(Q,S)库存策略在军用油料申请中的应用

依据库存理论,分析了目前军用油料申请方式的局限性,讨论了应用(Q,S)库存策略进行油料申请的优势和实现条件,认为应用(Q,S)库存策略进行油料申请可以解决目前油料申请中存在的一些问题,提高油料管理的军事经济效益。     

供应链环境下的库存控制策略

本文从单极库存控制策略和多级库存控制策略两个层面入手,详细阐述了VMI、JMI、CPFR等库存控制方法,从成本优化和时间优化两方面探讨了多级库存优化控制问题,从而寻求解决供应链环境下库存控制难题的方法。     

基于系统动力学的码头油库战时油料保障决策研究

针对海军码头油库战时油料保障中的油料储存量控制问题,运用系统动力学理论与方法建立了码头油库战时油料库存仿真模型。通过对模型的应用和仿真实验,研究了战时码头油库油料储存量、码头油库所需油料补给量等变量的动态变化规律,分析了油料保障时限和油料补给时间两个参数的改变对码头油库油料储存量以及油料保障的影响,为实施高效、准确的油料保障提供了决策依据。     

基于系统动力学的码头油库战时油料保障决策研究

针对海军码头油库战时油料保障中的油料储存量控制问题,运用系统动力学理论与方法建立了码头油厍战时油料库存仿真模型.通过对模型的应用和仿真实验,研究了战时码头油库油料储存量、码头油库所需油料补给量等变量的动态变化规律,分析了油料保障时限和油料补给时间两个参数的改变对码头油库油料储存量以及油料保障的影响,为实施高效、准确的油料保障提供了决策依据.     

货物库存控制策略的评价方法研究

针对目前库存控制策略较多的情况,提出了一种策略评价方法,并给出了评价方法的评价过程。对该方法进行计算机编程仿真,能够获得最优库存控制策略。     

CHC水泥集团库存优化管理解决方案

库存管理作为生产管理的重要内容,是企业降低成本,增强市场竞争优势,提高经济效益的重要手段。论文在对CHC（嘉新京阳）水泥集团库存控制现状进行分析的基础上,揭示了该集团库存管理所存在的问题,提出了CHC水泥集团库存控制策略和控制模型;同时,为保证库存控制策略的实施,结合实际情况,对CHC水泥集团库存业务流程和组织进行了调整,并将信息管理系统升级到ERP系统以配合库存管理新策略实施。     

基于系统动力学仿真决策模型的油库库存控制研究

对油库库存控制系统进行研究,结合油料收发的动态过程,运用系统动力学理论构建油库库存控制仿真决策模型,通过Vensim仿真平台模拟案例进行分析验证,为油库库存控制提供了一种新方法.     

军队油料投送方案模型化研究

针对军队油料保障力量建设发展及运用的实际。提出了军地油料一体化供应力量投送思想。结合这一思想，为有效发挥运输同庞大库存相比所具有的灵活性与相对较低的成本优势，建立了以运输为基础的油料保障系统。在建立以配送为基础的快速油料保障系统的前提下。设计了油料投送模型，分析了晟优投送方案。最后结合实例说明了模型建立的正确性与有效性。     

随机库存控制策略的优化仿真

针对多周期随机库存模型,采用库存策略,利用Excel及其专用插件Crystal Ball完成了库存系统的仿真,并运用OptQuest实现了库存策略的优化。结果表明该方法是解决随机库存控制策略的有效方法。     

装甲装备周转器材多级库存控制优化研究

分析了我军装甲装备周转器材库存控制现状,借鉴供应链管理环境下的多级库存优化控制思想和美军先进的速率管理理论,采用联合库存管理和多级库存优化控制策略对周转器材库存进行优化控制。     

货运车辆燃油消耗与运输效率关系研究

文中采用理论分析与模型构建相结合的方式,研究货运车辆的燃油消耗与运输效率之间的关系,基于调研数据,采用回归分析的方法构建模型,得到了不同车型车辆的百吨公里燃油消耗量与实载率的倒数关系模型,为企业提高车辆运输效率,降低燃油消耗提供数据参考。     

Economic uncertainty,oil prices,hedging and U.S. stock returns of the airline industry

This paper examines the impacts of economic policy uncertainty and oil price shocks on stock returns of U.S. airlines using both industry and firm-level data. Our empirical approach considers a structural vector-autoregressive model with variables recognized to be important for airline returns including jet fuel price volatility. Empirical results confirm that oil price increase, economic uncertainty and jet fuel price volatility have significantly adverse effect on real stock returns of airlines both at industry and at firm level. In addition, we also find that hedging future fuel purchase has statistically positive impact on the smaller airlines. Our results suggest policy implications for practitioners, managers of airline industry and commodity investors.     

国际初级产品分类价格对中国物价传导效应的实证研究

文章基于2001年1～12月的月度数据,对国际初级产品分类价格对中国物价的传导效应进行了实证分析。结果表明:国际初级产品价格对国内物价的传导效应具有由短期波动到长期均衡的动态机制特征,其对PPI和CPI均具有显著的正向影响。各分类价格指数对国内物价的影响之间存在较大差异,燃料价格对国内物价的影响最大且持续时间最长,非燃料价格的影响较小且持续时间相对短。燃料价格和农业原材料价格对PPI的影响显著,燃料价格、农业原材料价格和食品价格对CPI的影响显著,其他子成分的影响力很弱。     

基于VAR模型探究BDI和燃油价格的相互影响

燃油价格近期受疫情影响出现剧烈波动,国际干散货航运市场也受到巨大影响。基于Clarksons官方数据库1992年1月至2020年4月相关数据,进行实证研究发现,国际燃油价格的暴跌对波罗的海干散货运价指数的下降有着显著的正向影响;燃油价格虽然也在一定程度上受到BDI的影响,但存在一定的滞后性。这有利于干散货运输公司根据燃油价格波动预测运价指数的变化趋势,从而采取多样的方式应对冲击。也对保障干散货运输市场的稳定发展有重要意义。     

Determining optimal fuel delivery strategies under uncertainty

During the preparation before a hurricane makes landfall, affected individuals may be asked to evacuate. Large and small-scale evacuations can cause rapid increases in the demand for gasoline fuel. However, during a hurricane vessels carrying gas may be delayed and/or rerouted, adding to the difficulty of providing the necessary gas in affected areas. In this work, we determine alternate delivery locations and times for vessels carrying fuel that are scheduled to arrive and deliver fuel at ports impacted by an approaching hurricane. Motivated by Hurricane Irma in Florida, we develop a multi-period stochastic scheduling model that incorporates hurricane (weather) advisories, fuel delivery schedules, port storage capacities, and port docking capacities. Our model determines the best schedule based on two objectives: (1) minimize the total unmet demand at each port, and (2) minimize inequities in unmet demands among the ports. We also present a case study and a numerical experiment based on fuel delivery data from ports in Florida. Among our key findings is that port availability is the driving factor in determining feasible schedules for vessel gas deliveries. We also present a scheduling heuristic that dynamically adapts to weather advisories so as to minimize the impact of unmet demand in the affected areas.     

Regional forecasting of the demand for fossil fuels by electric utilities in the United States

The possibility of interfuel substitution in the generation of electrical energy exists. Given this fact, a demand model for various fossil fuels by electric utilities in the United States is developed. Using regional data, the results suggest that the responsiveness of the demand for coal, residual fuel oil, distillate fuel oil, and natural gas by electric utilities to relative price changes is significant. In a forecasting setting, the demand model performs remarkably well when actual and forecast values for 1979 are compared.     

Bayesian estimation of manufacturing effects in a fuel economy model

The analysis of fuel economy data results in estimates of the technology utilization by manufacturer and vehicle line. The analysis employs a hierarchical Bayesian regression model with random components representing vehicle lines and manufacturers. The model includes predictor variables which describe vehicle features, such as type of transmission, and vehicle line specific measurements, such as compression ratio. Non-informative priors with novel modifications are used and the Bayes estimates are obtained by use of Gibbs sampling. The results show there is substantial variability among manufacturers in efficiently utilizing technology for fuel economy.     

解析:大数据汽车电子故障远程在线诊断技术的应用

随着汽车电子化程度日益提高,通过移动互联与大数据的运用,对行驶中的汽车电子控制系统(燃油喷射系统、自动变速器、制动防抱死系统、安全气囊、空调、悬架等)进行远程在线诊断(On Board Diagnostic),将自动诊断所得到的汽车主要部件的工作状态与系统故障(故障码及数据流)利用移动互联与大数据连接到服务中心,并进行远程车辆诊断,以便随时为驾乘人员以及维修人员提供准确的故障位置和原因成为必然。     

Carpooling and driver responses to fuel price changes: Evidence from traffic flows in Los Angeles

We examine carpooling and driver responses to fuel price changes. Using a simple theoretical model, we show that traffic flows in mainline lanes unambiguously decrease when fuel prices increase, and this effect is stronger when the presence of a carpool lane provides a substitute to driving alone. In contrast, in carpool (HOV) lanes flow can either increase or decrease. These predictions are tested using 8 years of traffic flow data for 1700 locations in Los Angeles. In our preferred specification, the mean elasticity of flow with respect to fuel price is 0.136 for HOV lanes. For a 10% increase in fuel price this implies 10 additional carpools per hour, $8.8 million per year in additional congestion costs for carpoolers and $11.3 million lower costs for mainline drivers. For mainline lanes, flow elasticities are −0.083 and −0.050 for highways with and without an HOV lane. These estimates imply that the mean highway with an HOV lane experiences a 30% larger decrease in hourly flow compared to the mean highway without an HOV lane. Flows in HOV lanes show an immediate decrease following a price increase but respond positively to price increases over time, which suggests time is an important input to carpool formation.     

A study in using linear programming to design non-urban attendance areas

A great deal of recent work has been directed toward using mathematical programming to achieve racial balance in urban schools. However, with the ever increasing cost of fuel for buses, there also appears to be a need to apply these techniques in non-urban school districts to reduce the use of fuel. This paper describes the development of a linear programming model to assign students to schools in such a way, as to minimize student-miles. Using data gathered in a non-urban school district, this model was tested on a large scale linear programming package with encouraging results. The resulting computational results are presented and discussed along with comments on the additional work necessary to implement this model.