客车捎带模式下高铁快捷货物输送方案研究

以提高高铁快运当日达产品的时效性、收益率为核心,对既有载客动车组捎带模式下的快捷货物输送方案进行优化。借助时空网络以列车运行成本与时间惩罚费用之和最小为目标,同时满足货主时限、列车容量以及列车停站方案等约束,建立输送方案优化模型,通过匈牙利算法,并借助Matlab的Yalmip工具箱求解模型。以兰州西站至天水南站、宝鸡南站及西安北站部分时间段的快捷货物运输需求为背景进行算例分析,验证模型的有效性。结果表明合理估算列车装载容量及货物的延迟时限对输送方案的选择起重要作用。     

Extreme hawser tension assessment for FPSO vessel during offloading operation in Bohai bay

The Floating Production Storage and Offloading Unit (FPSO) is an offshore vessel that produces and stores crude oil prior to tanker transport.Robust prediction of extreme hawser tensions during Floating Production Storage and Offloading (FPSO) operation is an important safety concern. Excessive hawser tension may occur during offloading operations, posing an operational risk. In this paper, AQWA has been used to analyze vessel response due to hydrodynamic wave loads, acting on a specific FPSO vessel under actual sea conditions. Experimental validation of numerical results has been discussed as well.This paper advocates methodology for estimating extreme response statistics, based on simulations (or measurements). The modified ACER (averaged conditional exceedance rate) method is presented in brief detail. Proposed methodology provides an accurate extreme value prediction, utilizing all available data efficiently. In this study the estimated return level values, obtained by ACER method, are compared to the corresponding return level values obtained by Gumbel method. Based on the overall performance of the proposed method, it is concluded that the improved ACER method can provide more robust and accurate prediction of the extreme hawser tension.Data declustering issue has been addressed. Paper highlights ability of ACER method to account for a set of varying sea state probabilities, as required in engineering long term statistical analysis.Described approach may be well used at the vessel design stage, while defining optimal vessel parameters that would minimize potential FPSO hawser tension.     

Competitiveness of container terminal operating companies in South Korea and the industry–university–government network

Burgeoning container port facilities have fostered intensified competition among container terminal operating companies (CTOCs). However, despite research into their survival strategies which identified antecedents of competitiveness including hard factors such as facilities, available cargo and cargo processing ability, softer factors spanning human resource management, networks and strategic alliances with universities and government agencies in industry–university–government (I–U–G) networks have been overlooked. This study aims to examine both hard and softer antecedents of competitiveness as perceived by 152 professionals in South Korean CTOCs; empirical relationships among these antecedents, I–U–G networks, and competitiveness itself; and the significance of the I–U–G network in establishing and improving competitiveness. Posited antecedents of competitiveness included human resources, facilities, service quality, customer orientation, reputation, and government support policy as independent variables; the I–U–G network as a moderating variable; and competitiveness as a dependent variable. Empirical structural relationships revealed that excepting government support policy, each variable significantly affected CTOC competitiveness. Further, the I–U–G network moderated the relationships between the antecedents of competitiveness and competitiveness. Because an effective I–U–G network was pivotal in controlling CTOC competitiveness, improved competitiveness requires not only differentiation of human resources, facilities, service quality, customer orientation, and reputation factors but also I–U–G network developments.     

Controller design for gating traffic control in presence of time-delay in urban road networks

Recent studies demonstrated the efficiency of feedback-based gating control in mitigating congestion in urban networks by exploiting the notion of macroscopic or network fundamental diagram (MFD or NFD). The employed feedback regulator of proportional-integral (PI)-type targets an operating NFD point of maximum throughput to enhance the mobility in the urban road network during the peak period, under saturated traffic conditions. In previous studies, gating was applied directly at the border of the protected network (PN), i.e. the network part to be protected from over-saturation. In this work, the recently developed feedback-based gating concept is applied at junctions located further upstream of the PN. This induces a time-delay, which corresponds to the travel time needed for gated vehicles to approach the PN. The resulting extended feedback control problem can be also tackled by use of a PI-type regulator, albeit with different gain values compared to the case without time-delay. Detailed procedures regarding the appropriate design of related feedback regulators are provided. In addition, the developed feedback concept is shown to work properly with very long time-steps as well. A large part of the Chania, Greece, urban network, modelled in a microscopic simulation environment under realistic traffic conditions, is used as test-bed in this study. The reported results demonstrate a stable and efficient behaviour and improved mobility of the overall network in terms of mean speed and travel time.     

Evaluating determinants of attractiveness and their cause-effect relationships for container ports in Taiwan: users’ perspectives

The attractiveness of ports is usually a pre-requisite and necessary condition for ports to achieve competitiveness, as well as the springboard to explore the competitive advantages of ports. To determine whether a port is competitive, it is necessary to explore whether it boasts certain factors that make the port attractive to users. The main purpose of this article is to apply the Analytic Hierarchy Process (AHP) method and the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique to evaluate key determinants of attractiveness and their cause/effect relationships for container ports in Taiwan. The empirical results showed that: (1) Top six determinates of attractiveness for container ports are ‘ample cargo sources,’ ‘favorable port charges,’ ‘dense ship network and routes,’ ‘low transshipment costs,’ ‘efficient wharf operations,’ and ‘adequate wharfs and back-line land,’ respectively. (2) Among the above six determinants of attractiveness, ‘ample cargo sources’ is the cause determinant. Three determinants of port attractiveness, ‘favorable port charges,’ ‘dense ship network and routes,’ ‘low transshipment costs,’ which are the effect determinants. They are affected by the determinants of attractiveness of ‘ample cargo sources’. In addition, this study discusses the above findings and expects to provide the study results to Taiwan’s port authorities for reference.     

基于光纤传感系统的德国列车实时精确定位技术

实时、精确地获取列车位置信息是保证列车安全有效运行、发挥效率、提供最佳服务的前提。而轨旁传感器将在进行高效、可靠的列车跟踪和定位方面发挥重要作用。文章介绍德国基于光纤传感系统的列车实时精确定位技术,这是一种全新的解决方案,具有独特的优势和可能性。     

基于深度强化学习的智能船舶航迹跟踪控制

[目的]智能船舶的航迹跟踪控制问题往往面临着控制环境复杂、控制器稳定性不高以及大量的算法计算等问题。为实现对航迹跟踪的精准控制,提出一种引入深度强化学习技术的航向控制器。[方法]首先,结合视线(LOS)算法制导,以船舶的操纵特性和控制要求为基础,将航迹跟踪问题建模成马尔可夫决策过程,设计其状态空间、动作空间、奖励函数;然后,使用深度确定性策略梯度(DDPG)算法作为控制器的实现,采用离线学习方法对控制器进行训练;最后,将训练完成的控制器与BP-PID控制器进行对比研究,分析控制效果。[结果]仿真结果表明,设计的深度强化学习控制器可以从训练学习过程中快速收敛达到控制要求,训练后的网络与BP-PID控制器相比跟踪迅速,具有偏航误差小、舵角变化频率小等优点。[结论]研究成果可为智能船舶航迹跟踪控制提供参考。     

考虑空车调配协调的货物列车开行方案优化研究

为实现空车调配与货物列车开行方案协调优化，结合基本运行图架构与车流径路，构建货运时空服务拓展网络。考虑配空与装卸取送、集编发等环节的时间接续要求，节点与区段不对流空车要求，以重车流全程运送与空车配送等广义总费用最少为目标，建立整数规划弧路模型。针对既有算法设计局限性，结合重车或空车配空的时间接续要求，提出将不同的 k 短路重车流方案与空车配空方案相关联的改进可行解构造方法，设计混合差分进化求解算法。实例研究表明，考虑空车调配进行重车、空车流组织协调优化，能够减少空车走行费用，及时满足装车需求，有效保证作业车流配合中转车流集结编组及时挂线，提高方案可实施性。     

Capturing correlation with a mixed recursive logit model for activity-travel scheduling

Representing activity-travel scheduling decisions as path choices in a time–space network is an emerging approach in the literature. In this paper, we model choices of activity, location, timing and transport mode using such an approach and seek to estimate utility parameters of recursive logit models. Relaxing the independence from irrelevant alternatives (IIA) property of the logit model in this setting raises a number of challenges. First, overlap in the network may not fully characterize perceptual correlation between paths, due to their interpretation as activity schedules. Second, the large number of states that are needed to represent all possible locations, times and activity combinations imposes major computational challenges to estimate the model. We combine recent methodological developments to build on previous work by Blom Västberg et al. (2016) and allow to model complex and realistic correlation patterns in this type of network. We use sampled choices sets in order to estimate a mixed recursive logit model in reasonable time for large-scale, dense time-space networks. Importantly, the model retains the advantage of fast predictions without sampling choice sets. In addition to estimation results, we present an extensive empirical analysis which highlights the different substitution patterns when the IIA property is relaxed, and a cross-validation study which confirms improved out-of-sample fit.     

Optimal design of electric vehicle public charging system in an urban network for Greenhouse Gas Emission and cost minimization

In this paper, we address the optimization problem of allocation of Electric Vehicle (EV) public fast charging stations over an urban grid network. The objective is to minimize Greenhouse Gas Emissions (GHG) under multiple constraints including a limited agency budget, accessibility of charging stations in every possible charging request and charging demands during peak hours. Additionally, we address bi-criteria problems to consider user costs as the second objective. A convex parsimonious model that depends on relatively few assumptions and input parameters is proposed and it is shown to be useful for obtaining conceptual insights for high-level planning. In a parametric study using a hypothetical urban network model generated based on realistic parameters, we show that GHG emissions decrease with agency budget, and that the reductions vary depending on multiple factors related to EV market and EV technologies. The optimal solutions found from the bi-criteria problems are shown to be close to the solution minimizing GHG emissions only, meaning that the emission minimizing policy can also minimize user costs.