Data dependent input control for origin–destination demand estimation using observability analysis

In this paper, we address the observability issue of static O–D estimation based on link counts. Unlike most classic observability analyses that relied only on network topological relationships, our analysis incorporates the actual values of input parameters, thus including network operational relations as well. We first analyze possible mathematical properties of an O–D estimation problem with different data input. We then propose a modeling approach based on mixed-integer program for selecting model input that ensures observability and estimation quality. Through establishing a stronger connection between observability analysis and the corresponding estimation problem, the proposed method aims to improve estimation quality while reducing reliance on erroneous data.     

A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study

The management of products’ end-of-life and the recovery of used products has gained significant importance in recent years. In this paper, we address the carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. These returned products can either be disposed of or be remanufactured to be resold as new ones. Given this environment, an optimization model for a closed-loop supply chain (CLSC) in which carbon emission is expressed in terms of environmental constraints, i.e., carbon emission constraints, is developed. These constraints aim to limit the carbon emission per unit of product supplied with different transportation modes. Here, we design a closed-loop network where capacity limits, single-item management and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling. Then, the statistical approach to the possibility to synthesize fuzzy information is utilized. Therefore, using a defined possibilistic mean and variance, we transform the proposed fuzzy mathematical model into a crisp form to facilitate efficient computation and analysis. Finally, the risk caused by violating the estimated resource constraints is analyzed so that decision makers (DMs) can trade off between the expected cost savings and the expected risk. We utilize data from a company located in Iran.     

软岩边坡加固中锚索预应力变化影响因素分析

预应力锚索被广泛应用于边坡加固,并获得了良好的加固效果和经济效益,但针对锚索预应力的影响因素及变化规律的研究还不多见。本文简要分析了预应力锚索的受力形式,结合实际软岩边坡工程,比较分析施工期和雨季中大量的监测数据,详细探讨了边坡在最不利时期中影响预应力变化的主要因素及变化特点。主要包括锚索材料、施工影响及外部因素等,对进一步综合归纳预应力变化的规律及计算模型的确定有一定的参考价值。     

铁路旅客旅行换乘方案优选算法

为给铁路旅客选择合理的旅行方案提供参考,以旅行目标值与换乘目标值之和最小作为目标函数值,考虑旅客从起点站出发、最终到达终到站、在中转站进出平衡的约束条件,建立旅客旅行换乘方案选择问题的数学模型。分别给出旅行时间、换乘次数、票价、距离、到发时刻和综合指数6种目标权值的确定方法,提出最短路法和列车匹配法2种求解方法。最短路法是通过构造并简化旅客运输网络,求出网络上若干条次短路,再根据各条次短路上列车的接续,构造列车换乘方案网络图,根据该网络的目标权值确定最短路,得到最优换乘方案。列车匹配法是根据列车运行图信息直接搜索发、到站的接续列车集合,求其两列车对应的重合停车站,根据重合停车站集合的情况选择迭代步数,剔除显然不利方案,构成换乘方案,根据方案的权值进行比选,得到最优换乘方案。对2种算法均用C#编程实现,并用现有的全路客票数据进行检算。计算结果表明:2种算法均能得到最优换乘方案;列车匹配法所用计算时间比最短路法少160 ms。     

数字通信过电流选跳保护在地铁大环网供电系统中的应用

数字通信过电流选跳保护可弥补传统过电流保护在地铁33 k V环网供电系统中的不足,已广泛应用于多个城市地铁的供电系统。在分析保护原理的基础上,应用实际运行案例,总结了其保护特性,并提出了优化建议。     

企业家选择的最优机制设计

研究了股东在缺乏企业家的实际业务能力、服务成本等方面信息的情况下，利用博弈论显示原理设计不同的报酬合同来让企业家选择，从而根据企业家选择结果来判断其真实的能力或类型，避免了企业家逆向选择与道德风险问题的发生．通过分析，得出了最优报酬机制是由努力补偿金、风险补偿金和信息租金三部分组成．最优报酬机制的灵敏度与期望补偿正相关，与固定补偿负相关．高效的企业家比低效企业家工作更加努力，更乐于选择高强度激励、低固定补偿的合同和选用风险较小的项目．     

露石水泥混凝土路面关键技术研究

研究了露石水泥混凝土路面铺筑过程中必然要遇到的材料选择、冲洗时间、成熟度、双层铺筑混凝土强度等关键技术问题,分析了冲洗时间、成熟度的主要影响因素,发现温度越高,冲洗时间越早,最早冲洗时间与最迟冲洗时间有较大的间隔,常温下可达十多个小时,温度升高,间隔减小,成熟度随温度的升高而增大,相隔一定时间分两层振捣的水泥混凝土试件强度与一次振捣的水泥混凝土试件强度基本相同。结果表明:成熟度指标、试验法是评价、检测露石工艺性质的有效手段,两层铺筑方法是降低此种路面成本的有效途径。     

城市轨道交通系统的分类及选型

阐述了城市轨道交通系统的不同分类标准,以及各种城市轨道交通型式的定义,并对城市轨道交通系统的选型进行了论述。城市交通结构中,不能只依赖于某种形式的轨道交通,而应根据交通系统的特点以及城市的实际情况,有针对性地选型,避免盲目投资。     

京沪高速铁路中小跨度桥梁结构选型初探

结合秦沈客运专线和其它国家或地区高速铁路桥型的选择 ,对京沪高速铁路中小跨度桥梁的刚度、造价等方面进行分析 ,结论是箱形截面梁性能优于T梁 ,在地基条件好的区段连续梁优于简支梁。