一个最优库存决策模型

在已有的库存决策模型中,其决策标准是库存总成本最小,假设条件是订购成本C_1、单位存货在单位时间内的储存成本C_2、缺货成本C_3以及各时期的价格P为常数。现实中,这些条件都难以满足,因此其模型的应用价值不大。本文首先分析C_1、C_2、C_3的属性,再在此基础上建立一个具有一定应用价值的模型,其决策标准是库存系统的总利润最大。     

航材库存规划策略研究

现有的航材库存管理信息利用不充分,导致航材保障针对性不强、库存成本较大。以供应链库存管理理论为依据,在对航材分类的基础上,提出了航材库存规划策略,包括周转库存、安全库存与航材使用监控等方面,最后采用模糊综合评价方法对供应商进行评价。能够有效缓解航材供需矛盾,提高库存资金使用效力。     

基于供应链的企业库存成因及优化控制研究（续）

基于企业全面库存管理思想,对库存成本、库存控制、库存系统优化等管理经验与前人研究成果进行分析,借鉴先进企业的库存管理理念和方法,以大型制造企业为核心研究对象,在集供应商、制造商、经销商为一体的供应链作为研究框架的基础上,运用供应链系统理论作为研究方法,分析了库存管理现状、影响因素及产生原因,从优化生产管理、整合企业内部供应链和跨企业供应链的角度提出库存控制的相应对策,以实现全面的库存优化,提高经营效益。     

基于供应链的企业库存成因及优化控制研究

基于企业全面库存管理思想,对库存成本、库存控制、库存系统优化等管理经验与前人研究成果进行分析,借鉴先进企业的库存管理理念和方法,以大型制造企业为核心研究对象,在集供应商、制造商、经销商为一体的供应链作为研究框架的基础上,运用供应链系统理论作为研究方法,分析了库存管理现状、影响因素及产生原因,从优化生产管理、整合企业内部供应链和跨企业供应链的角度提出库存控制的相应对策,以实现全面的库存优化,提高经营效益。     

装备器材库存结构优化方法研究

器材是装备保障效益实现的物质基础,针对装备器材管理工作的关键环节——器材库存结构优化过程中涉及的相关问题,整理、分析了国内外相关研究现状,重点对节点库存优化与层级库存模式调整方法进行综述,并着眼于系统工程,充分考虑库存结构与器材供应的相互影响,对装备器材库存结构优化方法的下一步的研究重点与趋势进行了展望。     

基于安全库存的战时应急弹药储备库选址建模研究

为了更好适应战时弹药需求的不确定性,必须做好对战时应急保障系统的管理工作,应急弹药储备库的选址问题就是应急保障系统的关键环节．首先依据战时弹药需求特点,从库存策略的角度出发,引入安全库存概念;其次,建立了以建设成本和运输总距离为目标函数的战时应急弹药储备库选址模型;最后,运用Matlab对模型进行了仿真,验证了该模型的有效性．     

基于状态的维修与备件库存决策联合优化研究

针对需进行定期功能检测的设备,研究其基于状态的维修策略与备件库存策略联合优化方法。引入延迟时间理论,分析定期功能检测策略下备件库存的消耗与供应过程;基于设备功能退化和备件库存变化规律,建立以设备维修保障费用为优化目标的数学模型,并采用仿真的方法对设备功能检测周期、备件最大库存水平、备件订购周期等决策变量进行联合优化。通过一个算例对所提出的方法和建立的模型进行应用验证。     

基于遗传算法的虚拟物流联合库存控制研究

针对随机需求条件下的虚拟物流库存控制问题进行了深入研究，提出了一种新的联合库存控制策略——（T，S，s）策略，建立了相应的库存成本模型，并构造遗传算法对模型进行求解。结果分析表明，所提出的（T，S，S）联合库存控制策略是有效的。     

多品种维修器材统一订购策略的库存决策模型

分析了一种多品种维修器材联合订货的库存决策模型,该模型采用连续检查的多品种统一订购库存策略。维修器材库存控制的目的是在确保维修器材服务水平的基础上,降低库存成本。根据这一思想设计了算法,该算法首先假设订货点和订购提前期为零,根据库存成本确定最大库存量,然后考虑订货点和订购提前期不为零的情况,根据维修器材满足率确定各品种维修器材的订货点,从而求得决策参数。最后通过实例证明模型和算法的有效性。     

二级库存-运输系统的联合经济订购模型

结合器材供应的实际,构建了一个国家仓库-地区仓库形成的二级库存-运输系统,以最低费用为目标,建立了该系统的联合经济订购模型,求解了该系统各仓库的最佳订货量和订货次数;运用该模型对3种订货策略（年度1次订货、年度多次订货、零库存订货）进行了算例验证,表明了该模型在优化多级库存运输系统订货参数方面的意义。     

Dynamic pricing and replenishment: Optimality,bounds, and asymptotics

In many applications, managers face the problem of replenishing and selling products during a finite time horizon. We investigate the problem of making dynamic and joint decisions on product replenishment and selling in order to improve profit. We consider a backlog scenario in which penalty cost (resulting from fulfillment delay) and accommodation cost (resulting from shortage at the end of the selling horizon) are incurred. Based on continuous‐time and discrete‐state dynamic programming, we study the optimal joint decisions and characterize their structural properties. We establish an upper bound for the optimal expected profit and develop a fluid policy by resorting to the deterministic version of the problem (ie, the fluid problem). The fluid policy is shown to be asymptotically optimal for the original stochastic problem when the problem size is sufficiently large. The static nature of the fluid policy and its lack of flexibility in matching supply with demand motivate us to develop a “target‐inventory” heuristic, which is shown, numerically, to be a significant improvement over the fluid policy. Scenarios with discrete feasible sets and lost‐sales are also discussed in this article.     

A nonlinear continuous time optimal control model of dynamic pricing and inventory control with no backorders

In this paper, we present a continuous time optimal control model for studying a dynamic pricing and inventory control problem for a make‐to‐stock manufacturing system. We consider a multiproduct capacitated, dynamic setting. We introduce a demand‐based model where the demand is a linear function of the price, the inventory cost is linear, the production cost is an increasing strictly convex function of the production rate, and all coefficients are time‐dependent. A key part of the model is that no backorders are allowed. We introduce and study an algorithm that computes the optimal production and pricing policy as a function of the time on a finite time horizon, and discuss some insights. Our results illustrate the role of capacity and the effects of the dynamic nature of demand in the model. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

An economic lot‐sizing problem with perishable inventory and economies of scale costs: Approximation solutions and worst case analysis

The costs of many economic activities such as production, purchasing, distribution, and inventory exhibit economies of scale under which the average unit cost decreases as the total volume of the activity increases. In this paper, we consider an economic lot‐sizing problem with general economies of scale cost functions. Our model is applicable to both nonperishable and perishable products. For perishable products, the deterioration rate and inventory carrying cost in each period depend on the age of the inventory. Realizing that the problem is NP‐hard, we analyze the effectiveness of easily implementable policies. We show that the cost of the best Consecutive‐Cover‐Ordering (CCO) policy, which can be found in polynomial time, is guaranteed to be no more than (4 + 5)/7 ≈ 1.52 times the optimal cost. In addition, if the ordering cost function does not change from period to period, the cost of the best CCO policy is no more than 1.5 times the optimal cost. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

A partial characterization of the optimal ordering/rationing policy for a periodic review system with two demand classes and backordering

We consider a finite horizon periodic review, single product inventory system with a fixed setup cost and two stochastic demand classes that differ in their backordering costs. In each period, one must decide whether and how much to order, and how much demand of the lower class should be satisfied. We show that the optimal ordering policy can be characterized as a state dependent (s,S) policy, and the rationing structure is partially obtained based on the subconvexity of the cost function. We then propose a simple heuristic rationing policy, which is easy to implement and close to optimal for intensive numerical examples. We further study the case when the first demand class is deterministic and must be satisfied immediately. We show the optimality of the state dependent (s,S) ordering policy, and obtain additional rationing structural properties. Based on these properties, the optimal ordering and rationing policy for any state can be generated by finding the optimal policy of only a finite set of states, and for each state in this set, the optimal policy is obtained simply by choosing a policy from at most two alternatives. An efficient algorithm is then proposed. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Note on “An Optimal Recursive Method for Various Inventory Replenishment Models with Increasing Demand and Shortages” by Teng et al.

In a recent paper, Teng, Chern, and Yang consider four possible inventory replenishment models and determine the optimal replenishment policies for them. They compare these models to identify the best alternative on the basis of minimum total relevant inventory costs. The total cost functions for Model 1 and Model 4 as derived by them are not exact for the comparison. As a result, their conclusion on the least expensive replenishment policy is incorrect. The present article provides the actual total costs for Model 1 and Model 4 to make a correct comparison of the four models. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 602–606, 2000     

Optimal capacity in a coordinated supply chain

We consider a supply chain in which a retailer faces a stochastic demand, incurs backorder and inventory holding costs and uses a periodic review system to place orders from a manufacturer. The manufacturer must fill the entire order. The manufacturer incurs costs of overtime and undertime if the order deviates from the planned production capacity. We determine the optimal capacity for the manufacturer in case there is no coordination with the retailer as well as in case there is full coordination with the retailer. When there is no coordination the optimal capacity for the manufacturer is found by solving a newsvendor problem. When there is coordination, we present a dynamic programming formulation and establish that the optimal ordering policy for the retailer is characterized by two parameters. The optimal coordinated capacity for the manufacturer can then be obtained by solving a nonlinear programming problem. We present an efficient exact algorithm and a heuristic algorithm for computing the manufacturer's capacity. We discuss the impact of coordination on the supply chain cost as well as on the manufacturer's capacity. We also identify the situations in which coordination is most beneficial. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

装备备件管理技术综述

备件管理水平的高低直接影响着装备保障能力的发挥和使用保障费用的维持，备件管理现已成为世界范围内的研究热点。通过对国内外有关备件管理文献的分析，总结了备件管理在备件分类方法、需求预测与确定、库存控制与优化3个方面的研究现状。分析结果表明：备件管理将向多因素综合考虑的备件分类方法，基于备件需求不确定性的预测技术以及基于计算机辅助技术、物流和供应链管理等方向发展。     

Approximation algorithms for general one‐warehouse multi‐retailer systems

Logistical planning problems are complicated in practice because planners have to deal with the challenges of demand planning and supply replenishment, while taking into account the issues of (i) inventory perishability and storage charges, (ii) management of backlog and/or lost sales, and (iii) cost saving opportunities due to economies of scale in order replenishment and transportation. It is therefore not surprising that many logistical planning problems are computationally difficult, and finding a good solution to these problems necessitates the development of many ad hoc algorithmic procedures to address various features of the planning problems. In this article, we identify simple conditions and structural properties associated with these logistical planning problems in which the warehouse is managed as a cross‐docking facility. Despite the nonlinear cost structures in the problems, we show that a solution that is within ε‐optimality can be obtained by solving a related piece‐wise linear concave cost multi‐commodity network flow problem. An immediate consequence of this result is that certain classes of logistical planning problems can be approximated by a factor of (1 + ε) in polynomial time. This significantly improves upon the results found in literature for these classes of problems. We also show that the piece‐wise linear concave cost network flow problem can be approximated to within a logarithmic factor via a large scale linear programming relaxation. We use polymatroidal constraints to capture the piece‐wise concavity feature of the cost functions. This gives rise to a unified and generic LP‐based approach for a large class of complicated logistical planning problems. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

Inventory sharing under decentralized preventive transshipments

We consider preventive transshipments between two stores in a decentralized system with two demand subperiods. Replenishment orders are made before the first subperiod, and the stores may make transshipments to one another between the subperiods. We prove that the transshipment decision has a dominant strategy, called a control‐band conserving transfer policy, under which each store chooses a quantity to transship in or out that will keep its second‐subperiod starting inventory level within a range called a control band. We prove that the optimal replenishment policy is a threshold policy in which the threshold depends on the capacity level at the other store. Finally, we prove that there does not exist a transfer price that coordinates the decentralized supply chain. Our research also explains many of the differences between preventive and emergency transshipments, including differences in the optimal transfer policies and the existence or nonexistence of transfer prices that coordinate the system. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

An optimal critical level policy for inventory systems with two demand classes

Traditional inventory systems treat all demands of a given item equally. This approach is optimal if the penalty costs of all customers are the same, but it is not optimal if the penalty costs are different for different customer classes. Then, demands of customers with high penalty costs must be filled before demands of customers with low penalty costs. A commonly used inventory policy for dealing with demands with different penalty costs is the critical level inventory policy. Under this policy demands with low penalty costs are filled as long as inventory is above a certain critical level. If the inventory reaches the critical level, only demands with high penalty costs are filled and demands with low penalty costs are backordered. In this article, we consider a critical level policy for a periodic review inventory system with two demand classes. Because traditional approaches cannot be used to find the optimal parameters of the policy, we use a multidimensional Markov chain to model the inventory system. We use a sample path approach to prove several properties of this inventory system. Although the cost function is not convex, we can build on these properties to develop an optimization approach that finds the optimal solution. We also present some numerical results. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008