Sensitivity Analysis Based Method for Optimal Road Network Pricing

Road pricing is an important economic measure for optimal management of transportation networks. The optimization objectives can be the total travel time or total cost incurred by all the travelers, or some other environmental objective such as minimum emission of dioxide, an so on. Suppose a certain toll is posed on some link on the network, this will give an impact on flows over the whole network and brings about a new equilibrium state. An equilibrium state is a state of traffic network at which no traveler could decrease the perceived travel cost by unilaterally changing the route. The aim of the toll setting is to achieve such an equilibrium state that a certain objective function is optimized. The problem can be formulated as a mathematical program with equilibrium constraints (MPEC). A key step for solving such a MPEC problem is the sensitivity analysis of traffic flows with respect to the change of link characteristics such as the toll prices. In this paper a sensitivity analysis based method is proposed for solving optimal road pricing problems.     

The maximum covering/shortest path problem: A multiobjective network design and routing formulation

In this paper the authors introduce the maximum covering/shortest path problem and the maximum population/shortest path problem, a special case of the former model. Both models are formulated as two objective integer programs. A summary of the results of a sample problem for the latter formulation is given. Possible modifications to, and extensions and applications of both models are also presented. With these formulations the authors extend the concept of ‘coverage’ from facility location analysis to network design and routing analysis.     

New Tripodal Ligands Containing Aza-Thioethers as Selective Extractants for Silver(I)

A new series of tripodal receptors bearing imine and thioether units, have been synthesized in high yields by simple condensation method. The binding properties of these ligands towards alkali, alkaline earth and transition metal ions have been established by extraction and transport experiments. These podands have highest extraction and transport rate for Ag(I). The complexation of Ag(I) with the receptors has been established using ¹H-and ¹³C-NMR spectroscopy.This revised version was published online in July 2005 with a corrected issue number.     

基于博弈论的铁路集装箱中心站装卸作业研究

考虑铁路集装箱中心站不同装卸任务之间的竞争性因素,采用博弈论的方法,研究中心站在客户竞争驱动下的装卸资源调度及作业顺序问题。建立博弈模型并设计遗传算法,通过求解该问题的典型算例,将得到的均衡解与静态最优解进行对比,分析考虑竞争因素的作业方案与最优作业方案的差异。结果表明该方法在对最优方案影响较小的情况下,充分考虑了各装卸任务间的竞争公平性,为中心站确定更加合理的装卸作业顺序和资源调度提供科学的依据。     

带时间窗取送货问题的混合算法

为解决带时间窗的取送货问题,建立了集合划分模型,设计列生成算法与启发式规则相结合的CGA混合算法进行求解。首先,放松约束构建主问题及受限主问题,运用单纯形法与分支定界进行求解;其次,建立时空网络以构建子问题,基于修正的Dijkstra's算法,设计包含算法A、B1、B2的求解算法;最后,通过启发式算法解决节点重复覆盖问题。为验证算法有效性,进一步构建了OPT近似最优解算法;并基于CGA提出三种求解策略C1、C2、C3,做单因素方差分析,采用算例分析算法的性能。实验结果表明,对于客户点数量小于30的小规模算例,CGA与OPT所得结果相近,但CGA求解效率更显著;针对客户点数量为600的大规模算例,CGA至多在20分钟内求得结果,可见本文算法的精度和效率较高。而针对不同类型及规模的客户点的单因素方差分析结果显示,C1、C2、C3在“平均行驶距离成本”、“平均车辆数”、“平均求解时间”三个维度上差异性显著,经营者可根据实际需求进行策略选择。     

基于GA-ELM的水上交通事故严重程度影响因素识别研究

水上交通事故严重程度影响因素的识别对从根本上减少严重事故件数、降低事故危害和损失具有重要意义。在历史事故报告的基础上,构建并量化事故影响因素集,提出以极限学习机(ELM)为一般事故、严重事故的二分类器,以遗传算法(GA)为因素搜索算法的GA-ELM因素识别模型。对发生在我国水域的737件水上交通事故进行实证研究,并与以支持向量机(SVM)为分类器的GA-SVM模型进行对比分析。结果表明,GA-ELM模型识别出时段、人为致因、环境致因等9个事故严重程度影响因素,较GA-SVM模型结果更为精简,且分类精度较不做因素识别时分别提高8.2%、7.1%。此外,GA-ELM大大缩短运算时间。由此可见,GA-ELM可为水上交通事故严重程度影响因素识别提供一个较好的方法。     

Robust optimization of internal transports at a parcel sorting center operated by Deutsche Post World Net

Competitiveness in global markets requires the ongoing identification and full utilization of improvement potential. To cut costs by means of process optimization, logistics service providers need to focus on efficient planning — not only for external but also for internal transports. This contribution will demonstrate that significant reductions in internal transports at one of the Deutsche Post World Net’s main parcel sorting centers can be achieved by applying the robust solution of a modified three-dimensional linear assignment model.     

城市交通疏导的优化算法及应用研究

城市交通是一个随机性很强、复杂的系统.影响城市交通顺畅的因素很多,针对目前交通存在的问题,由具体实例到抽象特性,从城市局部到整体进行了研究分析.在现有硬件设施的基础上,采用最优化算法,对比现有算法存在的缺点提出新的优化策略,便于智能交通管理.     

Mass,momentum and energy conservation laws in zero-pressure gas dynamics and δ-shocks: II

We study δ-shocks in a one-dimensional system of zero-pressure gas dynamics. In contrast to well-known papers (see References) this system is considered in the form of mass, momentum and energy conservation laws. In order to define such singular solutions, special integral identities are introduced which extend the concept of classical weak solutions. Using these integral identities, the Rankine–Hugoniot conditions for δ-shocks are obtained. It is proved that the mass, momentum and energy transport processes between the area outside the of one-dimensional δ-shock wave front and this front are going on such that the total mass, momentum and energy are independent of time, while the mass and energy concentration processes onto the moving δ-shock wave front are going on. At the same time the total kinetic energy transforms into total internal energy.     

出行量预测不确定下基于灵敏度分析的拥挤收费定价模型

拥挤收费是改善城市交通的有效手段.对拥挤收费定价的研究方法之一,就是针对固定的出行量进行收费设计.由于出行量预测不确定的因素,应针对长期出行量预测不确定的情况,利用灵敏度分析的方法,对拥挤收费定价的问题进行研究.首先研究了出行者出行的广义费用,然后考虑出行者的出行决策及出行量预测不确定的因素,给出一个拥挤收费定价模型,为交通管理者提供理论依据.