A multi-warehouse inventory model for items with time-varying demand and shortages

This paper develops a deterministic replenishment model with multiple warehouses (one is an owned warehouse and others are rented warehouses) possessing limited storage capacity. In this model, the replenishment rate is infinite. The demand rate is a function of time and increases at a decreasing rate. The stocks of rented warehouses are transported to owned warehouse in continuous release pattern. The model allows shortages in owned warehouse and permits part of the backlogged shortages to turn into lost sales—which is assumed to be a function of the currently backlogged amount. The solution procedure for finding the optimal replenishment policy is shown. As a special case of the model, the corresponding models with completely backlogged shortages and without shortages are also presented. The models are illustrated with the help of numerical examples. Sensitivity analysis of parameters is given in graphical form.Scope and purposeIn practical inventory management, there exist many factors like an attracted price discount for bulk purchase, etc. to make retailers buy goods more than the capacity of their owned warehouse. In this case, retailers will need to rent other warehouses or to rebuild a new warehouse. However, from economical point of views, they usually choose to rent other warehouses. If there are multiple warehouses available, an important problem faced by the retailers is which warehouses to be selected to hold items replenished, when to replenish as well as what size to replenish. For such a problem, the existing two-warehouse models, based on an unrealistic assumption that the rented warehouse has unlimited storage capacity, presented some procedures for determining the optimal replenishment policy. This paper extends the existing two-warehouse models in three directions. Firstly, the traditional two-warehouse models assumed the storage capacity of the rented warehouse unlimited. The present paper relaxes this impractical assumption and considers the situation with multiple rented warehouses having a limited capacity. Secondly, the traditional two-warehouse models considered a constant demand rate or a linearly increasing demand rate. In this model, the demand rate varies over time and increases at a decreasing rate, which implies an increasing market going to saturation. Thirdly, we extend the two-warehouse models to the case with partially backlogged shortages. The purpose of this paper is to build a multi-warehouse replenishment model to help decision-makers solve the problem of which warehouses to be chosen to store items replenished and how to replenish.     

基于组件和设计模式的仓库系统框架

本文从仓库管理的需求出发，应用软件的组件和设计模式思想，设计实现了一个仓库的框架．该框架提供了仓库管理的仓库结构、仓库创建、业务管理、仓库分析和控制等基础功能．使用本框架所设计的组件和服务，通过具体应用的配置和简单扩展，可以高效高质量地建立起多层体系结构的仓库应用系统．本文的框架已经在实际仓库系统中获得应用．     

Managing dual warehouses with an incentive policy for deteriorating items

Distributors in a supply chain usually limit their own warehouse in finite capacity for cost reduction and excess stock is held in a rent warehouse. In this study, we examine inventory control for deteriorating items in a two-warehouse setting. Assuming that there is an incentive offered by a rent warehouse that allows the rental fee to decrease over time, the objective of this study is to maximise the joint profit of the manufacturer and the distributor. An optimisation procedure is developed to derive the optimal joint economic lot size policy. Several criteria are identified to select the most appropriate warehouse configuration and inventory policy on the basis of storage duration of materials in a rent warehouse. Sensitivity analysis is done to examine the results of model robustness. The proposed model enables a manufacturer with a channel distributor to coordinate the use of alternative warehouses, and to maximise the joint profit of the manufacturer and the distributor.     

基于XML的数据立方体的实现

数据仓库系统正广泛用于联机分析处理系统，为了能将多个数据仓库集成到一起，需要解决技术上和语义上的一些问题。一种基本的解决方法是建立一种标准化的、独立于各供应商的多维数据描述格式。本文介绍一个基于XML的文档模板集——xCube，它可在任何网络上交换数据仓库数据。由于XCube被组织成模块化的形式，所以立方体的多维模式、维数据和事实数据能分步传输，因此立方体都能很容易从一个数据仓库传输到另一个数据仓库。     

Web数据仓库的异步迭代查询处理方法

数据仓库信息量的飞速膨胀对数据仓库提出了巨大挑战.如何提高Web环境下数据仓库的查询效率成为数据仓库研究领域重要的研究问题.对Web数据仓库的体系结构和查询方法进行了研究和探讨.在分析几种Web数据仓库实现方法的基础上,提出了一种Web数据仓库的层次体系结构,并在此基础上提出了Web数据仓库的异步迭代查询方法.该方法充分利用了流水线并行技术,在Web数据仓库的查询处理过程中不同层次的结点以流水线方式运行,并行完成查询的处理,提高了查询效率.理论分析表明,该方法可以有效地提高Web数据仓库的查询效率.     

Regression approximation for a partially centralized inventory system considering transportation costs

Inventory centralization for multiple stores with stochastic demands reduces costs by establishing and maintaining a central ordering/distribution point. However the inventory centralization may increase the transportation costs since either the customer must travel more to reach the product, or the central warehouse must ship the product over longer distance to reach the customer. In this paper, we study a partially centralized inventory system where multiple central warehouses exist and a central warehouse fulfills the aggregated demand of stores. We want to determine the number, the location of central warehouses and an assignment of central warehouses and a set of stores. The objective is the minimization of the sum of warehouse costs and transportation cost. With the help of the regression approximation of cost function, we transform the original problem to more manageable facility location problems. Regression analysis shows that the approximated cost function is close to the original one for normally distributed demands.     

遗传算法在立体仓库货位优化分配中的研究

存储一定数量货物的自动化仓库中,以基于随机存储策略的库区和货位分配以及堆垛机行驶时间为优化控制目标,针对自动化立体仓库的库区和货位的分配策略问题进行了讨论,提出立体仓库的库区优化数学模型。在库区优化基础上,进一步提出货位优化数学模型,将Pareto最优解的概念与遗传算法相结合,提出了一种解决多目标优化问题的Pareto遗传算法解决货位优化问题,给出了仿真实验及分析。结果表明采用遗传算法优化策略可以有效地解决自动化立体仓库的货位优化分配问题。     

Development of a clinical data warehouse from an intensive care clinical information system

There are relatively few institutions that have developed clinical data warehouses, containing patient data from the point of care. Because of the various care practices, data types and definitions, and the perceived incompleteness of clinical information systems, the development of a clinical data warehouse is a challenge.In order to deal with managerial and clinical information needs, as well as educational and research aims that are important in the setting of a university hospital, Erasmus Medical Center Rotterdam, The Netherlands, developed a data warehouse incrementally. In this paper we report on the in-house development of an integral part of the data warehouse specifically for the intensive care units (ICU-DWH). It was modeled using Atos Origin Metadata Frame method. The paper describes the methodology, the development process and the content of the ICU-DWH, and discusses the need for (clinical) data warehouses in intensive care.     

A study on two-warehouse partially backlogged deteriorating inventory models under inflation via particle swarm optimisation

This paper deals with a deterministic inventory model for linear trend in demand under inflationary conditions with different rates of deterioration in two separate warehouses (owned and rented warehouses). The replenishment rate is infinite. The stock is transferred from the rented warehouse to owned warehouse in continuous release pattern and the associated transportation cost is taken into account. At owned warehouse, shortages, if any, are allowed and partially backlogged with a rate dependent on the duration of waiting time up to the arrival of the next lot. The corresponding problems have been formulated as nonlinear constrained optimisation problems for two different policies (inventory follows shortage (IFS) and shortage follows inventory (SFI)). Finally, the model has been illustrated with a numerical example and to study the effects of changes of different system parameters on initial stock level, maximum shortage level and cycle length with the minimum cost of the system, sensitivity analyses have been carried out by changing one parameter at a time and keeping the others at their original values.     

基于Apriori算法的立体仓库系统

传统仓库存储采用人力或人机结合方式搬运货物,采用纸笔记录相关库存和进出入库数据,存在效率低、安全隐患多和用人成本高等诸多问题.现代化工商业的发展对仓库存储技术提出了更高的需求,不仅仅局限于成本范畴,更成为获取利润的战略工具.本文介绍了自动化立体仓库系统的整体结构、各子系统功能及主要部分的设计.为了进一步提高生产效率,提升公司总体收益率,本文基于实验室的自动化立体库系统,将关联规则数据挖掘Apriori算法应用于其中,对出库信息进行挖掘,提供更加科学的生产和出库建议.该系统具有高度自动化、智能化、信息化管理等特点,对提高仓储管理效率,提高企业收益具有重要意义.     

Heuristics for determining the number of warehouses for storing non-compatible products

In this paper we discuss a version of the classical knapsack problem, where the objective is to minimize the number of warehouses needed to store given items, each with some space requirements. In this version, some of the items are incompatible with each other, and cannot be stored together. We apply some newly developed heuristics to this problem and compare the results with other available algorithms. The computational results are presented and indicate that higher quality solutions can be obtained using the new heuristics.     

制造物联环境下智能仓库货位分配模型

仓库货位合理规划与分配是减少产品存取时间、提高仓库作业效率的关键。在构建基于制造物联技术的智能仓库环境下,针对多品种智能仓库的货位分配问题,建立了考虑多规则约束的多目标智能仓库货位分配模型,提出一种模型求解的改进遗传算法。实验表明：模型和算法能找到有效的仓库货位分配方案,验证了其有效性。     

基于遗传模拟退火算法的立体仓库储位优化

针对自动化立体仓库储位分配问题,结合仓库运作特点和安全性要求,构建了自动化立体仓库储位优化问题的多目标模型,并提出了求解模型的基于Sigmoid曲线的改进自适应遗传模拟退火算法（SAGA）。首先,以降低货品出入库时间、同组货品距离和货架重心为目标建立储位优化模型;然后,为了克服遗传算法（GA）局部搜索能力差和易陷入局部最优的缺点,引入基于Sigmoid曲线的自适应交叉变异操作和逆转操作,同时完成与SAGA的融合;最后,对改进遗传SAGA进行算法优化性、稳定性和收敛性测试。仿真实验表明,相比模拟退火（SA）算法的求解结果,该算法对货品出入库时间的优化度提高了37.7949个百分点、对同组货品距离提高了58.4630个百分点、对货架重心优化度提高了25.9275个百分点,并且该算法具有更好的稳定性和收敛性。由此验证了改进遗传SAGA求解问题的有效性,该算法可为自动化立体仓库储位优化提供决策方法。     

数据仓库的质量管理问题和方法

A data warehouse is often a large-scale information system for an enterprise,so its quality management isimportant and difficult. Recently, some researchers have studied the problems of quality management in data ware-houses from different views ,and achieved some good results. This paper will broadly introduce the concept ,methods and techniques in quality management in data warehouses ,and discuss the important quality factors in data warehous-es in detail.     

基于数据仓库和OLAP技术的证券交易系统的实现方案研究

数据仓库和联机分析处理(OLAP)技术是信息技术领域的新兴技术,而如何应用到证券交易中是证券业面临的问题。建立证券交易数据仓库并使用OLAP技术,可以将大量源数据有效地转化为有用的知识信息,并服务于决策过程。基于数据仓库的证券交易系统就是在面向信息处理的联机事务处理(OLTP)系统的基础上并引入数据仓库和OLAP技术而发展起来的。论文结合证券交易业务提出了系统实现的解决方案,并给出了基于证券交易业务的数据仓库的体系结构、逻辑模型、粒度模型,以及基于证券交易业务的联机分析处理(OLAP)系统的实现方法。     

Agent技术在Web数据仓库结构中的应用研究

针对基于Web的数据仓库体系结构存在的问题,在该体系结构中引入软件Agent技术,运用移动Agent技术来解决传统方法难以解决的一些主要问题,提出了一种基于Agent的Web数据仓库系统体系结构。文中发挥数据仓库技术和Web技术结合的优势,重点研究了Agent技术在Web服务器端的应用,在把有用的Web数据集成并入到数据仓库中这一目前的研究热点问题中,提出了基于Agent技术将HTML页面转化为XML数据源的解决方案。此外,文章分别研究了应用服务器端和数据仓库系统中的Agent技术的应用,并提出了将Agent技术引入后实现基于Web的数据仓库体系的关键技术。     

超大型压缩数据仓库上的CUBE算法

数据压缩是提高多维数据仓库性能的重要途径,联机分析处理是数据仓库上的主要应用,Cube操作是联机分析处理中最常用的操作之一.压缩多维数据仓库上的Cube算法的研究是数据库界面临的具有挑战性的重要任务.近年来,人们在Cube算法方面开展了大量工作,但却很少涉及多维数据仓库和压缩多维数据仓库.到目前为止,只有一篇论文提出了一种压缩多维数据仓库上的Cube算法.在深入研究压缩数据仓库上的Cube算法的基础上,提出了产生优化Cube计算计划的启发式算法和3个压缩多维数据仓库上的Cube算法.所提出的Cube算法直     

基于数据驱动的螺旋式数据仓库开发方法的研究

文章首先分析了数据仓库与数据库技术本质的区别,讨论了软件系统开发的生命周期方法、快速原型法、螺旋法的特点,然后结合数据仓库开发特点,提出了基于数据驱动的螺旋式开发方法,并给出运用该方法开发数据仓库的步骤。     

A two-warehouse inventory model with imperfect quality production processes

One of the weaknesses of some production-inventory models is the unrealistic assumption that all items produced are of good quality. But production of defective units is a natural phenomenon in a production process. Defective items should be treated as a result of imperfect quality production. On the other hand, the classical inventory models usually assume the available warehouse has unlimited capacity. In many practical situations, there exist many factors like temporary price discounts making retailers buy a capacity of goods exceeding their own warehouse. In this case, retailers may rent other warehouses for the need of business. A lot of researchers studied inventory models with two warehouses and inventory models with imperfect quality separately. Compared with previous models, based on Salameh and Jaber [Salameh, M. K., Jaber, M. Y. (2000). Economic production quantity model for items with imperfect quality. International Journal of Production Economics, 64, 59–64.], this paper tries to incorporate the above concepts to establish a new inventory model with two warehouses and imperfect quality simultaneously. The mathematical model by maximizing the annual total profit and the solution procedure are developed and numerical examples are provided to illustrate them.     

Lagrangean-based solution approaches for the generalized problem of locating capacitated warehouses

The traditional capacitated warehouse location problem consists of determining the number and the location of capacitated warehouses on a predefined set of potential sites such that the demands of a set of customers are met. A very common assumption made in modeling this problem in almost all of the existing research is that the total capacity of all potential warehouses is sufficient to meet the total demand. Whereas this assumption facilitates to define a well‐structured problem from the mathematical modeling perspective, it is in fact restrictive, not realistic, and hence rarely held in practice. The modeling approach presented in this paper breaks away from the existing research in relaxing this very restrictive assumption. This paper therefore investigates the generalized problem of locating warehouses in a supply chain setting with multiple commodities with no restriction on the total capacity and the demand. A new integer programming formulation for this problem is presented, and an algorithm based on Lagrangean relaxation and decomposition is described for its solution. Three Lagrangean heuristics are proposed. Computational results indicate that reasonably good solutions can be obtained with the proposed algorithms, without having to use a general purpose optimizer.