Parking policies in large cities in Germany

This article deals with highly motorized large West German cities of about 200,000 inhabitants and more, which usually provide reasonable public transport systems. Illegal parking with shares of about 40 to 50% of the total parking is widespread in the parking problem areas of those cities, especially in the inner-city residential and mixed-use areas. Parking spaces are demanded by residents, employees, customers and visitors, and by delivery and service traffic. The different characteristics of parking demands by different user groups are discussed. The total parking supply consists of public and private spaces. The share of private spaces is about 40 to 50% of the total parking spaces in German cities. The amount of car traffic generated by a parking space depends on parking duration and parking turnover, as well as on search traffic. So the change of a space from long-duration use of an employee to short-duration of customers — as often discussed in parking concepts — generates at least five-fold car traffic. The measurements and effects of parking control of public spaces as well as the parking regulations in zoning ordinances, restrictions on the construction of new private parking spaces and park-and-ride are discussed. Finally, a parking concept methodology — using the example of Frankfurt am Main — is discussed.     

重大突发公共卫生事件下城市应急医疗物资优化调度研究

针对新型冠状病毒肺炎（新冠肺炎）疫情防控中应急医疗物资调度不尽合理、集配中心中转效率不够高等问题，重新设计了重大突发公共卫生事件下城市应急医疗物资调度与配送体系，并给出了应急医疗物资的分类方法。从医疗物资使用需求和库存估计可使用时间2个维度构建需求点紧急度指标，考虑突发公共卫生事件特征，以加权的需求满足率最大化为主要目标、车辆行驶距离最小化为次要目标，构建应急医疗物资动态分配模型，并通过算例验证了模型的有效性和可行性。结果表明：所构建的模型能够兼顾医疗物资分配的公平和效率，符合突发公共卫生事件中应急医疗物资供给和需求的动态变化特性，确保在物资短时间供给不足的情况下各需求点也能公平获取一定比例的物资；且模型仅要求各需求点上报各种品类医疗物资的使用人数和库存量，同时模型还给出数据缺失时的自动计算办法，可操作性更强；运用紧急度指标对需求满足率最大化目标进行校正，解决了各需求点因需求量差异对公平分配造成的影响，使得应急医疗物资分配更加合理。研究成果结合了新冠肺炎疫情防控中应急医疗物资调度的具体过程，使得分配模型更符合实际需要，可为城市应急医疗物资优化调度提供决策依据。     

Containership scheduling with transit-time-sensitive container shipment demand

This paper examines the optimal containership schedule with transit-time-sensitive demand that is assumed to be a decreasing continuous function of transit time. A mixed-integer nonlinear non-convex optimization model is first formulated to maximize the total profit of a ship route. In view of the problem structure, a branch-and-bound based holistic solution method is developed. It is rigorously demonstrated that this solution method can obtain an ε-optimal solution in a finite number of iterations for general forms of transit-time-sensitive demand. Computational results based on a trans-Pacific liner ship route demonstrate the applicability and efficiency of the solution method.     

基于随机需求的多频次道路货运调度模型及算法

以道路货物运输为研究对象,采用多频次调度方法对随机需求的道路货运调度问题进行研究,给出了基于随机需求的多频次调度模型及求解模型的微粒群算法,同时通过算例验证了该模型的可行性。     

基于序贯代理模型的转子系统频响特性区间分析方法

在转子系统的频率响应分析中,不确定性广泛存在,并且对分析结果有较大的影响。本文提出了一种面向含区间不确定性转子系统频响分析的序贯代理模型方法。基于区间数学以及转子动力学理论,本文首先建立了含区间参数转子系统频响的控制方程。基于传统的静态代理模型提出了面向转子系统区间分析的序贯代理模型方法。该方法首先通过叫少量的样本点构造粗糙代理模型,再提出了两个指标函数进行下一阶段的选点。重复该过程,直到满足收敛条件,最终可以得到转子系统频率响应的精细代理模型,进而得到区间边界。和传统的区间分析方法相比,该方法精度高,适合非线性问题。     

从宏观经济形势看中重型卡车的技术战略

基于我国GDP走势、社会货运总量、国内工业化进程、产业结构升级、发展地区调整等宏观经济因素导致的公路运输供给和需求分析,结合东风商用车市场研究,探索我国重化工业阶段国内卡车市场需求的发展趋势和技术战略。     

出行者特征要素对公交服务模式的影响分析

公共交通是面向大众的服务,公共交通服务模式的制定与完善需要重点考虑出行者的出行需求,才能从根本上提高公共交通的竞争力。借鉴服务经济学的理论将公共交通服务模式分为公交服务标准、出行者界面、公交服务环境和技术4个维度。基于攀枝花市居民出行调查与公交专项调查数据,应用SPSS定量分析出行者特征要素与公交服务选择的相关性,以考察研究出行者对于公交服务的需求,并提出改善策略。通过研究表明,出行目的、出行时间、职业和年龄与公交服务模式的相关性较大。     

不完全信息下的CGF主体决策行为及模型研究

着重分析了决策的风险特性,建立了CGF主体的决策行为模型。分析加入感知行为后对决策行为复杂性的影响;提出了一种不确定型决策方法用于处理不完全感知信息对决策行为的影响;最后用示例说明了该方法的有效性。     

The price of uncertainty in pavement infrastructure management planning: An integer programming approach

Currently there is a true dichotomy in the pavement maintenance and rehabilitation (M&R) literature. On the one hand, there are integer programming-based models that assume that parameters are deterministically known. On the other extreme, there are stochastic models, with the most popular class being based on the theory of Markov decision processes that are able to account for various sources of uncertainties observed in the real-world. In this paper, we present an integer programming-based alternative to account for these uncertainties. A critical feature of the proposed models is that they provide – a priori – probabilistic guarantees that the prescribed M&R decisions would result in pavement condition scores that are above their critical service levels, using minimal assumptions regarding the sources of uncertainty. By construction of the models, we can easily determine the additional budget requirements when additional sources of uncertainty are considered, starting from a fully deterministic model. We have coined this additional budget requirement the price of uncertainty to distinguish from previous related work where additional budget requirements were studied due to parameter uncertainties in stochastic models. A numerical case study presents valuable insights into the price of uncertainty and shows that it can be large.