基于时间窗约束的军事虚拟仓库库存控制模型研究

考虑了由一个战役仓库和一个战术仓库组成的军事虚拟仓库库存系统,假设战术仓库的需求是随机的且送货时间需要满足时间窗的约束,而战役仓库的库存量需要满足战术仓库多个周期的需求.基于这些假设,以系统成本最小为目标建立了该军事虚拟仓库系统的库存成本模型,并给出了有效的算法求解战术仓库的最优订货数量以及战役仓库的库存量和送货次数,实现了系统的最小运行成本.     

库存管理中的安全技术

持有合适的安全库存是企业在成本节约和满足客户需求间的权衡,因此确定合适的安全库存量对于企业甚至整个供应链来说都非常重要。文章研究了确定安全库存时需要注意的三个事项:一是需要区分周期服务水平CSL和产品补给率fr;二是区分季节性库存与安全库存;三是需要重视少数异常值的发现和对安全库存的影响。     

成本与需求联动下的超市库存多期优化模型

优化库存是超市成功运作的关键,在成本与需求联动条件下,以利润最大化为目标函数,利用管理科学的方法,调整多期商品的进货量,实现库存成本控制最优。最后以万德隆南师二店为例,论证了在进货成本与需求联动的条件下,可以实现超市库存成本的降低,增加超市利润。     

成本与需求联动下的超市库存多期优化模型

优化库存是超市成功运作的关键,在成本与需求联动条件下,以利润最大化为目标函数,利用管理科学的方法,调整多期商品的进货量,实现库存成本控制最优。最后以万德隆南师二店为例,论证了在进货成本与需求联动的条件下,可以实现超市库存成本的降低,增加超市利润。     

库存成本约束下的供应链协调研究

在随机需求下,库存协调研究的核心是达到供应链整体成本的最小化,文中在考虑库存持有成本和缺货惩罚成本的情况下构建了基于供应商和零售商的基准库存水平的成本函数,在此基础上分别比较了集中决策和分散博弈下的纳什均衡最优情况。然后给出一个线性转移支付契约来达到整个供应链的协调,实现了库存成本在销售层面的任意分配。     

基于预防检查的安全库存生产策略

基于会随机发生失控的不可靠生产系统,研究了允许缺货情况下,考虑预防检查结果对安全库存的影响.根据一个完整周期的生产过程,分析了生产过程中的费用组成,建立了考虑预防检查和安全库存的EMQ模型,以求得使单位时间内总费用最小的最优安全库存量、正常生产时间.最后,通过数学案例,总结了模型中参数的变化对决策变量和目标函数的影响.研究结果表明:随着劣化率的增大,单位时间内总费用增加,最优安全库存量增加,正常生产时间减少.     

浅析订单式生产对物流成本的影响——以一汽大众为例

订单式生产是以消费需求为中心来安排生产的,这一生产方式能够消除浪费．大幅度降低生产系统中的原材料、在制品、产成品的库存量和销售中的逆向物流量,进而使库存最优．物流总成本最低。以一汽大众的订单式生产为例,首先简要概述了订单式生产的含义和精髓：其次对一汽大众订单式生产的实践过程及其在降低物流成本方面取得的成效进行了较为详细的剖析：最后通过对一汽大众实施订单式生产在降低物流成本方面所取得的成效的分析．阐述了订单式生产在降低物流成本方面所起的作用。通过分析,作者认为订单式生产不但能够降低企业的库存成本、生产物流成本和退货成本．还能为企业创造了更多的利润空间,因此这一生产方式已逐渐成为我国企业把握市场脉搏,提升竞争力,实现可持续发展的主流生产方式。     

库存成本控制的精准性考核

<正>企业的运营离不开良好的库存管理。库存量不足,会造成企业不能及时生产和满足客户的需求,影响销售,甚至会造成客户转向从竞争对手购买,导致失去客户。然而,库存量过大,会占用大量的流动资金,造成资金呆滞,影响资金的时间价值和机会收益。尤其是当产品更新换代快时,库存量过大可能会造成公司有大量过时产品,给公司带来严重的资金损失,有的时候会导致公司倒闭。随着市场的竞争加剧,库存控制的重要性越来越突出。     

模糊库存容量约束的多产品库存策略研究

基于模糊数的可信性理论.引入利润率、需求率、库存成本率.根据它们对库存总成本的影响赋予不同的权重得到库存评价指标.据此对产品库存规模进行分类。假定多产品的库存容量为LR型模糊数.根据库存评价指标定义了与单位存储空间相关的额外库存成本.从而确定了最优订货策略。最后通过算例探讨了此模型的有效性和稳定性。     

融合节点群遍历访问仿真算法在智慧云物流库存中的应用

关注库存问题可以有效帮助企业控制成本,提高竞争力,可以避免由于缺货或积压货物造成企业无法正常经营。传统库存管理模式注重对库存分类管理,方便确定订货时间和数量。然而,现实中客户需求会随时发生变化,要求现代智慧云物流要根据一些随机变量来确定库存量、订货时间以及订货批量,因此需要将节点群遍历访问仿真算法融入智慧云物流库存控制与管理中。     

一类变库存费且存货影响销售率的EOQ模型

从实际背景出发,在变库存费和存货影响销售率条件下,分别就最小化平均费用和最大化平均利润讨论了具有Ramp型需求的变质性物品的EOQ模型,给出了无短缺量拖后和部分拖后条件下最佳订购批量的求解方案,数值例子对两个不同目标下的最佳订购批量及各项相关费用进行了比较,揭示了变库存费和存货影响销售率对最优订货策略的影响。     

A Note on the Newsboy Model with a Cutoff Transaction Size and Gauss Holding and Penalty Cost Functions

In recent papers, the inventory models were presented in which customers with an order larger than a prespecified cutoff transaction size are satisfied in an alternative way, against additional cost. They assumed the holding and penalty cost functions are linear functions. In this paper, the Gauss function can be applied such as the cost for mailing letters or packages in the post office. Therefore, we address a variant of the holding and penalty cost functions by considering the Gauss holding and penalty cost functions to fit in with the most practical situations. In addition, we also assume that customers with an order larger than a prespecified cutoff transaction size are still assumed to be satisfied in an alternative way. Moreover, when the maximum demand is large, much more time may be required to determine the optimal solution. Thus, we adopt and modify the algorithm of the Golden Section Search Technique to determine the optimal order-up-to level S and the cutoff transaction size q systematically and provide illustrative numerical example.     

A Note on EOQ Model for Items with Mixtures of Exponential Distribution Deterioration,Shortages and Time-varying Demand

An inventory model is considered in which inventory is depleted not only by demand, but also by deterioration. In this paper, we derive the EOQ model for inventory of items that deteriorates at a mixtures of exponential distributed rate, assuming the demand rate with a continuous function of time. Moreover, the proposed model cannot be solved directly in a closed form, thus we used the computer software IMSL MATH/LIBRARY (1989) to find the optimal reorder time Further, we also find that the optimal procedure is independent of the form of the demand rate. Finally, we also assume that the holding cost is a continuous, nonnegative and non-decreasing function of time in order to generalize EOQ model. Moreover, four numerical examples and sensitivity analyses are provided to assess the solution procedure.     

基于延期支付和价格折扣策略的易变质物品库存模型

在资金具有时值、供应商给零售商提供定期信用支付和价格折扣的支付策略条件下,讨论了需求跟价格相关、变质率为常数的易变质物品库存问题,建立了优化补货周期和销售策略的库存模型,目的是极大化平均总利润。分析了模型最优解的存在性和唯一性,并给出数值实验。     

Learning curves and lot sizing for independent and dependent demand

This paper explores the effect of learning curve cost behavior, as opposed to linear, on lot sizing. The first portion of the paper develops optimizing models for the independent demand situation. The second portion examines lot sizing for dependent demand, developing a lot sizing rule similar to Part Period Balancing.After examining the shortcomings of previous attempts at the independent demand lot sizing problem, two models are derived. Excluding material costs (for an assembly operation, the cost of all components), the optimal lot size is seen to vary linearly with demand and inversely with the carrying cost rate.When material costs are included a smaller optimal lot size is derived. The difference between the two, expressed as a fraction of the smaller lot size, equals the material/labor ratio of the last unit produced in the smaller lot size. For dependent demand, the incremental model developed by Freeland and Colley as an improvement on Part Period Balancing is used as a beginning concept. An analogous model, called Assembly Period Balancing, is developed for learning curve cost behavior. The decision rule for combining lots is expressed as a comparison of the material/labor ratio of the lot considered for combining with another expression involving the carrying cost rate, relative lot size and the learning curve exponent.Finally, cost data from an electronics manufacturer are used to examine the cost penalties of failing to recognize learning curve cost behavior. It is shown that optimal lot sizes for learning curve costs can be much larger than those obtained assuming linear costs. It is also shown that much larger lots can be economically combined in the dependent demand case when costs follow a learning curve.     

The optimality of (s,S) inventory policies in the infinite period model*

Summary The infinite period stationary inventory model is considered. There is a constant lead time, a nonnegative set-up cost, a linear purchase cost, a holding and shortage cost function, a fixed discount factor β, 0 < β < 1, and total backlogging of unfilled demand. Both the total discounted cost (β < 1) and the average cost (β= 1) criteria are considered. Under the assumption that the negatives of the one period holding and shortage costs are unimodal, a unified proof of the existence of an optimal (s.S) policy is given. As a by-product of the proof upper and lower bounds on the optimal values of s and S are found. New results simplify the algorithm of Veinott and Wagner for finding an optimal (s, S) policy for the case β< 1. Further it is shown that the conditions imposed on the one period holding and shortage costs can be weakened slightly.     

供应链二级分销网络的一种成本优化模型

提出了一种二级分销网络的成本优化的模型。模型研究了单个工厂的制造商和多个分销商组成的二级分销网络成本优化问题,把保证不发生缺货情况作为约束条件。综合考虑了订货成本、库存持有成本、运输成本和建立分销点和分销中心的成本,并给出了基于遗传算法的模型求解步骤。     

Optimal maintenance center inventories for fault-tolerant repairable systems

In many military and commercial contexts, complex equipment which is expected to perform very reliably is often designed to be fault-tolerant, that is, able to function although some of the parts have failed. A popular fault-tolerant design is the m-out-of-n system, where there are n identical parts, at least m of which must be functional for machine operation. Complex equipment of this type often undergoes scheduled maintenance overhauls at regular intervals during which all failed components are replaced. Failure to have replacements on hand for failed parts requires emergency measures at premium cost. When repairable parts are highly reliable and expensive, both holding and shortage costs are high. A reasonable objective is to choose initial spares inventory to minimize the sum of holding costs and expected shortage costs.We first develop a model to determine the optimal repairable parts inventory for a maintenance center servicing machines containing a single m-out-of-n system. The model is then extended to handle a related problem, finding optimal maintenance center inventories for machines containing several m-out-of-n systems of different parts, minimizing total expected costs subject to a constraint on total inventory investment.We assume that there is a fleet of machines, which experience identical workloads. There is a cycle time of T days between overhauls for an individual machine. A machine arrives at the maintenance center for overhaul each day. At the overhaul, all failed parts are removed and sent to a repair shop, from which they eventually return to the maintenance center to be used again as spares. The total number of spares undergoing repair and on hand is a constant. There are no backorders; if the number on-hand spares is insufficient to meet demand at an overhaul, a shortage penalty is assessed which depends on the number and type of spares required.While computing holding costs is straightforward, computing expected shortage costs is more complex. Expected shortage costs are dependent upon several factors, including component failure rates, the values of m and n, part repair rates, and the initial number of spares on hand. We assume that the system of interest is well specified, so that the parameters of the model are known except for the number of initial spares of each type, which are the decision variables. We model the on-hand inventory of each type of part as a Markov chain with the number of spares on hand at the end of each day as the states, under the assumptions that failure rates are constant and repair times follow independent exponential distributions. We then calculate the steady-state probabilities of stockout of various numbers of spares, as a function of the initial spares inventory. The expected shortage costs for a given type of spare may then be calculated by finding the product of the penalty cost for lacking p spares and the probability of lacking p spares and summing over all possible p values.Solutions to the problem of finding optimal initial inventory level for a machine containing a single m-out-of-n system may be found easily by enumeration. Solutions to the constrained problem where the machine contains several independent m-out-of-n systems, may be found by dynamic programming. Sensitivity analysis of costs to changes in the inventory investment constraint is clear, and computational effort is reasonable. A simple example is included to illustrate the solution method for both problems.     

随机需求和提前时间存储系统的建模与仿真

讨论了需求量、需求发生的间隔以及提前时间都为随机变量的一般随机存储系统。以平均库存总费用和缺货率为系统性能指标建立仿真模型，将二者加权平均得到策略的综合系数。在各种费用参数给定后，利用计算机仿真技术来选定最优存储策略。