如何构建应对突发事件的供应链策略体系

针对突发事件具有危害性极大而事件发生的概率很难预测的现状,分析了供应链系统突发事件的特点、供应链系统应对突发事件策略的类型,提出了构建以"弹性供应链策略"为主的供应链应对突发事件的策略体系,对包括延迟制造计划、战略应急库存、备用供应商等策略的运用,以及选择供应链应对突发事件策略的原则进行论述.     

研发团队名称:现代物流与运输管理创新

主要研究方向:研究领域涉及区域物流战略与规划、供应链风险管理、企业物流系统设计与经营战略、物流园区规划与设计、港口与航运规划管理、港航企业发展战略与规划、海港与口岸(保税)经济、海上突发事件应急预案与应急物流管理等。团队负责人:杨家其博士,教授,博导,武汉理工大学交通学院副院长,交通运输工程学科学术带头人之一,曾     

食品供应链应对突发事件的决策研究

近年来，世界各地频频发生的各种突发事件，引起了食品供应链上各个环节企业的信用危机，甚至导致了外交危机以及贸易摩擦。因此，非常有必要从供应链的视角来进行食品企业的突发事件研究。     

基于供应链的企业库存成因及优化控制研究

基于企业全面库存管理思想,对库存成本、库存控制、库存系统优化等管理经验与前人研究成果进行分析,借鉴先进企业的库存管理理念和方法,以大型制造企业为核心研究对象,在集供应商、制造商、经销商为一体的供应链作为研究框架的基础上,运用供应链系统理论作为研究方法,分析了库存管理现状、影响因素及产生原因,从优化生产管理、整合企业内部供应链和跨企业供应链的角度提出库存控制的相应对策,以实现全面的库存优化,提高经营效益。     

基于电子商务的供应链管理集成技术研究

针对传统的供应链管理难以实现企业与合作伙伴间对信息的实时同步共享,不能充分支持和体现供应链管理的战略优势和系统特征的问题,在分析基于电子商务的供应链管理集成模式的基础上,给出以BizTalk为主要开发平台的电子商务供应链管理系统集成的技术架构,使供应链上的节点企业可以真正实现与供应商、经销商和客户的信息共享。     

数量折扣契约下三级供应链的需求扰动管理

突发事件的发生会导致市场需求发生变化，扰乱供应链的协调。此时，可以依靠数量折扣契约来恢复供应链的协调。为此，在线性需求关系下三级供应链中主要研究了两个阶段：就集权和分权的供应链如何有效地调整批发定价策略以协调变化后的环境给出了最优策略。     

基于Multi-agent供应链建模与仿真研究综述

基于Multi—agent的建模与仿真已成为研究供应链这一类复杂系统的最重要手段之一。笔者首先分析了Agent与Multi—agent系统的特征．然后对有关基于Multi—agent的供应链建模与仿真的应用研究文献进行了回顾．分析了与传统数学建模方法相比，采用Multi—agent技术进行供应链的建模与仿真的优势，最后指出了采用Multi—agent仿真方法是解决供应链计划、协调、实施等问题的一种有效机制和工具     

城市智能交通系统与供应链管理协同发展研究

根据城市经济的发展,提出在供应链管理系统中应用智能交通系统,以提高整个物流系统的效益和客户服务水平.在构建供应链管理与智能交通系统协同发展体系结构的基础上,论述了协同发展的技术领域,提出实现协同发展的硬件环境要求和软件约束.结合鄂州市发展现状,对城市智能交通系统与供应链管理的协同发展进行了实证研究.     

复杂SC库存控制系统仿真及现状研究

1．概述1．1供应链及库存系统的发展竞争日益激烈的全球化经济所产生的各种需求,使得人们开始普遍关注供应链及供应链管理。供应链理念已经成为全球主要大型公司的一种普遍的运营实践模式。因此,研究供应链管理的发展有着重要的作用。     

城市智能交通系统与共应链管理协同发展研究

根据城市经济的发展,提出在供应链管理系统中应用智能交通系统,以提高整个物流系统的效益和客户服务水平。在构建供应链管理与智能交通系统协同发展体系结构的基础上,论述了协同发展的技术领域,提出实现协同发展的硬件环境要求和软件约束。结合鄂州市发展现状,对城市智能交通系统与供应链管理的协同发展进行了实证研究。     

完善我国铁路突发事件应急管理法律机制路径探讨

为提高铁路突发事件应急管理水平,完善铁路突发事件应急管理法律机制,为铁路突发事件应急管理提供有效的法律支撑和完备的法律保障,在阐述铁路突发事件和铁路突发事件应急管理法律机制内涵的基础上,针对协同协作机制、社会化机制、应急管理法律体系、应急预案体系、应急管理标准化机制尚不完善等方面,剖析我国铁路突发事件应急管理法律机制掣肘铁路应急管理法治化的困境,提出完善我国铁路突发事件应急管理法律机制的路径,即:完善铁路突发事件应急管理协作机制,完善铁路突发事件应急管理社会化机制,完善铁路突发事件应急管理法律体系,完善铁路突发事件应急预案体系,完善铁路突发事件应急管理标准化机制,最终实现铁路突发事件应急管理的法治化、制度化和科学化。     

基于安全防范和应急处置的铁路应急管理初探

从突发事件应急管理的概念入手，探讨铁路加强应急管理的必要性，结合郑州铁路局应急管理现状，分析应急管理工作存在的问题，提出相应的对策和建议。     

An emergency logistics distribution approach for quick response to urgent relief demand in disasters

Quick response to the urgent relief needs right after natural disasters through efficient emergency logistics distribution is vital to the alleviation of disaster impact in the affected areas, which remains challenging in the field of logistics and related study areas. This paper presents a hybrid fuzzy clustering-optimization approach to the operation of emergency logistics co-distribution responding to the urgent relief demands in the crucial rescue period. Based on a proposed three-layer emergency logistics co-distribution conceptual framework, the proposed methodology involves two recursive mechanisms: (1) disaster-affected area grouping, and (2) relief co-distribution. Numerical studies with a real large-scale earthquake disaster occurring in Taiwan are conducted, and the corresponding results indicate the applicability of the proposed method and its potential advantages. We hope that this study can not only make the proposed emergency logistics system available with more benefits to the development of emergency logistics systems for the urgent needs of disaster areas around the world but also stimulate more excellent researches concerning emergency logistics management.     

Risk management of logistics systems

Nowadays, with the globalization of business operations, logistics systems are threatened by all kinds of uncertainties and disruptions. Almost every month, serious accidents in transportation and natural disasters all around the world are reported in the media. As a result, an effective and efficient risk management scheme is of a top most priority in the mind of all professionals in logistics management. This paper concisely explores risk management of logistics systems in several critical areas, namely disruption risk management, operational risk control, disaster and emergency management, and logistics service risk analysis. The papers featured in the special issue are also introduced and examined. This paper ends with a proposal of various future research directions for advancing risk management of logistics systems.     

Dynamic relief-demand management for emergency logistics operations under large-scale disasters

This paper presents a dynamic relief-demand management model for emergency logistics operations under imperfect information conditions in large-scale natural disasters. The proposed methodology consists of three steps: (1) data fusion to forecast relief demand in multiple areas, (2) fuzzy clustering to classify affected area into groups, and (3) multi-criteria decision making to rank the order of priority of groups. The results of tests accounting for different experimental scenarios indicate that the overall forecast errors are lower than 10% inferring the proposed method’s capability of dynamic relief-demand forecasting and allocation with imperfect information to facilitate emergency logistics operations.     

An integrated approach to modeling the impact of floods on emergency services: A case study of Calgary,Alberta

Floods are becoming more frequent and the magnitude of direct consequences, relating to destruction of critical infrastructure and loss of life, has highlighted the importance of flood management. This study proposes a methodology for quantifying the impact of predicted and historic flood events on emergency services. The approach moves beyond simple flood inundation mapping by accounting for the relationship between flood depth and vehicular speed. A case study is presented for Calgary, Alberta, where the depths of a predicted 100-year flood and a historic 2013 flood event are modeled. The methodology applies geographic information systems to flood depth mapping, utilizing digital elevation models, flood extents, and hydrological data. Flood depths are then assigned to links comprising the road network, where the maximum vehicle speed is calculated as a function of the standing depth of water on a link. The flooded network is used to derive service areas for several types of emergency services (emergency medical services (EMS), fire, and police), following targeted response times. The results locate and quantify the residential and work populations that no longer meet the targeted response times. During both flood scenarios, EMS is found to have the greatest reduction in accessibility, with 23% and 47% of residents and workers, respectively, not served. Fire services are seen to be more resilient with only 3% and 9% of residents and workers, respectively, not served. The results for police services are similar to fire services. However, the former have a greater range of response times, meaning these areas represent those that are completely isolated during both flood events. Overall, the integrated methodology quantifies vulnerable populations on a partially degraded network, the results of which can be used to develop evacuation plans and emergency response strategies.     

Managing the drone revolution: A systematic literature review into the current use of airborne drones and future strategic directions for their effective control

Commercial and private deployment of airborne drones is revolutionising many ecosystems. To identify critical issues and research gaps, our systematic literature review findings suggest that historic issues such as privacy, acceptance and security are increasingly replaced by operational considerations including interaction with and impacts on other airspace users. Recent incidents show that unrestricted drone use can inflict problems on other airspace users like airports and emergency services. Our review of current regulatory approaches shows a need for further policy and management response to both manage rapid and efficient drone usage growth, and facilitate innovation (e.g. intraurban package delivery), with one promising strategic response being low altitude airspace management (LAAM) systems for all drone use cases.     

Generating a spatial coverage plan for the emergency medical service on a regional scale: Empirical versus random forest modelling approach

Adequate spatial coverage by the emergency medical service and the ability to reach any location in the area of interest in the shortest possible time are crucial for the survival of patients with serious conditions. Knowledge of blind spots (i.e. sites that cannot be reached within the required time) represents key information for improving the service quality and may lead, e.g. to a relocation of bases or to other active interventions. Spatial coverage can be derived from experience based on historical data. Such an approach may be problematic if a larger area is being analysed, especially if data is not available for some parts of such areas or if no data is available. To eliminate such problems, we created a prediction model utilising the random forest ensemble learning method. The model is capable of predicting the travel time based on available historical data on ambulance movements (GPS) and the geometric and construction characteristics of individual road segments. We therefore collaborated with the regional public administration and emergency medical service authorities to deliver a time- and resource-efficient solution for emergency spatial planning practice. The outputs from the newly built model were subsequently validated against data from an empirical model currently used by the regional authorities. The results from both models were compared from the perspective of performance in various seasonal and time-of-day conditions. The prediction of travel times using the new model improved according to all the evaluated validation metrics. The importance and applicability of the foregoing model lies in the fact that it can be incorporated into the current emergency medical service management system in a simple manner in terms of data availability and the required computational resources. We conclude that the dynamic model presented in this paper represents an improvement relative to the reference data, and discuss the possibilities of further improving the proposed model.     

Exploring cabin safety services needs of elderly air passengers

The present study was aimed at investigating elderly air passengers’ perceptions and behaviours in case of an emergency in the cabin. It is grounded on the idea that if the seniors have the knowledge of what is happening and how to respond, they might effectively protect themselves during a flight should an emergency situation arise. In the study, 296 elderly passengers filled out a questionnaire measuring their awareness of cabin safety knowledge, safety attitudes and behaviour in the event of an emergency. The results indicate that elderly passengers are not familiar with cabin safety information and tend to have incorrect perceptions of some safety regulations. They are also not confident in preparing for an emergency landing and evacuation. It is thus important for airlines and governments to educate elderly passengers before a flight.     

高速铁路应急调度协同处置流程结构化分析方法研究

高速铁路应急调度处置流程的结构化分析,对于提升应急调度处置效率和质量,推动应急调度智能化进程具有重要意义。针对结构化分析需求,提出一种基于铁路规章的应急调度处置流程分解与重构方法,以图形化方式重构应急调度处置流程,并基于随机Petri网理论建立高速铁路应急调度协同处置流程模型,给出多工种协同的SPN模型建立与等价化简、性能分析的方法,通过计算识别处置流程风险控制点和关键环节,选取场景“运行途中司机发现晃车”建模并分析,分析结果符合现场实际情况,表明该结构化分析方法能够从信息传递和处置流程角度提示风险控制点和关键环节,为多工种协同的应急调度指挥工作提供决策参考。