京交通大学系统科学学院北京100044 华东交通大学交通运输工程学院南昌330013

为缓解城市轨道交通通勤线路中大客流车站及其下游车站的站台拥挤,降低候车乘客的聚集程度和安全风险,本文从时间和空间角度系统优化城市轨道交通列车容量资源配置。通过考虑时变客流需求和预留车厢策略,提出城轨列车时刻表与列车容量... 详细信息

为缓解城市轨道交通通勤线路中大客流车站及其下游车站的站台拥挤,降低候车乘客的聚集程度和安全风险,本文从时间和空间角度系统优化城市轨道交通列车容量资源配置。通过考虑时变客流需求和预留车厢策略,提出城轨列车时刻表与列车容量分配协同优化方法。具体地,通过引入列车发车时间、预留车厢数量和客流分配方案相关决策变量,以最小化预留车厢运营成本和站台乘客最大聚集数量为目标,建立列车时刻表与列车容量分配协同优化线性整数规划模型。其中,采用大M方法构建的客流分配约束能够满足乘客在时间和空间上的先到先服务原则。为验证所构建模型的有效性,设置4组数值算例进行对比实验,并采用优化求解器Gurobi求解。结果表明,相较于计划列车时刻表方案和两种单一优化策略方案,协同优化方案能够显著降低最大乘客聚集数量分别约为60%、52%和31%,降低乘客总等待时间分别约为29%、17%和29%。即协同优化方法能够均衡城轨列车容量的时空分布,从而有效降低站台候车乘客的聚集风险。

关键词：城市交通列车容量时空分配协同优化列车时刻表大客流场景站台拥挤

面向客流聚集风险防控的城轨列车实时调度模型与算法

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交通运输工程与信息学报 2024年第2期22卷 90-103页

作者：陈星阴佳腾高原蒲凡杨立兴南昌轨道交通集团有限公司南昌330220 北京交通大学系统科学学院北京100044 北京交通大学先进轨道交通自主运行全国重点实验室北京100044 北京理工大学管理与经济学院北京100081

“后疫情时代”下,我国城市轨道交通客流量快速反弹并进一步持续攀升。在此背景下,以缓解车站拥挤度为目标,研究面向客流聚集风险防控的列车实时调度问题具有重要的现实意义。在线路运营受到异常事件干扰条件下,结合列车跳停策略和运行... 详细信息

“后疫情时代”下,我国城市轨道交通客流量快速反弹并进一步持续攀升。在此背景下,以缓解车站拥挤度为目标,研究面向客流聚集风险防控的列车实时调度问题具有重要的现实意义。在线路运营受到异常事件干扰条件下,结合列车跳停策略和运行图协同调整,以最小化线路车站拥挤度为目标函数,以车厢满载率为模型约束,建立列车实时调度混合整数线性规划模型。为提高模型求解效率,提出可变邻域搜索算法,首先基于线性规划松弛原理设计模型初始解的启发式计算规则,之后基于可变邻域搜索算法寻找初始解邻域内的近似最优解作为列车实时调度问题的最终解。使用北京地铁亦庄线实际数据进行了仿真实验,仿真结果表明:以标准“站站停”策略生成的运行图调整方案作为评价基准,采用可变邻域搜索算法计算得到的列车实时调度策略可降低线路拥挤度约67.56%,减少约38.28%的线路最大断面客流量,计算时间在1 min左右,可满足列车实时调度的需求,验证了本文提出的列车实时调度模型与求解算法能有效降低车站拥挤度、均衡线路客流的断面分布,对突发大客流带来的车站乘客聚集问题具有较好的调整效果。

关键词：城市轨道交通列车实时调度客流优化列车跳停混合整数线性规划可变邻域搜索

Energy-saving operation approaches for urban rail transit systems

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Frontiers of Engineering Management 2019年第2期6卷 139-151页

作者： Ziyou GAO lixing yang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China

With the accelerated urbanization in China, passenger demand has dramatically increased in large cities, and traffic congestion has become serious in recent years. Developing public urban rail transit systems is an indispensable approach to overcome these problems. However, the high energy consumption of daily operations is an emerging issue due to increased rail transit networks and passenger demands. Thus, reducing the energy consumption and operational cost by using advanced optimization methodologies is an urgent task for operation managers. This work systematically introduces energysaving approaches for urban rail transit systems in three aspects, namely, train speed profile optimization, utilization of regenerative energy, and integrated optimization of train timetable and speed profile. Future research directions in this field are also proposed to meet increasing passenger demands and network?based urban rail transit systems.

关键词： urban rail transit energy saving speed profile optimization regenerative energy train timetable

数字经济下云南省农产品行业电子商务发展策略研究

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全国流通经济 2024年第6期 157-160页

作者：瞿晓娟杨丽星昆明幼儿师范高等专科学校云南昆明651700

随着互联网快速发展,数字经济已然成为必然趋势,对实体经济造成较大冲击,如何实现协同发展,促进经济全面提升受到重视。电子商务的出现,将数字经济与实体经济相融合,打破时间空间限制,依托互联网进行线上交易,再通过物流完成商品运输,... 详细信息

随着互联网快速发展,数字经济已然成为必然趋势,对实体经济造成较大冲击,如何实现协同发展,促进经济全面提升受到重视。电子商务的出现,将数字经济与实体经济相融合,打破时间空间限制,依托互联网进行线上交易,再通过物流完成商品运输,不仅提高了市场交易有效性,还在一定程度上促进了地方特色产品对外销售。云南地处西南,农产品种类丰富,然而受交通、地理位置等因素影响,外省人鲜有了解其特色农产品,再加上农产品具有保质期短、存储困难等特性,在一定程度上制约行业发展。电子商务在农产品行业中的应用,打开了云南省对外销售大门,对于农业可持续发展有着促进作用。本文将结合实际情况,对数字经济下云南省农产品行业电子商务的发展策略进行分析,为后续开展的有关工作提供参考。

关键词：数字经济云南省农产品电子商务发展

Robust energy-efficient train speed profile optimization in a scenario-based position-time-speed network

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Frontiers of Engineering Management 2021年第4期8卷 595-614页

作者： Yu CHENG Jiateng YIN lixing yang State Key Laboratory of Rail Traffic Control&Safety Beijing Jiaotong UniversityBeijing 100044China E-mail:jiatyin@***

Train speed profile optimization is an efficient approach to reducing energy consumption in urban rail transit systems.Different from most existing studies that assume deterministic parameters as model inputs,this paper proposes a robust energy-efficient train speed profile optimization approach by considering the uncertainty of train modeling parameters.Specifically,we first construct a scenario-based position-time-speed(PTS)network by considering resistance parameters as discrete scenariobased random variables.Then,a percentile reliability model is proposed to generate a robust train speed profile,by which the scenario-based energy consumption is less than the model objective value at a confidence level.To solve the model efficiently,we present several algorithms to eliminate the infeasible nodes and arcs in the PTS network and propose a model reformulation strategy to transform the original model into an equivalent linear programming model.Lastly,on the basis of our field test data collected in Beijing metro Yizhuang line,a series of experiments are conducted to verify the effectiveness of the model and analyze the influences of parameter uncertainties on the generated train speed profile.

关键词： robust train speed profile percentile reliability model scenario-based position-time-speed network mixed-integer programming