肩回交路条件下多机牵引机车周转图的优化

针对采用机车肩回交路的重载铁路线路,将其列车运行图中的列车运行线转化为节点,机车周转线转化为边,运用机车转化为流,从而将机车周转图的优化问题转化为网络流问题.在此基础上,以运用机车数最少、单机走行数最少、附挂机车数最少、机车在站停留时间最短和机车工作均衡性最好为优化目标,以网络流问题中的节点流量守恒和节点流量要满足节点需求为约束条件,建立肩回交路条件下的多机牵引机车周转图多目标优化模型.按照优化目标函数的优先级,采用分层序列法对模型求解,并利用C#语言编写程序,通过调用ILOG CPLEX优化软件实现了该算法.算例表明,采用所给模型和据此编制的机车周转图优化程序,可以快速优化肩回交路条件下的多机牵引机车周转图.     

旅客列车过站径路优化模型与算法

在给定铁路客运站站形布局和列车运行图的前提下,研究旅客列车过站径路优化问题。过站径路由列车的接车作业进路、占用的到发线和发车作业进路拼接而成。以旅客列车的接发车作业进路为决策,以道岔和到发线占用相容性为约束,以最大化接发车作业进路效用和到发线运用效用为优化目标,建立旅客列车过站径路优化的0-1规划模型。设计基于极大列车过站径路方案k剔除邻域系的模拟退火算法。以某客运站为例验证该模型和算法的合理性。结果表明:模型对实际问题的描述准确,算法效率较高,适用于求解大规模铁路客运站旅客列车过站径路优化问题。     

基于无线Mesh网络技术的列车宽带接入原型系统设计

随着高速铁路、公路交通的发展,信息网络的移动接入技术需要得到相应的改善和提高。根据公共移动通信网和铁路专用移动通信网的发展现状,目前有多种列车移动接入技术。通过方案比较,本文原型系统采用了基于无线Mesh网络技术的无线宽带接入技术。当前,无线Mesh网络可遵循的标准有IEEE802.11s草案,该草案对无线Mesh网络的功能、接口及网络协议栈进行了全面的定义。本文根据IEEE802.11s草案,在Linux操作系统下定义了Mesh协议栈框架,并在此基础上设计实现了针对列车的车地宽带接入带状应用场景的无线Mesh网络原型系统,并就搭建的实际网络场景进行了性能测试。实验结果表明,所设计的原型系统基本达到了列车车地宽带接入应用的要求。     

我国地铁工程施工图审查现状及政策建议

地铁工程施工图审查是政府监管地铁工程勘察设计质量的一项重要手段。通过与建筑工程对比,说明我国地铁工程具有施工图审查机构数量少、全国范围承揽业务、审查费率低等特点;分析我国地铁工程施工图审查中存在的问题,如在制度执行中审查机构抗风险能力差、高度市场化易导致不正当竞争等问题。通过借鉴发达国家和香港地区的施工图审查制度和实施经验,提出当前我国地铁工程施工图审查体制改革的几点政策建议。     

数字式点火模块自适应控制的研究

采用了在常规汽油机上仅利用分电器输出的点火触发信号进行点火提前和点火能量自适应控制的方法；根据国家有关标准进行了自适应点火控制模块的软硬件设计，经道路和发动机台架试验证明该点火器能在一定程度上提高使用车辆的经济性。     

基于神经网络的半主动悬架自适应模糊控制

提出了基于神经网络的自适应模糊控制策略。模糊控制主要用来对付系统的非线性；神经网络根据振动响应的方差递推结果来辨识车体的振动情况实时调节模糊控制器的量化因子，使模糊控制器对路面的变化具有自适应的能力。在半主动悬挂1／4车非线性模型的基础上进行了仿真研究。     

汽车半主动悬架的神经网络自适应控制

本文提出了用两个线性神经网络对汽车半主动悬架系统进行在线辨识和控制的策略，介绍了该控制系统中神经网络的在线训练方法，进行了仿真计算和结果分析。     

自适应信号控制下交叉口延误计算方法研究

为了研究交通信号的自适应控制方法,需要对交叉口延误进行定量的分析与计算。本文根据信号交叉口理论,在以往定时信号延误研究的基础上,基于交叉口一个进口方向的车辆延误分析,推导了信号控制交叉口不同交通运行状况下的交叉口延误公式;进而对自适应信号控制下交叉口延误的计算方法进行了研究,提出了自适应信号控制下交叉口延误的计算方法———根据交叉口各进口方向不同的交通运行状况以及所处的相序选择相应的公式计算交叉口各进口方向的车辆延误,然后对其求和,得到交叉口延误。     

How the cap limit for food-crop-based biofuels may affect France’s stakeholders by 2030? A range-based multi-actor multi-criteria analysis

From 2012 to 2016, the long-term signal in the biofuel market changed almost once per year, leading to a drastic decrease in investments and contributing to multiple production unit closures in France and around Europe. The European Commission proposed a new renewable energy directive that includes a 3.8% cap limit on the contribution of food-crop biofuels by 2030. Given the role of biofuels in green growth, the bioeconomy, and renewable energy incorporation targets, how will this measure affect the stakeholders by 2030? Will it lead to, contribute to, or hamper their sustainability criteria? This paper aims to contribute to this debate by studying the case of France. To this end, our methodology—the range-based multi-actor multi-criteria analysis—aims to (1) explicitly consider the stakeholder groups and their sustainability criteria; (2) evaluate and compare how the cap limit will affect these sustainability criteria whether or not advanced biofuels are deployed by 2030; (3) capture the uncertainty of the context evolution and biofuel capacity to fulfil the stakeholders’ sustainability criteria by means of a Monte Carlo. The results suggest that the cap limit is a double-edged sword for the stakeholders and their sustainability criteria. Shifting towards advanced biofuels while limiting the food-crop biofuels is the better alternative for most of the stakeholders. Nevertheless, given biofuel policy instability and the lost confidence of investors, such a shift may not occur by 2030. In such a case, this paper demonstrates that the cap limit may highly and negatively affect the stakeholders and their sustainability targets, whereas fostering French food-crop biofuel production at its full capacity level constitutes a better alternative. As no alternative is suited to all actors simultaneously, this paper also studies the strengths and weaknesses of these alternatives from each stakeholder groups’ perspective.     

A rolling horizon algorithm for auto-carrier transportation

This paper introduces a rolling horizon algorithm to plan the delivery of vehicles to automotive dealers by a heterogeneous fleet of auto-carriers. The problem consists in scheduling the deliveries over a multiple-day planning horizon during which requests for transportation arrive dynamically. In addition, the routing of the auto-carriers must take into account constraints related to the loading of the vehicles on the carriers. The objective is to minimize the sum of traveled distances, fixed costs for auto-carrier operation, service costs, and penalties for late deliveries. The problem is solved by a heuristic that first selects the vehicles to be delivered in the next few days and then optimizes the deliveries by an iterated local search procedure. A branch-and-bound search is used to check the feasibility of the loading. To handle the dynamic nature of the problem, the complete algorithm is applied repeatedly in a rolling horizon framework. Computational results on data from a major European logistics service provider show that the heuristic is fast and yields significant improvements compared to the sequential solution of independent daily problems.