随机局部弹性及在库存管理中的应用

提出随机局部弹性的概念，讨论了相应的运算法则，研究了不允许缺货的存贮模型中，总费用对采购量与采购周期的局部弹性。给出了总费用联合概率密度的一般表达式。通过实例说明，当采购量与采购周期的分布特性已知时，总费用的弹性变化范围就完全被确定。     

随机需求弹性及在经济分析中的应用

引入随机弹性的概念及随机弹性的相关性质，进而给出随机需求弹性．利用随机需求弹性分析了当消费群体的收入为随机变量时，其收入对需求量的变化和影响．给出了当收入服从某种分布时，需求量的弹性分布．     

三种物资同时段需求的EOQ模型

本文研究了三种物资同时段需求的EOQ模型,从理论以及实例均说明了该模型相对单一物资的EOQ模型,能够缩小这三种物资对仓库的占用空间,该模型在实际问题中要求需求和采购价格均随着时间的变化而变化,通过算法计算得到了满足三种物资同时段需求的最佳采购次数,最后得出了所要建立满足需求的最小仓库容量．     

基于MSPC的物资采购风险控制研究

本文首先对大量物资采购危机案例进行归纳分析,然后对采购风险诱因进行分类总结。物资采购风险被划分为三类:企业物资采购市场风险、企业物资缺货与备货风险和供应链管理的物资采购风险。针对企业物资采购风险的整体性,本文提出了基于多变量统计过程控制(MSPC)的物资采购风险综合分析模型,该模型可从全局角度控制企业物资采购风险。最后结合一家典型铝业公司监测数据,论证多变量统计过程控制模型在控制企业物资采购风险方面的有效性。     

二次型之比服从F—分布的充分必要条件

考察F－分布的密度和矩，本文给出了正态随机向量二次型之比服从F－分布的充分必要条件，进而给出了椭球等高随机向量二次型之比服从F分布的充分必要条件．作为应用，我们减弱了传统F－检验中对两简单子样独立性的要求．     

大型水电工程物资调运建模及算法

根据小湾水电工程物资供应管理的实际情况,提出了物资调运的三级节点概念模型,论述了物资采购与调运的数学模型,并给出了具体算法。模型已应用于该工程物资调运决策支持系统中,运行实践表明,该模型能够辅助调度人员制定合理的物资采购与调运方案。     

一类过程需求存贮系统的策略研究及其费用弹性分析

本文首先讨论了需求到达为复合泊松随机过程的库存管理问题,给出了在单位时间内期望总成本费用最小的条件下的确定性的最优订货策略(Q,T).然后分析了在订购量和订购周期为随机变量,其联合分布已知的条件下,基于随机局部弹性理论,分析了总费用关于订购量和订购周期的局部弹性的联合分布,为订购策略的制定提供了合理的依据.     

零件参数设计的动态规划模型

对于本零件参数设计问题,我们建立一个动态规划模型,分阶段以不同的目标搜索求优。在每阶段中,必须以继承和保持前面已获得的目标做为约束条件.在实施动态规划前,根据题设经验公式,先把零件参数根据敏感性进行分类,对零件参数的取值空间作裁剪,把求优空间充分缩小。 假设各零件参数独立正态分布,对求优空间中的每组候选值,随机模拟出性能参数y的概率密度函数,从而确定它是否满足阶段目标和最终目标。 编制程序实现算法后,我们得到了四百多组满意的设计方案,并给出一组推荐方案,其总费用为421元/台,求得原设计方案的总费用为3202元/台,费用降低为2781元。 当零件参数的分布国数未知时,我们利用矩的方法重建产品性能参数y的分布函数,从而可以利用我们的动态规划的模型进行参数设计,我们模型进行总结,给出了零件设计的一般方法,最后,我们对模型和算法进行了进一步的讨论,并给厂家提出了一些实用的建议。     

非线性Poisson-Gamma回归模型中存在偏大离差时离差参数的齐性检验

Poisson回归模型广泛地应用于分析计数型数据，但该模型往往存在偏大离差(overdispersion)问题．刻画Poisson回归模型的偏大离差性的两种方法是拟似然方法和随机效应法(Lee＆Nelder，2000)，已有许多作者利用随机效应法研究了Poisson模型的偏大离差的检验问题．但他们均假定随机效应是独立同分布的，本文对他们的假设进行检验．我们分别在组内效应一致和组内效应不一致的情形下，研究了存在偏大离差的Poisson-Gamma非线性随机效应模型中，随机效应方差(称为离差参数)的齐性检验问题，得到了离差参数齐性的score检验统计量．最后给出两个数值例子说明本文方法的应用．     

马氏调节风险模型下的有限时间破产问题

本文主要研究马氏调节模型中有限时间内的破产变量的分布,给出了有限时间内索赔次数的分布律、总索赔金额的分布函数,且采用了离散近似的方法,显示近似方法的结果与精确的概率密度函数非常接近.此外,使用分解概率密度函数的方法,求出破产时间和破产时赤字的联合分布的具体表达式.     

Management Adopts Operational Research: Session Report

Quantitative methods are derived to assist buyers purchasing commodities in fluctuating price markets. Demand is known whilst price is a stochastic variable which may contain trends or seasonal fluctuations. The essential feature of the problem is that the buyer has many opportunities to make a purchase.Mathematical models are formulated to describe particular commodity buying problems. The optimal purchasing policy is derived by using dynamic programming. It consists of a set of discrete price breaks at each buying opportunity together with the associated stock levels the buyer should aim to achieve at each price break with his purchase at this opportunity. The price breaks are dependent on the probability density functions of future prices and the number of future buying opportunities. Recurrence relations are derived to calculate these price breaks. The case of restrictions on the purchase quantity at each price offer, either because of supply limitations or by the buyer as a policy decision, and price discounts are also considered.A case study illustrating the techniques is given and the methods are extended to purchasing for a blending problem with substitutable commodities.     

The stochastic EOQ model with random sales price

The article deals with a stochastic economic order quantity (EOQ) model over a finite time horizon where uniform demand over the replenishment period is price dependent. The selling price is assumed to be a random variable that follows a probability density function. As demand is probabilistic, stock out situation may occur. Based on the partial backlogging and lost sale cases during stock out period, the author develops the criterion for the optimal solution for the replenishment size such that the integrated expected profit is maximized. Moreover, the article suggests a new function regarding price dependent demand. Finally, numerical examples and its sensitivity analysis of key parameters are given to illustrate the proposed model.     

Optimizing a Production System with a Fixed Delivery Schedule

This note considers a model in which a manufacturing company purchases a raw material, manufactures a product (at a finite rate) and ships a fixed quantity of the product to a single customer at fixed and regular intervals of time, as specified by the customer. In general there are several shipments made during each production run. The objective is to determine a purchasing and production schedule which minimises the total cost of purchasing, manufacturing and stockholding. It extends previously published work by considering the possibility that a single raw material purchase provides stock for several production runs or that several raw material purchases provide stock for a single production run.     

Inventory Control with a Randomly Available Discount Purchase Price

A mathematical model is developed for a basic single-commodity storage system in which the stock controller is faced with a randomly fluctuating purchase price. High- and low-price periods are defined and a purchasing policy is specified which depends upon both the number of units in storage and the price period in which the system is operating. For the case of random demand the limiting stochastic behaviour of the system is obtained and the cost of operating the system is derived.     

时变需求等量进货情形下集成供应链生产订货策略研究

构建了一个包含原料采购、生产和销售过程的集成供应链模型,研究了由原料、生产商和销售商产品构成的三层库存系统的生产订货问题。在有限的规划期内,销售商每次进货量相同,生产商按照EOQ模型采购原材料。以最小化供应链系统的总运营成本为目标,构建一个混合整数非线性规划模型,寻找销售商最优订货方案和生产商最佳生产策略。首先利用网络优化方法求解生产商的最优生产计划,其次利用定界穷举法寻求销售商最优的订货周期,给出了具体的计算方法和Matlab程序。通过算例分析验证了算法的有效性,并研究了各参数对最小费用及最优解的影响。     

Optimal lot size model for deteriorating items with demand rate dependent on displayed stock level (DSL) and partial backordering

In this paper, we consider the problem of determining the lot size of a single deteriorating item with the demand rate dependent on displayed stock level, selling price of an item and frequency of advertisement in the popular electronic and print media, also through the sales representatives. Shortages, if any, are allowed and partially backlogged with a variable rate which depends on the duration of waiting time upto the arrival of next lot. Here, the transportation cost for replenishing the goods is considered explicitly and the storage capacity of the showroom/shop is assumed to be limited (finite). According to the relative size of the stock level dependency demand parameters and the storage capacity of the showroom/shop, different scenarios with sub scenarios have been mentioned and solved with the help of GRG (generalised reduced gradient) method and the computational procedure. The convexity analysis is done by showing the average profit function in each case as pseudo concave. To illustrate the results and its significant features, a numerical example is given. Finally, to study the effect of changes of demand parameters, deterioration, backlogging parameters and mark-up rate on the maximum initial stock level, shortage level, frequency of advertisement per cycle along with the maximum average profit are presented numerically.     

随机需求条件下的延迟发运策略模型及性质

本针对随机需求条件下物流配送中心的库存和运输联合决策问题，在基本库存和自身运输能力不足的情况下，提出对剩余客户订货需求采取部分延迟到下一期与部分利用第三方物流立即发运两相结合的策略，并在具有一般惩罚(损失)费延迟发运量限制的条件下，建立运输和库存相关总成本数学期望最小的优化模型，论证了该模型的主要性质，在此基础上很容易构造求解该类问题的优化方法。