Dynamic Planning of Facility Locations with Benefits from Multitype Facility Colocation

This article presents a mixed‐integer programming model for a multitype facility colocation problem with capacity expansion over a multiperiod horizon. This problem is motivated by the emerging U.S. biofuel industry that is rapidly expanding its infrastructure facilities to produce bioethanol from agricultural crops. Each type of facility (e.g., corn‐ or cellulose‐based biorefinery) requires a different type of raw material (e.g., corn or perennial grass), but they produce the same final product (e.g., bioethanol), and colocation of multiple types of facilities results in cost‐saving benefits due to complementary production process and byproduct recycling. Multiple solution approaches (i.e., Lagrangian relaxation, Benders decomposition, and accelerated Benders decomposition) are proposed to solve this problem. Numerical experiments show that accelerated Benders decomposition most effectively solves large‐sized problems in a short amount of time. Various managerial insights are also drawn from the computational results.     

浅析山地城市道路拥堵机理及解决方案

道路拥堵已经成为很多城市的疑难问题,而山地城市由于其独特的地形地貌特征,拥堵情况尤其严重。山地城市的交通特点为:呈“多中心、组团式”布局,居民出行方式多样化,中长途跨组团需求旺盛,道路服务质量较低,建设管理难度较大。其中居民对交通的需求、城市交通设施现状、政府的管理能力以及居民的交通素养是产生拥堵的内在机理。在分析山地城市拥堵现状的基础上,提出交通供需平衡、智慧交通管理、道路交通管理、完善停车设施、公共交通为导向的开发模式、构建生态城市单元和职住均衡是解决道路拥堵的有效措施。     

Patrol Route Planning for Incident Response Vehicles under Dispatching Station Scenarios

Traffic incidents often contribute to major safety concerns, impose additional congestion in the neighboring transportation networks, and induce indirect costs to economy. As roughly a third of traffic crashes are secondary accidents, effective incident management activities are critical, especially on roadways with high traffic volume, to detect, respond to, and clean up incidents in a timely fashion, which supports safety constraints and restores traffic capacity in the transportation network. Hence, it is beneficial to simultaneously plan for first respondents’ dispatching station location and patrol route design to mitigate congestion. This article presents an optimal route planning for patrolling vehicles to facilitate quick response to potential accidents. A mixed‐integer nonlinear program is proposed that minimizes the respondents’ patrolling travel cost based on the expected maximum response time from each arbitrary location to all incident locations (a.k.a. hotspots) with various incident occurrence probabilities. We have developed a column generation‐based solution technique to solve the route optimization model under different station design scenarios. To investigate the impact of dispatching station design on the routing cost, an integrated genetic algorithm framework with embedded continuous approximation approach is developed that reduces the complexity of the hybrid location design and route planning problem. Numerical experiments on hypothetical networks of various sizes are conducted to indicate the performance of the proposed algorithm and to draw managerial insights. The models and solution techniques, developed in this article, are applicable to a number of network problems that simultaneously involve routing and facility location choices.     

促进就业与居住空间配置均衡，提高上海城市交通出行效率

近年来随着上海市的城市扩张,就业地与居住地的失衡引发了较为严重的城市交通拥堵。传统的从供给和需求两个层面采取的种种举措只能短期缓解交通拥堵的现状．收效不大。因此,必须摒弃“就交通论交通”的单一思维,另辟蹊径一通过促进就业与居住均衡来改善城市交通。本文分别在空间结构层面、用地层面、规划层面提出促进均衡的措施,从交通产生的源头出发减轻拥堵。     

高架城市及其城市空间发展的三层结构模式

随着城市建设规模的不断扩大,城市交通拥堵、停车难及汽车尾气伴生的环境污染、热岛效应等问题日趋严重,已成为未来城市发展的瓶颈问题。近年来,全方位开发利用地下空间的呼声日渐升高,其中包括地下交通、地下商业空间、地下基础设施,甚至地下人居环境等,然而,人类需要阳光、雨露、空气,甚至风、雨、雪等自然生态。笔者认为,地下空间发展应该遵循的最基本原则,就是最大限度地满足人类生态环境的自然回归。基于这一理念,本文提出了以人为本的高架城市理念,通过人类活动空间层(高架层)、交通空间层(地面层)和地下基础设施空间层(地下层)的三层式空间结构,形成人居活动空间上移、影响人居活动的基础设施下移的城市规划建设新模式,为有效破解城市交通拥堵、人居活动空间短缺、城市空气污染等当代城市“综合征”提供新的思路。     

论城市规模与交通拥堵的关联性及其政策意义

随着城市空间的日益拓展及机动化进程的加快,许多大城市深陷交通拥堵困境。本文首先试图建构模型,探析其拥堵困境的微观机制,进而在公共政策的视角下探讨解决拥堵的各种选择,明确城市交通领域的公共政策逻辑与政府责任。研究发现,若交通结构、城市道路面积占比、城市出行发生的空间分布,以及出行发生密度等既定,则随着城市规模增大,交通拥堵必定会不断加剧。由此可见,城市交通领域的公共政策及公共干预诉求与城市规模有关;制定和实施科学的交通政策、确保城市交通系统的运行效率是大城市、特大城市政府不容回避、刻不容缓的责任。     

混合交通网络设计的双层模型及遗传算法求解

根据混合交通网络设计问题的特点,利用双层规划模型和遗传算法对该问题进行求解。对交通网络中的路段进行分类,通过限定决策变量的取值范围,将混合交通网络离散化。建立混合交通网络设计的双层模型。其中,上层模型以方案总投资额最小为目标函数,以路段负荷度和可行域为约束条件;下层模型为交通流分配的用户均衡模型。根据所建模型的离散特性,研究其遗传算法解法,并给出算法的具体实现步骤。以一个抽象的交通网络为例,给定网络中的路段属性、OD交通量等参数,利用MATLAB软件对模型编程求解,能够获得满意的交通网络设计方案,表明双层模型和遗传算法是一种研究混合交通网络设计问题的有效方法。最后,对该模型存在的不足及改进方向进行了探讨。     

台北市交通建设管理对重庆的启示

该文简要介绍了台北市概况及交通政策,并通过对台北市公共交通、停车管理、道路交叉口"渠化"与"干道绿波"、占道开挖管理、人行过街设施优化、道路收费政策等方面的研究,对比分析重庆市与台北市的交通承载能力,得出重庆市的道路交通承载能力还有大幅度提升余地的结论,提出当前解决交通拥堵的状况应由修建城市道路转移到改善管理手段上来。最后建议通过大力发展公共交通、增加路网密度、优化交叉口、发展单向交通组织加强智能交通系统建设等方式来提高重庆交通的管理水平与服务水平     

基于城市发展战略的深圳高铁枢纽规划研究——以深圳北站和福田站为例

由于需求与供应特征的不同,高铁车站的选址理念会不同,依托高速铁路车站建设的高铁枢纽在规划设计理念上也各有鲜明的特色.广深港客运专线深圳境内车站——深圳北站和福田站的综合交通枢纽就形成了两种截然不同的城市综合交通枢纽模式,前者选址于城市副中心,采用的是一般综合交通枢纽的选址、建设方式,属于典型的功能定位高、基础条件好、配...     

Traffic, transportation, infrastructure and externalities A theoretical framework for a CGE analysis

In Europe traffic congestions make it impossible to estimate travel time. The increasing number of cars calls for a transportation policy towards an improved efficiency of the transportation system. However, extending road infrastructure to reduce the congestion externality implies another type of externality, air pollution. Designing a transportation policy in industrialized countries one has to consider this trade-off. Our objective is to investigate the role of transportation services and their pricces within an interindustry framework. The authority wishes to minimize total cost of production with respect to the provision of infrastructure subject to an emission standard. By omitting a financial constraint to finance infrastructure we determine the size of infrastructure where no congestion occurs. The productivity effect of infrastructure and the cost savings from a dissolved congestion determine the optimal stock of infrastructure. Our congestion index is unity in that case of no financial constraint. If the extension of infrastructure has to be paid for by taxation, we obtain a lower level of infrastructure. In view of the trade-off between the benefit of a productivity gain from a dissolved congestion and the deadweight loss from taxation this lower level of infrastructure will result in an index of congestion higher than unity, implying a negative externality to the economy. Received: June 1996 / Accepted: February 1997     

运输需求管理的思想、方法及实施的基本内容

运输需求管理 (TDM )在发达国家已得到重视并开始实施 ,并成为解决目前交通问题的有效措施 ,我国存在同样的交通问题 ,需要引入TDM管理思想 .介绍了国外采取的措施及取得的成果 ,提出了我国TDM的措施和引入TDM思想的初步做法 .     

Optimizing Location and Capacity for Multiple Types of Locomotive Maintenance Shops

Thousands of locomotives run in the North America railroad network and each of them must receive periodic maintenance service; meanwhile, the locomotives may break down during shipment operations and demand repair. Maintenance shops are characterized by the types of locomotives they can handle and the level of service they can provide. This article formulates a mixed‐integer program model to optimize location and capacity of locomotive maintenance shops. The objective is to minimize the sum of the costs for building new (or shutting down existing) maintenance shops, the costs for capacity expansion (or reduction), and the costs for shipping broken locomotives to a suitable shop. A Lagrangian‐relaxation‐based heuristic algorithm is proposed to solve the shop location and capacity planning problem. The model and solution techniques are applied to a full‐scale real‐world case study, while the computational results show that the current maintenance shops are overly built and recommend that two maintenance shops should be closed and an amount of capacities should be reduced from the existing shops. A series of numerical sensitivity analyses are also conducted to draw managerial insights.     

End‐to‐End Deep Learning Methodology for Real‐Time Traffic Network Management

This article presents a novel real‐time traffic network management system using an end‐to‐end deep learning (E2EDL) methodology. A computational learning model is trained, which allows the system to identify the time‐varying traffic congestion pattern in the network, and recommend integrated traffic management schemes to reduce this congestion. The proposed model structure captures the temporal and spatial congestion pattern correlations exhibited in the network, and associates these patterns with efficient traffic management schemes. The E2EDL traffic management system is trained using a laboratory‐generated data set consisting of pairings of prevailing traffic network conditions and efficient traffic management schemes designed to cope with these conditions. The system is applied for the US‐75 corridor in Dallas, Texas. Several experiments are conducted to examine the system performance under different traffic operational conditions. The results show that the E2EDL system achieves travel time savings comparable to those recorded for an optimization‐based traffic management system.     

恶劣天气下城市主干道交通拥堵的管理对策

通过分析我国城市主干道各种恶劣天气情况下交通拥堵现象及原因,结合我国国情,提出加强基础建设、实施公共交通系统优先发展和优化交通管理的对策与建议,从而完善城市交通管理,解决城市交通拥堵问题。     

物流配送车辆对广州城市交通的影响及对策研究

大中城市交通拥堵情况日趋严重,"城市交通拥堵"和"如何治堵"已成为当前的热门话题。广州作为国家中心城市之一,城市交通拥堵情况也不例外。事实上,广州市一直致力于解决交通拥堵问题,积极采取多项措施加以解决,近期更是研究制订《亚运后广州中心城区缓解交通拥堵方案》。但是,广州治理城市交通拥堵一直以来都忽视一个重要的方面——即如何科学缓解城市物流配送车辆对城市交通带来的压力。本文试图深入了解城市物流配送车辆对广州城市交通造成压力的程度、结构及特点,分析造成压力的原因和内在机理,判明合理与不合理的因素之所在,提出科学缓解城市物流配送车辆对城市交通压力的基本思路和主要对策措施。     

A LOCATIONAL MODEL FOR THE SITE SELECTION OF SOLID WASTE MANAGEMENT FACILITIES WITH TRAFFIC CONGESTION CONSTRAINTS

The management of an integrated solid waste system has significantly changed with increasing environmental concerns. Conventional location/allocation models for solid waste management usually incorporate mass balance, capacity limitation, operating, and financial constraints. But the siting of important facilities, such as landfills, incinerators, and transfer stations, in a growing metropolitan region still encounters an explicit limitation: a traffic congestion constraint. The transfer station is the most critical one due to the various loading of different types of incoming and outgoing trucks during the peak hours in the metropolitan region. A mixed integer programming model with the framework of dynamic optimization still can be used efficiently for site selection over time once the traffic congestion constraint is included. The practical implementation of such a model is assessed by a case study of the Kaohsiung solid waste management system in Taiwan. It shows that the incorporation of the traffic congestion constraint does influence the optimal flow pattern in the soldity waste management network.     

An Approach to Dynamic Classification of Traffic Flow Patterns

Abstract: Analyses on the dynamics of traffic flow, ranging from intersection flows to network‐wide flow propagation, require accurate information on time‐varying local traffic flows. To effectively determine the flow performance measures and consequently the congestion indicators of segmented road pieces, the ability to process such data in real time is out of the question. In this article, a dynamic approach to specify flow pattern variations is proposed mainly concentrating on the incorporation of neural network theory to provide real‐time mapping for traffic density simultaneously in conjunction with a macroscopic traffic flow model. To deal with the noise and the wide scatter of raw flow measures, a filtering is applied prior to modeling processes. Filtered data are dynamically and simultaneously input to processes of neural density mapping and traffic flow modeling. The classification of flow patterns over the fundamental diagram, which is dynamically plotted with the outputs of the flow modeling subprocess, is obtained by considering the density measure as a pattern indicator. Densities are mapped by selected neural approximation method for each simulation time step considering explicitly the flow conservation principle. Simultaneously, mapped densities are matched over the fundamental diagram to specify the current corresponding flow pattern. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized within a series of intelligent management strategies including especially nonrecurrent congestion effect detection and control.     

不同类型农村基础设施建设的PPP模式选择研究

农村基础设施是农业生产、农村环境和农民生活的重要支撑载体。为解决我国农村基础设施单一供给模式难以满足当前农村发展现实需要的问题,PPP模式作为农村基础设施建设创新管理模式逐渐备受关注。然而不同类型的农村基础设施分别适合何种具体的PPP模式是其实施前必须认真回答的问题。为此在农村基础设施的传统功能分类基础上,分析不同农村基础设施的经济特性,阐述其引入PPP管理模式的前提条件,结合PPP管理模式主要类型及特征,提出经营性、准经营性和非经营性为分类的农村基础设施PPP模式管理框架,为不同类型的农村基础设施建设匹配合适的PPP管理模式。     

Network‐wide traffic speed forecasting: 3D convolutional neural network with ensemble empirical mode decomposition

Accurate traffic speed forecasting is one of the most critical tasks in proactive traffic management and the deployment of advanced traveler information systems. This paper proposes a hybrid forecasting approach named DeepEnsemble by integrating the three‐dimensional convolutional neural network (3D CNN) with ensemble empirical mode decomposition (EEMD). There are four steps in this hybrid approach. First, EEMD is adopted to decompose the complex traffic speed time series data with noise into several intrinsic mode functions (IMFs) and a residue. Second, a three‐dimensional tensor is established and fed into 3D CNN for prediction. Third, the output of 3D CNN prediction is obtained by a linear combination of the results of all components. Finally, the 3D CNN prediction output, external features, and historical features are fused to predict the network‐wide traffic speed simultaneously. The proposed DeepEnsemble approach is tested on the three‐month traffic speed series data of a real‐world large‐scale urban expressway network with 308 traffic flow detectors in Beijing, China. The experimental results indicate that DeepEnsemble outperforms the state‐of‐the‐art network‐wide traffic speed forecasting models. 3D CNN learns temporal, spatial, and depth information better than 2D CNN. Moreover, forecasting accuracy can be improved by employing EEMD. DeepEnsemble is a promising model with scalability and portability for network‐wide traffic speed prediction and can be further extended to conduct traffic status monitoring and congestion mitigation strategies.     

Mapping to Cells: A Simple Method to Extract Traffic Dynamics from Probe Vehicle Data

In the era of big data, mining data instead of collecting data are a new challenge for researchers and engineers. In the field of transportation, extracting traffic dynamics from widely existing probe vehicle data is meaningful both in theory and practice. Therefore, this article proposes a simple mapping‐to‐cells method to construct a spatiotemporal traffic diagram for a freeway network. The method partitions a network region into small square cells and represents a real network inside the region by using the cells. After determining the traffic flow direction pertaining to each cell, the spatiotemporal traffic diagram colored according to traffic speed can be well constructed. By taking the urban freeway in Beijing, China, as a case study, the mapping‐to‐cells method is validated, and the advantages of the method are demonstrated. The method is simple because it is completely based on the data themselves and without the aid of any additional tool such as Geographic Information System software or a digital map. The method is efficient because it is based on discrete space‐space and time‐space homogeneous cells that allow us to match the probe data through basic operations of arithmetic. The method helps us understand more about traffic congestion from the probe data, and then aids in carrying out various transportation researches and applications.