基于最优定权组合模型的物流量预测

为了实现对市场需求变动的准确估计,在经过参阅大量文献之后,采用趋势外推模型、灰色GM（1,1）模型分别进行物流量的预测,以每种方法单项预测结果组合误差平方和最小为原则,提出一种最优定权组合预测模型,以此为物流园区的合理规划做出贡献。     

Seasonal exponential smoothing with damped trends : An application for production planning

This paper reviews a spreadsheet-based forecasting approach which a process industry manufacturer developed and implemented to link annual corporate forecasts with its manufacturing/distribution operations. First, we consider how this forecasting system supports overall production planning and why it must be compatible with corporate forecasts. We then review the results of substantial testing of variations on the Winters three-parameter exponential smoothing model on 28 actual product family time series. In particular, we evaluate whether the use of damping parameters improves forecast accuracy. The paper concludes that a Winters four-parameter model (i.e. the standard Winters three-parameter model augmented by a fourth parameter to damp the trend) provides the most accurate forecasts of the models evaluated. Our application confirms the fact that there are situations where the use of damped trend parameters in short-run exponential smoothing based forecasting models is beneficial.     

DeepAR: Probabilistic forecasting with autoregressive recurrent networks

Probabilistic forecasting, i.e., estimating a time series’ future probability distribution given its past, is a key enabler for optimizing business processes. In retail businesses, for example, probabilistic demand forecasts are crucial for having the right inventory available at the right time and in the right place. This paper proposes DeepAR, a methodology for producing accurate probabilistic forecasts, based on training an autoregressive recurrent neural network model on a large number of related time series. We demonstrate how the application of deep learning techniques to forecasting can overcome many of the challenges that are faced by widely-used classical approaches to the problem. By means of extensive empirical evaluations on several real-world forecasting datasets, we show that our methodology produces more accurate forecasts than other state-of-the-art methods, while requiring minimal manual work.     

The use of advance order data in demand forecasting

This paper uses advance order data and historical demand data from a manufacturing shop and from a service operation to develop and test a forecasting methodology for predicting customer demand over a forecast horizon. The proposed methodology uses simple linear regression to model the relationship between a total demand ratio and a partial demand ratio. Comparison of the proposed model to a standard regression approach and a commonly used multiplicative model showed that the proposed model exhibited the greatest forecast accuracy.     

No excuses: forecasting can be managed

Originally written for manufacturers, the forecasting concepts presented in this article are easily applied to a hospital or health care facility with a supply function or central distribution center. Forecasting can offer a method of managing the control of medical supplies, pharmaceuticals, or maintenance items. A statistical based forecasting approach with seasonality testing could be useful in analyzing patient census data, calculating trends, and then recommending staffing levels. Cost containment and efficiency of operations are priorities in any industry. Forecasting the demand of medical supplies and services in today's hectic health care environment can have a significant effect on both customer service and financial results. The bottom line is happy patients and healthy profits.     

基于人员和车辆可租赁条件下的车辆路径选配模型及优化

物流服务供应商面临的决策问题常常是复杂的规划问题。文中考虑短程的计划,物流服务供应商在需求点的时间窗、车辆的容积和人员的调度,包括租用的人员和车辆的条件下决定收发件路线,建立了路线和人员调度相结合的规划模型。采用节约启发式算法来求解车辆路径问题,得到路线安排的满意解。之后采用贪婪启发式算法对人员进行分配,通过实际案例得出:在租赁人员和车辆的情况下比不租赁人员和车辆总的费用更低。结果表明,启发式算法既能够满足时间限制,又能够节约运输里程和费用。     

区域性物流产业集聚区发展规划研究

现代物流服务体系的建设重点在于物流产业集聚区的建设与规划,在分析物流网络体系的基础上,明晰物流产业集聚区的内涵、规划原则和规划重点。以新沂市物流产业集聚区为案例,探讨区域性物流产业集聚区规划中的市场需求预测、战略愿景、规划目标、产业导向和重点项目。     

Safety stocks and component commonality

In the implementation of an MRP-based planning system it is often desirable to hold safety stocks at the component level. This approach is typical of a system that assembles finished products to order but builds components to a forecast. The same approach makes sense when end-item buffers would be prohibitively expensive to maintain, or when there is significant spares demand for the components.The existing theory for sizing component safety stocks is little more than an application of the principles governing single-level inventory decisions. The standard deviation of the distribution for demand is the key parameter. A multiple of this standard deviation, called the safety factor, is set by management policy. This safety factor determines the size of the safety stock. In simple cases there is a direct relationship between the safety factor and the level of customer service.Component commonality refers to a situation in which one component is common to more than one end item. The presence of commonality makes it difficult to determine safety stocks accurately. The existing theory, which is reviewed briefly, examines the effects of commonality on the component's safety factor. However, commonality destroys the relationship between safety factor and service level. This article introduces a simple example to illustrate this fact. The example suggests some problems that must be addressed if the theory is to encompass commonality. Among these are the need to develop service level measures for multiple products and to analyze the relationship between safety stock and service level.     

Effects of amalgamations: evidence from Swiss municipalities

Many OECD countries have amalgamated their municipalities during the last couple of decades. For decisions concerning future territorial rescaling, it is crucial to augment the previously inconclusive evaluative knowledge of the effects of mergers. This paper examines the effects of amalgamations conducted between 1998 and 2009 in the areas of public service delivery, local finance, administrative staff, municipal autonomy and local democracy. The data are obtained from two comprehensive surveys of all local secretaries (top civil servants) in Switzerland in 1998 and 2009. The analysis – based upon a comparison between a quasi-experimental and a control group – (partially) supports the hypothesis of a positive effect on public service delivery, the professionalization of staff and municipal autonomy. The effect on local finance is inconclusive, and negative effects on local democracy are not discovered in the framework of this study.     

Evaluating spatial service and layout efficiency of municipal Wi-Fi facilities for SmartCity planning: A case study of Wuhan city,China

This paper explores an approach to evaluating spatial service and layout efficiency of municipal Wi-Fi facilities for cyber infrastructure planning in the construction of a smart city. Based on the equilibrium principle that Wi-Fi services supply should meet the spatial demand for recreation, urgency, and security, two evaluation models were built. In the first model, the spatial service efficiency of Wi-Fi facilities is measured by a mean ratio of three types of demand spaces covered by Wi-Fi service. In the other model, spatial layout efficiency of each Wi-Fi facility is calculated by a demand load indicator - the sum of the three types of demand space's ratios of served quantity to the average quantity it should carry, and then assessed by relationship with its adjacent facilities. Corresponding statistical methods and analysis processes were also designed using the function modules found in ArcGIS software. The approach was applied to Wuhan city in 2016. After overlaying influence areas of 688 Wi-Fi facilities with demand spaces of 137 access points for recreation, 1200.99 km roads for urgency, 121.54 km² regions for security, the results show that there exists a spatial disequilibrium between supply and demand of Wi-Fi service in Wuhan due to lack of comprehensive planning. Specifically, there are 67 points, 700.76 km roads, and 42.59 km² regions of demand spaces covered by Wi-Fi service, with service efficiencies of 48.91%, 58.35%, and 35.04% respectively and an overall spatial service efficiency of 47.43%. Among all the Wi-Fi facilities, there are 481 carrying saturated demand, 3 straying from the centre of demand space, and 204 redundant. The overall spatial layout efficiency of Wi-Fi facilities is 43.01%. The conclusion is that the dense and massive redundant Wi-Fi facilities should be optimized, especially in the centre areas along the confluence of Yangtze and Han rivers and new Wi-Fi facilities supplemented in other ill-equipped areas. Since many metropolitan cities experience the same problem, this novel approach will find wide application in the future and offer improved evaluation strategies for researchers and policymakers.     

Demand forecasting and order planning for humanitarian logistics: An empirical assessment

Humanitarian aid organizations are most known for their short-term emergency relief. While getting aid items to those in need can be challenging, long-term projects provide an opportunity for demand planning supported by forecasting methods. Based on standardized consumption data of the Operational Center Amsterdam of Médecins Sans Frontières (MSF-OCA) regarding nineteen longer-term aid projects and over 2000 medical items consumed in 2013, we describe and analyze the forecasting and order planning process. We find that several internal and external factors influence forecast and order planning performance, be it indirectly through demand volatility and safety markup. Moreover, we identify opportunities for further improvement for MSF-OCA, and for humanitarian logistics organizations in general.     

Co-Production and the Co-Creation of Value in Public Services: A suitable case for treatment?

Co-production is currently one of cornerstones of public policy reform across the globe. Inter alia, it is articulated as a valuable route to public service reform and to the planning and delivery of effective public services, a response to the democratic deficit and a route to active citizenship and active communities, and as a means by which to lever in additional resources to public service delivery. Despite these varied roles, co-production is actually poorly formulated and has become one of a series of ‘woolly-words’ in public policy. This paper presents a conceptualization of co-production that is theoretically rooted in both public management and service management theory. It argues that this is a robust starting point for the evolution of new research and knowledge about co-production and for the development of evidence-based public policymaking and implementation.     

基于灰色系统理论的茂名市物流需求预测分析

物流产业发展规划的制定、物流基础设施建设的可行性研究等都需要有确切的物流需求数据作为依据．因此,建立科学合理的预测模型对物流需求进行定量预测,就显得尤为重要。通过建立GM（1,1）来对茂名物流需求量进行定量预测,同时根据预测结果提出相应的对策,试图为茂名市政府制定物流决策提供一定的参考。     

基于订单生产的供应链价格与承诺交货时间决策和协调

针对订单生产需求受价格和承诺交货时间影响以及延期现象,建立由生产商和销售商组成的供应链价格与承诺交货时间决策模型。研究表明:最优承诺交货时间绑定在服务水平上,提高服务水平可以降低双重边际化效应;相对于集中决策,分散决策采用较高的价格和较短的承诺交货时间,其最优利润和最优需求较少;此外,采用收益分享方式构建了供应链协调模型,得出销售商收益分享比例处于某一范围内才能实现供应链的协调。     

On exploiting scale economies

Indivisibilities give rise to scale economies in the provision of many local public services. Exploitation of these scale economies often requires that the activities of several communities be coordinated. In this study we analyze the game analog to a simple waste collection system in order to determine the requirements for the design of a financing system that will sustain optimal participation in a regional service system plan. We find that market based pricing in the face of scale economies created by indivisibilities will generally not support an optimal partition of communities into service districts. We also find that characterization of the game structure of local public service delivery systems is feasible and provides information for designing appropriate cost-sharing arrangements.     

A reformulation of the aggregate planning problem

This article proposes a reformulation of the aggregate planning problem which more closely agrees with situations frequently encountered in practice. The proposed reformulation assumes that a firm's production planners want to determine the expected service and inventory levels for a given production profile in the face of uncertain seasonal demand. By using several different production profiles that are each consistent with the firm's staffing, subcontracting, and overtime policies, it is possible to pick the profile that best meets the firm's preferences for service level and inventory turns. Actually, the trade-offs between inventory and service levels are examined so that an informed choice can be made by all of those concerned.One of the advantages of the proposed model is that communications can be established among production, marketing, and finance managers who often have conflicting goals. Also, levels for inventory turns, service, and production can be set that are consistent with each other. Furthermore, several alternative production profiles can be examined in a relatively short time through the use of the simulation model proposed.An application of the model to the Wagner Spray Tech Company, a producer of painting equipment, is presented. In this particular case, where forecasting errors are quite high, some of the potential uses of the model are presented. Also, reasons are given why this particular reformulation of the aggregate planning problem was found to be useful.     

基于IOWA算子的灰色—多项式组合模型在武汉市物流需求预测中的应用

针对2002～2009年武汉市物流需求的数据,采用灰色GM 1,1模型和多项式拟合模型两种单项预测模型对数据进行建模预测。并结合组合预测理论,采用基于IOWA算子的组合预测模型进行预测,结果表明基于诱导有序加权平均算子的组合预测模型的预测精度明显高于两种单项预测方法,说明了该方法用于物流需求预测的可行性和有效性,并在此基础上对2010～2012年的武汉市物流需求作出预测。     

Daily retail demand forecasting using machine learning with emphasis on calendric special days

Demand forecasting is an important task for retailers as it is required for various operational decisions. One key challenge is to forecast demand on special days that are subject to vastly different demand patterns than on regular days. We present the case of a bakery chain with an emphasis on special calendar days, for which we address the problem of forecasting the daily demand for different product categories at the store level. Such forecasts are an input for production and ordering decisions. We treat the forecasting problem as a supervised machine learning task and provide an evaluation of different methods, including artificial neural networks and gradient-boosted decision trees. In particular, we outline and discuss the possibility of formulating a classification instead of a regression problem. An empirical comparison with established approaches reveals the superiority of machine learning methods, while classification-based approaches outperform regression-based approaches. We also found that machine learning methods not only provide more accurate forecasts but are also more suitable for applications in a large-scale demand forecasting scenario that often occurs in the retail industry.     

基于影响因素多维融合与贝叶斯概率更新的电力物资需求预测

通过梳理电力物资需求预测中存在的真实需求和计划需求、物资出库量和真实需求的不一致,以及电力物资需求的内外部影响问题,提出基于影响因素多维融合与贝叶斯概率更新的电力物资需求预测方法。首先分析了电力物资需求的内外部影响因素及其筛选,并按其对需求预测的影响程度进行权重赋值;其次设计了影响因素多维融合与贝叶斯概率更新的电力物资需求预测框架,介绍了贝叶斯概率更新的需求预测流程步骤;最后以温州市10kv配网项目的电力电缆需求预测为例进行算例说明。应用算例表明该方法能有效反映需求因素对电力物资需求变动的影响,符合电力物资需求特性,且具有很强的拓展性。     

供应商供给策略形成的牛鞭效应分析

在采用满足市场需求经营策略下，针对供应链上成员共享与没有共享信息的情况，我们分别给出了供应链上各成员为满足用户需求而对最终产品需求进行预计的模型，利用所建立的模型讨论了该经营策略形成的牛鞭效应，并指出了供应链上每往上游前进一步，最终产品需求预测放大的数量。最后，讨论了信息共享对控制该种策略下牛鞭效应的效果。