供应提前期和需求不确定下库存系统的随机比较

本文研究供应提前期和需求不确定下包含最小化成本和最大化利润的一致化报童问题中随机比较实现的充分条件,并通过随机比较定量刻画提前期和需求不确定性对库存系统决策和利润的影响。首先引入报童收益函数,给出其优化前后满足随机占优及拉普拉斯变换序的充分条件。进一步,在周期需求服从指数分布的情形下,定量刻画固定提前期与提前期服从几何分布两种情况的随机单调性。最后,将上述结论应用到报童模型中,得到提前期需求对一致化报童问题的随机单调性。     

基于随机提前期的二级库存系统的优化方法

针对需求和提前期均是随机的情况下,考察了一个简单的二级库存系统,即单个供应商、单个零售商的优化问题,两者均采用s,Q策略进行库存管理,他们的订货数量Qr,Qs都是已知常数,以每计划周期内系统运行期望总费用最小建立了目标函数,寻求系统的决策变量sr,ss,最后给出了求解算法与数值算例.     

中国股市量价关系分析中的后验分布构造与模拟

研究中国股票市场中的两个重要指标:股票价格与交易量,随机波动模型具有长期波动性预测能力,只是由于参数估计的困难而没有受到重视.随着马尔可夫链蒙特卡罗(MCMC)方法和计算机计算能力的提高,这种困难是可以克服的.采用基于马尔可夫链蒙特卡罗(MCMC)模拟技术的贝叶斯估计方法,在基于引入预期交易量和非预期交易量的随机波动模型下,对模型参数进行后验分布的构造,并以2005年1月-2012年5月的上证综合指数的每日收盘指数及相应的日成交量序列为样本,通过实证仿真得到参数结果值.结果表明,非预期交易量对股市价格的影响要大于预期交易量.     

随机弹性需求下供应链销售价格与提前期联合决策及协调机制

研究了市场需求随机且对销售价格及提前期敏感的条件下,供应链如何制定最优的销售价格、提前期以及库存因子使得利润最大化。首先,分析了集中决策与分散决策供应链的最优决策,发现集中决策与分散决策模式下的提前期与库存因子是相同的,但分散决策下的销售价格更高、期望利润更低,且分散决策与集中决策供应链的利润之比随着需求对价格的敏感程度的增大而增大。然后建立了收入共享与成本分担的协调机制,并分析了其最优决策。研究发现,协调决策机制可以有效地压缩提前期,并能同时使供应链达到帕累托改进,但不能达到完美协调,而且还发现协调决策下制定的最优销售价格比分散决策要低。最后通过数值计算对三种供应链决策模式下的绩效进行了比较分析,结果表明供应链利润随着需求方差增大而减小,提前期压缩程度随着材料成本承担比例增大而增大。上述结论可以为企业制定销售价格与提前期决策以及企业间的协调提供有益的指导。     

基于变分算法的贝叶斯分层收缩模型及其应用

贝叶斯统计推断通常会遇到后验分布中出现高维积分这一公认的计算难题。一种常用的解决方法是使用MCMC算法。然而,MCMC算法在处理高维大数据或复杂模型时计算效率很低,并且难以判断算法收敛性。针对自适应贝叶斯收缩模型、贝叶斯LASSO模型和扩展的贝叶斯LASSO模型,本文提出了一种更高效的变分贝叶斯(VB)算法来进行参数估计和变量选择。该算法源于理论物理中的平均场理论。它将复杂积分问题转化为最优化问题,使用假定分布族中最接近目标后验分布的分布来近似求解,并且易于判断算法收敛情况。数值模拟结果显示,VB算法不仅计算速度明显优于MCMC算法,而且其模型拟合和变量选择效果也与MCMC算法相当,可以作为MCMC算法的一种替代方法。最后,本文运用VB算法分析了俄罗斯房产售价的重要影响因素。     

求解硬时间窗约束下随机需求库存-路径问题的优化算法

随机需求库存-路径问题(Stochastic Demand Inventory Routing Problem, SDIRP)即考虑随机需求环境下供应链中库存与配送的协调优化问题,是实施供应商管理库存策略过程中的关键所在,也是典型的NP难题之一。文章以具有硬时间窗约束的随机需求库存-路径问题(Stochastic Demand Inventory Routing Problem with Hard Time Windows, SDIRPHTW)为研究对象,将SDIRPHTW分解为直接配送的随机库存-路径问题和具有硬时间窗约束的路径优化问题两个子问题,并以最小化系统运行成本和用车数量为目标,设计了一个基于(s,S)库存策略和修正C-W节约法的启发式算法。最后,通过相应的数值算例验证了算法的有效性。     

模糊环境下可控提前期供应链库存优化的Stackelberg模型研究

为了有效地缩短提前期与降低库存成本,研究了模糊环境下可控提前期的供应链库存优化问题.利用三角形模糊数描述需求的不确定性,建立了一类模糊需求条件下可控提前期供应链库存优化的Stackelberg模型.利用三角形模糊数描述成本系数的不确定性,建立了模糊成本系数条件下可控提前期供应链库存优化的Stackelberg模型,并提出利用均值面积度量法来解模糊化.通过数值分析来验证两类模型的优化效果.     

动态联合库存的决策模型及算法

考虑生产商、销售商联合库存的动态优化问题,建立的随机需求下生产-销售运作系统的排队模型,得到了系统的稳态概率分布和队长分布.以成本最小化为目标,模型算法找到了最优的运作策略和机器使用数量.数值模拟的结果表明,依赖于指定机器数量的动态调整策略明显优于静态系统.     

库存理论(四)

4.2基于稳态分析的随机库存模型 前面讨论的多阶段随机库存模型中利用了动态规划的最优化原理,把问题的求解化为一个多阶段决策过程.一般来讲,其求解是很困难的.本段从另外的角度来考虑.假定讨论的是无限时段,由库存水平(随机过程)的稳态分析,根据所采用的定货策略对系统加上费用结构,然后对稳态下单位时间系统运行的期望总平均费用(或折扣费用)求极小,用这种方法来求出最优策略中的参数. 我们先从最简单的随机模型开始. 4.2.1单个需求连续盘点的随机库存模型 假定α)相邻单个需求之间的时间间隔X1, X2,…独立同分布X,有分布F(x),密度f(x)…     

基于顾客反馈的销售商库存控制策略仿真

销售商的实际服务水平与其目标服务水平存在差异.针对服务水平影响顾客潜在需求和销售商库存水平的复杂系统问题,运用服从特定分布的离散随机数模拟市场中受历史实际服务水平影响的顾客反馈需求,建立以总销售利润最大为目标的销售商库存系统动力学仿真模型模拟顾客-销售商间的互动反馈关系,基于STELLA软件动态模拟服务水平控制策略下库存系统中物流和信息流的传递和反馈.最后的实例仿真结果验证了模型和算法的合理有效性,指出了敏感型销售商与固执型销售商在面对不同顾客需求时的绩效差异,这也表明了提出的算法在现代商品销售中的实用性.     

A multi-item mixture inventory model involving random lead time and demand with budget constraint and surprise function

This study deals with a multi-item mixture inventory model in which both demand and lead time are random. A budget constraint is also added to this model. The optimization problem with budget constraint is then transformed into a multi-objective optimization problem with the help of fuzzy chance-constrained programming technique and surprise function. In our studies, we relax the assumption about the demand, lead time and demand during lead time that follows a known distribution and then apply the minimax distribution free procedure to solve the problem. We develop an algorithm procedure to find the optimal order quantity and optimal value of the safety factor. Finally, the model is illustrated by a numerical example.     

Reducing lost-sales rate on the stochastic inventory model with defective goods for the mixtures of distributions

In this paper, we assume that the demands of different customers are not identical in the lead time. Thus, we investigate a continuous review inventory model involving controllable lead time and a random number of defective goods in buyer’s arriving order lot with partial lost sales for the mixtures of distributions of the lead time demand to accommodate more practical features of the real inventory systems. Moreover, we analyze the effects of increasing investment to reduce the lost sales rate when the order quantity, reorder point, lost sales rate and lead time are treated as decision variables. In our studies, we first assume that the lead time demand follows the mixture of normal distributions, and then relax the assumption about the form of the mixture of distribution functions of the lead time demand and apply the minimax distribution free procedure to solve the problem. By analyzing the total expected cost function, we develop an algorithm to obtain the optimal ordering policy and the optimal investment strategy for each case. Finally, we provide numerical examples to illustrate the results.     

An inventory system with unit demand and varying ordering levels

An inventory system with unit demand, varying ordering levels and random lead times is considered in this paper. Ordering level is determined by the number of demands during last lead time. The ordering quantity will be such as to bring back the inventory level to S at the ordering epoch. No backlog is permitted. The time dependent probability distribution of the inventory level is obtained. Correlation between the number of demands during a lead time and the length of the next inventory dry period is obtained and it is illustrated by an example.     

Managing a dual-channel supply chain under price and delivery-time dependent stochastic demand

Several leading manufacturers recently combined the traditional retail channel with a direct online channel to reach a wider range of customers. We examine such a dual-channel supply chain under price and delivery-time dependent stochastic customer demand. We consider five decision variables, the price and order quantity for both the retail and the online channels and the delivery time for the online channel. Uncertainty frequently arises in both retail and online channels and so additional inventory management is required to control shortage or overstock and that has an effect on the optimal order quantity, price, and lead time. We developed mathematical models with the profit maximization motive. We analyze both centralized and decentralized systems for unknown distribution function of the random variables through a distribution-free approach and also for known distribution function. We examine the effect of delivery lead time and customers’ channel preference on the optimal operation. For supply chain coordination a hybrid all-unit quantity discount along a franchise fee contract is used. Moreover, we use the generalized asymmetric Nash bargaining for surplus profit distribution. A numerical example illustrates the findings of the model and the managerial insights are summarized for centralized, decentralized, and coordinated scenarios.     

An integrated inventory model with controllable lead time and distribution‐free demand

The impact of lead time reduction on an integrated periodic review inventory system comprising a single vendor and multiple buyers with a step crashing cost function and service‐level constraints is studied. The probability distribution of demand during the protection period for each buyer is unknown, but the mean and the variance are given. Each production lot of the vendor can be delivered in a number of shipments to all buyers. A minimax distribution‐free procedure with Lagrange multipliers is applied to determining the lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle so that the expected total system cost is minimized. Numerical experiments along with sensitivity analysis were performed to illustrate the effects of parameters on the decision and the total system cost. Copyright © 2009 John Wiley & Sons, Ltd.     

基于可控提前期和可变押后订单比例的库存问题研究

针对可控提前期领域现有研究中存在的不足,提出了同时考虑可控提前期和缺货对押后订单比例影响的连续盘点库存管理问题。在市场需求服从正态分布条件下建立年总成本表达式,并同时决策订货量、订货点和提前期使年总成本最小。实例计算表明我们的库存管理方法可以减少总成本,提高顾客服务水平和使库存管理更加平稳。     

Inventory System Subject to Disaster with General Interarrival Times

Abstract

We discuss a single commodity continuous review (s, S) inventory system in which commodities get damaged due to external disaster. Shortages are not permitted and lead time is assumed to be zero. The interarrival times of demands constitute a family of i.i.d. random variables with a common arbitrary distribution. The quantity demanded at a demand epoch is arbitrarily distributed which depends only on the time elapsed since the last demand epoch. Transient and steady state probabilities of the inventory levels are derived by identifying suitable semi-regenerative process. In the case when the demand is for unit item and the disaster affects only an exhibiting item, the steady state probability distribution is obtained as uniform. An optimization problem is discussed and numerical examples are provided.     

Optimizing delivery lead time/inventory placement in a two-stage production/distribution system

In this paper we study a system composed of a supplier and buyer(s). We assume that the buyer faces random demand with a known distribution function. The supplier faces a known production lead time. The main objective of this study is to determine the optimal delivery lead time and the resulting location of the system inventory. In a system with a single-supplier and a single-buyer it is shown that system inventory should not be split between a buyer and supplier. Based on system parameters of shortage and holding costs, production lead times, and standard deviations of demand distributions, conditions indicating when the supplier or buyer(s) should keep the system inventory are derived. The impact of changes to these parameters on the location of system inventory is examined. For the case with multiple buyers, it is found that the supplier holds inventory for the buyers with the smallest standard deviations, while the buyers with the largest standard deviations hold their own inventory.     

需求中断下具有提前期的双渠道供应链的风险规避决策

讨论了由一个制造商和一个零售商所组成的双渠道供应链在需求中断下具有提前期的双渠道供应链的风险规避问题.给出了在需求中断前后的最优价格、最优提前期和最优生产决策.研究表明决策变化量是需求中断量的线性函数,在集中式下最优的决策和销售量与供应链的市场份额和需求中断有关,模型的最优生产体现了一定的稳健性.对于提前期来说,当市场份额较大时,最优提前期关于风险规避系数呈正比例,当市场份额较小时,最优提前期关于风险规避系数呈反比例.