航班快速恢复建模与仿真研究

随着民用航空的发展与竞争,航班延误不仅影响航空飞行的安全与正常,更与航空公司的运营效率、运营成本及乘客利益息息相关。针对某一恶劣天气影响,对某公司受影响航班进行重新调配,考虑到航班的备降、盘旋等待、延误、取消等多种状态,以总成本最小为目标函数,建立航班快速恢复模型,通过MATLAB运用遗传算法设计航班恢复算法进行求解,得出最经济的航班恢复方案。     

考虑拥堵空间排队与溢出的道路网静态交通流分配

为刻画拥堵空间排队与溢出现象对交通流分配的影响，提出考虑拥堵空间排队与溢出的道路网静态交通流分配问题，并构建相关的求解算法，用于描述交通需求在起讫点移动过程中路网整体的宏观运行状态。首先，丰富和完善考虑拥堵空间排队与溢出的静态交通流分配的相关假设，提出次生瓶颈、拥堵干扰与渗透和分段化路段阻抗等基本概念和理论，来刻画拥堵交通瓶颈、拥堵空间排队等交通现象；其次，建立网络瓶颈识别算法和空间排队回溯算法，基于此构建考虑拥堵空间排队和溢出的增量分配算法，用于求解交通流分配的结果；最后，通过使用一个具有说明型的算例进行对比分析。研究结果表明：建立的瓶颈识别、排队回溯和增量分配算法可以识别路网中的瓶颈位置及其拥堵排队区域，并可计算得到各路段上的分段分配流量；与点排队只影响瓶颈路段的运行状况和均一的路段分配结果相比，可有效描述路网整体的宏观运行状态以及由于拥堵空间排队所导致的拥堵干扰与渗透现象；不同于“时间片”的伪动态交通流分配模型，新建算法的分配结果是“全时段”与“整体性”的路网宏观运行状态，包含了拥堵瓶颈的具体位置和空间排队的干扰与渗透情况；一般拥堵点排队模型和基于“时间片”的拥堵空间排队模型难以刻画拥堵干扰与渗透现象以及路网整体的宏观运行状态，故所建立的分配方法是对传统拥堵交通流分配的丰富和发展。     

斜腿刚构桥几何布局的优化设计

采用数学规划的方法从静力和动力两方面对斜腿刚构桥的几何布局进行优化设计。静力优化设计的优化目标是截面截面应力平方均值最小，动力优化设计的优化目标是结构自振周期平方和最小。采用了直接搜索法寻优。通过算例可知，这两种优化设计方法均可行，且均为刚性设计。     

基于红外搜索系统的被动测距技术研究

红外搜索系统是一种被动探测系统，量测数据中无目标的距离量；而评判来袭目标的威胁程度离不开其距离量。介绍了基于红外搜索系统的被动测距技术测量目标距离的算法、原理框图以及仿真试验与结果。     

基于排序二叉树的摘挂列车编组钩计划自动编制方法

根据摘挂列车编组调车作业原理,将摘挂列车下落问题抽象为排序问题,提出一种基于排序二叉树的编组钩计划自动编制方法.根据待编列车序列构造排序二叉树;利用排序二叉树的有序性快速搜索出有序车组序列,将其作为下落方案的可选集.考虑邻组、暂合列内收编固定组组别和空闲组别、端组等因素,从可选集中筛选出较优的下落方案.通过定义收编固定组简化列车收编过程,实现列车收编过程的计算机自动编制.通过实例验证,采用该方法降低了选择下落方案的复杂性,减少了列车编组钩计划的调车钩数,而且可根据实际调车线数灵活调整方案.     

102 m系杆拱桥跨铁路站场顶推施工技术

通过石环高速公路东互通立交桥的施工实践,研究总结了长距离、大跨径系杆拱桥、钢筋混凝土箱梁跨密集型铁路站场顶推施工的方案设计和顶推施工及质量控制措施,对同类桥梁的顶推施工具有很好的借鉴作用。     

Free-floating bike sharing: Solving real-life large-scale static rebalancing problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.     

变邻域搜索求解公共交通乘务调度问题

公共交通乘务调度问题是一个将车辆工作切分为一组合法班次的过程,它是NP难问题,许多求解方法的效率都与班次评价密不可分,本文通过裁剪TOPSIS方法(Technique for Order Preference by Similarity to an Ideal Solution)设计了TOPSIS班次评价方法.此外,通过裁剪变邻域搜索算法使之适合求解乘务调度问题,提出了基于变邻域搜索的乘务调度方法(Crew Scheduling Approach Based on Variable Neighbourhood Search,VNS),其中,并入了TOPSIS班次评价方法在调度过程中进行班次评价,设计了两种带概率的复合邻域结构以增加搜索的多样性,帮助跳出局部最优,在VNS中利用模拟退火算法进行局部搜索.利用中国公共交通中的11组实例进行了测试,测试结果表明,VNS优于两种新近提出的乘务调度方法,且其结果关于班次数接近于下界.     

The load-dependent vehicle routing problem and its pick-up and delivery extension

The present paper examines a Vehicle Routing Problem (VRP) of major practical importance which is referred to as the Load-Dependent VRP (LDVRP). LDVRP is applicable for transportation activities where the weight of the transported cargo accounts for a significant part of the vehicle gross weight. Contrary to the basic VRP which calls for the minimization of the distance travelled, the LDVRP objective is aimed at minimizing the total product of the distance travelled and the gross weight carried along this distance. Thus, it is capable of producing sensible routing plans which take into account the variation of the cargo weight along the vehicle trips. The LDVRP objective is closely related to the total energy requirements of the vehicle fleet, making it a credible alternative when the environmental aspects of transportation activities are examined and optimized. A novel LDVRP extension which considers simultaneous pick-up and delivery service is introduced, formulated and solved for the first time. To deal with large-scale instances of the examined problems, we propose a local-search algorithm. Towards an efficient implementation, the local-search algorithm employs a computational scheme which calculates the complex weighted-distance objective changes in constant time. Solution results are presented for both problems on a variety of well-known test cases demonstrating the effectiveness of the proposed solution approach. The structure of the obtained LDVRP and VRP solutions is compared in pursuit of interesting conclusions on the relative suitability of the two routing models, when the decision maker must deal with the weighted distance objective. In addition, results of a branch-and-cut procedure for small-scale instances of the LDVRP with simultaneous pick-ups and deliveries are reported. Finally, extensive computational experiments have been performed to explore the managerial implications of three key problem characteristics, namely the deviation of customer demands, the cargo to tare weight ratio, as well as the size of the available vehicle fleet.     

大跨度钢箱梁斜拉桥中跨合龙关键技术

以4座主跨超过400 m的钢箱梁斜拉桥中跨合龙控制为背景,对大跨度钢箱梁斜拉桥中跨合龙的2种方法进行对比分析,对合龙各主要工序的关键技术进行研究。提出了合龙段配切长度的计算公式和合龙口宽度连续观测的测点布置方式。建议:在调整好合龙口姿态后可不加压重,也可不采用临时劲性骨架锁定;采用无线采集设备采集合龙口结构的温度场,用激光测距仪测量合龙口宽度以提高观测效率和安全性;在悬臂施工阶段关注梁长累计误差并通过调整后续梁段的制造长度消除之。