融通仓与创新集成物流增值服务

着重从如何与金融机构协作,进行第三方物流服务创新展开讨论。介绍了融通仓的概念和发展现状、研究背景和目的以及创新集成物流增值服务的功能和模式。     

跨境供应链网络海外仓的鲁棒性选址模型及算法

新经济形态下，全球政治、经济形势瞬息万变，多种人为和自然因素导致商业供应链的生存环境日益严峻. 跨境供应链网络作为典型的时效性和运营环境等都具有极大不确定性的复杂网络，研究其鲁棒性问题具有一定的理论意义和实际应用场景. 首先阐明了跨境供应链网络的内涵，认为海外仓的选址优化是控制网络鲁棒性的重要手段；随后基于最小最大后悔值构建了海外仓的鲁棒性选址模型，利用情景松弛算法对模型进行求解. 算例分析结果证明，所构建的海外仓鲁棒性选址模型及算法适用于跨境供应链网络情景.     

A comparison of various algorithms to extract Magic Formula tyre model coefficients for vehicle dynamics simulations

Tyre models are a prerequisite for any vehicle dynamics simulation. Tyre models range from the simplest mathematical models that consider only the cornering stiffness to a complex set of formulae. Among all the steady-state tyre models that are in use today, the Magic Formula tyre model is unique and most popular. Though the Magic Formula tyre model is widely used, obtaining the model coefficients from either the experimental or the simulation data is not straightforward due to its nonlinear nature and the presence of a large number of coefficients. A common procedure used for this extraction is the least-squares minimisation that requires considerable experience for initial guesses. Various researchers have tried different algorithms, namely, gradient and Newton-based methods, differential evolution, artificial neural networks, etc. The issues involved in all these algorithms are setting bounds or constraints, sensitivity of the parameters, the features of the input data such as the number of points, noisy data, experimental procedure used such as slip angle sweep or tyre measurement (TIME) procedure, etc. The extracted Magic Formula coefficients are affected by these variants. This paper highlights the issues that are commonly encountered in obtaining these coefficients with different algorithms, namely, least-squares minimisation using trust region algorithms, Nelder–Mead simplex, pattern search, differential evolution, particle swarm optimisation, cuckoo search, etc. A key observation is that not all the algorithms give the same Magic Formula coefficients for a given data. The nature of the input data and the type of the algorithm decide the set of the Magic Formula tyre model coefficients.     

我国区域性综合物流中心的建设分析

分析了综合物流中心建设的必要条件,提出我国建设区域性综合物流中心的建议,为我国在新形势下开展综合物流领域的建设提供参考。     

多式联运协同服务系统的设计与实现

多式联运已成为现代物流的高速公路,而信息化建设是推动多式联运快速发展的主要因素。文中介绍了多式联运协同服务（MTC）系统的架构设计和功能,实现＂port to door＂各环节的信息互动和协同作业要求,为货主/货代、船公司、物流企业等部门物流操作、信息跟踪及物流监管服务等提供全方位的支持。通过系统建设,全面整合各环节系统及信息资源,构筑高效联动、功能完备的集疏运服务平台,为多式联运提供全程无缝式信息一体化服务。     

物流无人机对地风险评估方法研究

随着智能交通运输体系的完善和无人机应用场景的拓展，物流无人机应运而生。物流无人机被认为是解决快递配送“最后一公里”问题的有效运输方式，但由空中碰撞、系统失效等原因导致的无人机坠落有可能对地面人员造成伤害并产生经济损失。因此本文聚焦无人机物流运输场景，研究物流无人机坠地后造成的死亡人数和经济损失，并利用风险矩阵综合评估风险。主要内容包括：分析物流无人机空中碰撞后产生机货分离的情况，建立由物流无人机和货物坠地造成 的地面死亡人数计算模型；对无人机和货物进行分类，建立经济损失计算模型，包括由无人机和货物价值损失构成的直接经济损失，以及由社会服务机构费用消耗构成的间接经济损失；综合物 流无人机和货物坠地造成的地面死亡人数和经济损失建立风险评估矩阵。算例证明，利用本文方法得到的地面死亡人数为每飞行小时3.74×10-12~1.87×10-7人，符合等效安全水平；每次事故经济损失为6734.8~33619.0元，也在合理区间内。本文提供的方法可以对物流无人机地面风险评估和管控提供一定借鉴和指导意义。     

The role of alternative fuel vehicles: Using behavioral and sensor data to model hierarchies in travel

Greater adoption and use of alternative fuel vehicles (AFVs) can be environmentally beneficial and reduce dependence on gasoline. The use of AFVs vis-à-vis conventional gasoline vehicles is not well understood, especially when it comes to travel choices and short-term driving decisions. Using data that contains a sufficiently large number of early AFV adopters (who have overcome obstacles to adoption), this study explores differences in use of AFVs and conventional gasoline vehicles (and hybrid vehicles). The study analyzes large-scale behavioral data integrated with sensor data from global positioning system devices, representing advances in large-scale data analytics. Specifically, it makes sense of data containing 54,043,889 s of speed observations, and 65,652 trips made by 2908 drivers in 5 regions of California. The study answers important research questions about AFV use patterns (e.g., trip frequency and daily vehicle miles traveled) and driving practices. Driving volatility, as one measure of driving practice, is used as a key metric in this study to capture acceleration, and vehicular jerk decisions that exceed certain thresholds during a trip. The results show that AFVs cannot be viewed as monolithic; there are important differences within AFV use, i.e., between plug-in hybrids, battery electric, or compressed natural gas vehicles. Multi-level models are particularly appropriate for analysis, given that the data are nested, i.e., multiple trips are made by different drivers who reside in various regions. Using such models, the study also found that driving volatility varies significantly between trips, driver groups, and regions in California. Some alternative fuel vehicles are associated with calmer driving compared with conventional vehicles. The implications of the results for safety, informed consumer choices and large-scale data analytics are discussed.     

基于交通大数据的移动模式分析综述

交通大数据可为揭示交通主体显性出行行为背后的深层规律（即移动模式）提供重要基础。精确掌握大数据驱动下交通主体的移动模式，可为需求预测、客流组织、土地利用、事件管理等应用提供理论依据。交通大数据主体繁多、时空多态、关联性复杂的特性迫使小数据时代下的移动模式分析方法转型和升级，但仍可能遇到移动模式一致性表达难、异常类型检测难、复杂关联性表达难、时空多态性建模难、一体可视化分析难等普遍问题。针对这些问题，利用科学知识图谱，对2010~2020年期间3 747篇文献的热点关键词分布、发表趋势分布、出版刊物分布等特点进行归纳总结，结合常见的移动模式分析数据集，系统综述现有研究在移动模式常态分析、非常态分析、关联分析、预测分析和可视化分析方向上的阶段性进展。其中，移动模式常态分析综述了个体活动特性分析、出行类别划分、特定群体分析等应用的研究进展。移动模式非常态分析综述了基于模板匹配和数据驱动的非常态事件检测方法的发展脉络。移动模式关联分析综述了面向不同数据源的关联特性检测方法的发展近况。移动模式预测分析综述了基于数理统计和数据驱动的交通属性预测方法的发展状况。移动模式可视化分析综述了用户交互设计、移动模式宏观可视化、微观可视化和整体可视化的发展近况。最后，系统总结各个分支方向面临的主要问题与挑战，并从数据整合、模型创新、机制变革等角度提炼移动模式分析研究的未来发展趋势，期望为后续研究采用新理论技术开展移动模式分析提供参考。     

甘肃省农产品冷链物流系统评价研究

如何构建高效运作的农产品冷链物流系统对于农产品毁损率、减少不必要的经济损失进而提高农民的收入意义重大。文章建立了多层次综合评价体系，应用模糊层次分析法（F_AHP）的原理及算法综合评价了甘肃省农产品冷链物流系统的绩效，验证了F．AHP法在这一领域应用的有效性，并进一步剖析了该省农产品冷链物流系统存在的诸多问题。