可替代产品库存模型的研究

市场上,很多产品之间可相互替代,商家为了获得的更多的利润,经常会用一种产品替代另一种产品.不仅如此.某种产品缺货时,也可以重新进货以满足顾客的需求.我们从销售商的角度,讨论这两个因素对库存策略的影响,建立了这类问题有两个产品的单周期的利润最大化模型,证明了目标函数是凹的和子模的,从而问题的解是存在的,给出了最优订货量(原始库存)的必要条件,讨论了各参数对库存的影响.通过比较,证明了商家采取替代策略和允许再订货可以提高利润并且可减少库存总量.     

可替代产品库存模型的研究

市场上，很多产品之间可相互替代，某种产品缺货时，可用另一种产品替代，也可以重新进货以满足顾客的需求。我们的目的是：从销售商的角度，讨论这两个因素对库存策略的影响。我们建立了这类问题有两个产品的单调期的利润最大化模型。证明了问题的解的存在性，给出了目标函数是凹函数和子模函数的充分条件，讨论了求解的方法和各参数对库存的影响。通过对几种特殊情况的讨论和比较，证明了替代和再订货可以提高利润并且可减少库存总量。     

具有库存损耗且允许缺货的EOQ模型

提出了一种库存损耗量随时间和库存量变化,且允许缺货的EOQ模型,证明了该模型的平均总费用函数在给定条件下为凸函数,并讨论了模型的最优策略及近似解.     

单向可替代产品价格和库存的联合决策

考虑单周期问题中零售商同时销售两种可单向替代的产品,以期望利润为目标函数建立数学模型.将库存和替代价格共同作为零售商决策变量,证明其目标函数是凹函数,并得到求模型最优解的充要条件及解存在的范围.最后假设产品需求为正态分布,通过数值实验对模型的最优解进行分析,结果表明:实行最优替代价格策略可以有效提高零售商期望利润;允许替代销售不一定提高市场服务水平;被替代产品的销售价格和残值对零售商的最优替代价格决策没有显著影响.     

双向替代产品库存模型研究

运用最优控制理论和数理经济学方法研究了供应链管理时代下广泛存在的双向替代产品的最优库存问题,建立了利润最大化前提下的双向替代品的库存模型,证明了该问题解的存在性,并给出了求解最优订货量的方法步骤,可为实施有效的库存管理、降低企业的物流成本提供借鉴.     

基于贝叶斯信息更新的动态库存与定价研究

考虑价格对需求量的扰动并利用贝叶斯公式对需求分布函数中的未知参数进行不断学习更新,研究缺货部分比例延迟交货情形下的动态库存与动态定价问题,刻画了最优利润函数的性质并证明了"基准库存列表价格"是最优的库存价格水平,并由此得到了最优的补货策略和定价策略。     

供应商管理库存的渠道利润优化分析

本文研究了供应链管理的渠道利润问题。对有确定需求、有初始库存和库存短缺的一种畅销商品,建立了供应商管理库存的渠道利润模型。通过对此模型的进一步分析,证明了在短期激励下供应商管理库存的渠道利润优于一般库存的渠道利润;也证明了在长期激励下,供应商管理库存可以产生比短期激励下更优的渠道利润,也优于一般库存的渠道利润。这一结果对于供应链环境下的库存管理在理论和工程上具有实际意义。     

快速补货模式下的动态定价与库存联合策略

在供应有限的情况下,研究常规补货和快速补货下商品动态定价问题.首先,建立了动态规划模型,理论证明了最优库存策略是基于(s,S)策略下改进的基本库存策略.其次,提出了一种启发式策略求复杂系统的最优策略,启发式算法能够求出最优价格和最优库存水平.最后,数值算例研究表明,库存管理中采用快速补货提高了零售商的利润;初始库存水平越高零售商的利润越高.     

替代产品的动态库存决策与控制

考虑了替代产品的动态库存决策与控制问题,建立了替代产品的多周期动态库存决策与控制模型.得到了目标函数的一些重要性质,给出了系统最优参数的求解算法,利用动态规划方法对系统的库存参数进行了优化求解.     

基于存货质押的库存管理研究

针对基于存货质押的库存管理问题进行分析并构建模型,从还贷和不还贷两个角度,研究模型的最佳订货批量和质押量.模型以利润函数为目标函数,利润函数包括了销售额、缺货损失、剩余品价值、产品成本以及贷款本息和.通过对利润函数进行求解,得出最佳订购批量、存货质押量和最大期望利润,最后根据利润的大小决定是否偿还贷款.     

Single-period Two-product Inventory Model with Reorder and Substitution

In market, excess demands for many products can be met by reorder even during one period, and retailers usually adopt substitution strategy for more benefit. Under the retailer's substitution strategy and permission of reorder, we develop the profits maximization model for the two-substitutable-product inventory problem with stochastic demands and proportional costs and revenues. We show that the objective function is concave and submodular, and therefore the optimal policy exists. We present the optimal conditions for order quantity and provide some properties of the optimal order quantities. Comparing our model with Netessine and Rudi's, we prove that reorder and adoption of the substitution strategy can raise the general profits and adjust down the general stock level.     

Sourcing from suppliers with random yield for price-dependent demand

We study a multi-period inventory planning problem. In each period, the firm under consideration can source from two possibly unreliable suppliers for a price-dependent demand. Our analysis suggests that the optimal procurement policy is neither a simple reorder-point policy nor a complex one without any structure, as previous studies suggest. Instead, we prove the existence of a reorder point for each supplier. No order is placed to that supplier for any inventory level above the reorder point and a positive order is issued to that supplier for almost every inventory level below the reorder point. We characterize conditions under which the optimal policy reveals monotone response to changes in the inventory level. Furthermore, two special cases of our model are examined in detail to demonstrate how our analysis generalizes a number of well-known results in the literature.     

Stock Control Using the Stock Level Frequency Distribution

Stock level frequency distributions are derived for continuous review stock control policies in which the lead time demand is normally distributed. The percentage points of the distributions have been tabulated, and the table can be used to determine the reorder point that will meet a specified customer order quantity from stock with a specified probability. The results can also be used to determine the order up to point for a periodic review policy and the reorder point for a mixed policy.     

Multi-item inventory control with full truckloads: A comparison of aggregate and individual order triggering

In this paper, we consider the stochastic joint replenishment problem in an environment where transportation costs are dominant and full truckloads or full container loads are required. One replenishment policy, taking into account capacity restrictions of the total order volume, is the so-called QS policy, where replenishment orders are placed to raise the individual inventory positions of all items to their order-up-to levels, whenever the aggregate inventory position drops below the reorder level. We first provide a method to compute the policy parameters of a QS policy such that item target service levels can be met, under the assumption that demand can be modeled as a compound renewal process. The approximation formulas are based on renewal theory and are tested in a simulation study which reveals good performance. Second, we compare the QS policy with a simple allocation policy where replenishment orders are triggered by the individual inventory positions of the items. At the moment when an individual inventory position drops below its item reorder level, a replenishment order is triggered and the total vehicle capacity is allocated to all items such that the expected elapsed time before the next replenishment order is maximized. In an extensive simulation study it is illustrated that the QS policy outperforms this allocation policy since it results in lower inventory levels for the same service level. Although both policies lead to similar performance if items are identical, it can differ substantially if the item characteristics vary.     

A heuristic for triggering emergency orders in an inventory system

This paper considers a single-echelon inventory system with a warehouse facing compound Poisson customer demand. Normally the warehouse replenishes from an outside supplier according to a continuous review reorder point policy. However, it is also possible to use emergency orders. Such orders incur additional costs but have a much shorter lead time. We consider standard holding and backorder costs as well as ordering costs. A heuristic decision rule for triggering emergency orders is suggested. The decision rule minimizes the expected costs under the assumption that there is only a single possibility for an emergency replenishment, but the rule is used repeatedly as a heuristic. Given a certain reorder point policy for normal replenishments, our decision rule will always reduce the expected costs. A simulation study illustrates that the suggested technique performs well under different conditions.     

Joint-optimization of inventory policies on a multi-product multi-echelon pharmaceutical system with batching and ordering constraints

This paper presents a methodology to find near-optimal joint inventory control policies for the real case of a one-warehouse, n-retailer distribution system of infusion solutions at a University Medical Center in France. We consider stochastic demand, batching and order-up-to level policies as well as aspects particular to the healthcare setting such as emergency deliveries, required service level rates and a new constraint on the ordering policy that fits best the hospital’s interests instead of abstract ordering costs. The system is modeled as a Markov chain with an objective to minimize the stock-on-hand value for the overall system. We provide the analytical structure of the model to show that the optimal reorder point of the policy at both echelons is easily derived from a simple probability calculation. We also show that the optimal policy at the care units is to set the order-up-to level one unit higher than the reorder point. We further demonstrate that optimizing the care units in isolation is optimal for the joint multi-echelon, n-retailer problem. A heuristic algorithm is presented to find the near-optimal order-up-to level of the policy of each product at the central pharmacy; all other policy parameters are guaranteed optimal via the structure provided by the model. Comparison of our methodology versus that currently in place at the hospital showed a reduction of approximately 45% in the stock-on-hand value while still respecting the service level requirements.     

模糊随机需求的连续盘点存储策略研究

考虑到需求的模糊随机性,建立模糊随机需求情况下连续盘点存储策略的模糊随机成本模型。利用模糊随机变量的期望值理论,推导出了其成本期望值模型的解析表达式,进而给出了最优再订货点所属区间的判别条件以及最优再订货点和经济订货量的计算式;基于此,设计了一模糊随机需求的连续盘点最优存储策略算法。最后结合数值算例,分析了模糊随机需求概率分布及缺货成本对最优存储策略的影响。     

Reorder quantities for (<Emphasis Type="Italic">Q,R</Emphasis>) inventory models

The reorder level R and the reorder quantity Q are the parameters to be decided in a continuous review inventory policy. Their optimal values can be approached through iterative methods, but these are tedious and inconvenient for control routines. A frequent practice is to set Q as the economic reorder quantity and compute R accordingly. Yet this practice may introduce a substantial cost penalty. The paper re-arranges conventional theoretical expressions in order to facilitate the use of numerical approximations to help find a quasi-optimal solution. This approach is then applied to Gamma distributed demands showing that computations are straightforward.