供应链库存协调与优化模型研究

传统的库存管理主要把注意力放在企业内部的库存控制,不注重供应链的协调与合作. 这种局部优化的管理模式导致供应链物流不畅,成本增加,企业及其供应链缺乏竞争力. 供应 链的协调与合作成为改善供应链绩效,增强企业竞争力的重要手段. 在需求和供应都不确定的 情形下,通过模型研究对两阶供应链的库存协调及其价值作了一些有益的探讨. 引入了有效库 存水平的概念,以反映上游缺货对下游库存的影响,构造了定期检查补货模式下的供需双方库 存模型,对安全因子进行整体优化,降低供应链库存成本. 同时,也介绍了安全因子整体优化的 实现机制,并对整体优化的价值作了敏感性分析     

基于战略与需求预测的库存管理研究

本文探讨将库存管理上升到企业战略管理的层次,建立一种更有效的库存管理模型。首先企业基于自身的战略选择及评估,并结合企业历史销售记录进行库存ABC分类,分析各类产品在企业战略评估表（如波士顿矩阵）中所处的位置,进而确定其库存策略。依据各类产品不同的库存策略及需求特性,企业再确定相应的库存管理模型。对于企业至关重要的A类产品及企业战略产品,需要根据其需求特性,建立适当的预测模型,从而能够科学地制定库存计划,兼顾库存在提高客户服务水平及降低库存成本的矛盾,从而优化库存管理。     

LR型模糊需求下连续盘点库存策略研究

本文研究了LR型模糊需求下缺货需补的连续盘点库存优化问题。基于可信性理论,建立了成本最小化的库存模型和两种服务水平下的库存分析模型,给出了其求解方法,并将成本和服务水平两方面进行综合获得最优库存策略。最后的算例分析,数值比较了不同模型下的库存策略。     

随机需求直接发运的运输与库存整合优化研究

分销系统的运输与库存整合优化是供应链管理的重要研究课题.本文分析了随机需求两级分销系统的三种配送策略,并具体给出了基于整车直接发运策略的运输决策与库存控制整合优化数学模型,可得到最优的两级最优库存水平和最优的运输频率.最后对给出的算例,利用MATLAB7的规划求解功能容易获得了问题的最优解.     

提前期、构建成本和短缺量拖后率均可控的EOQ模型

传统库存模型通常将提前期和构建成本视为不可控制。事实上可以通过追加投资缩短提前期和降低构建成本。缺货期间,为减少订单丢失量和补偿顾客的损失,供应商会给予一定的价格折扣。现实库存系统中,容易得到需求的期望值和标准差,但较难得到其分布规律。基于此,考虑短缺量拖后率与价格折扣和缺货期间库存水平相关,提出了一种需求为任意分布且提前期和构建成本均可控的EOQ模型,证明了模型存在唯一最优解,给出了一种寻优算法。数值仿真分析表明,一般情况下,压缩提前期和降低构建成本能降低订购批量和安全库存,降低库存总成本;短缺量拖后系数和缺货概率对库存总成本影响较大,企业应尽量降低缺货概率,尤其在短缺量拖后系数较小时。     

时变需求环境下供应链缺货时点与补货次数优化研究

本文基于博弈模型,研究在时变需求和无替代供应源的环境下供需双方缺货时点和补货次数的纳什均衡问题,并通过算例,具体分析了供需之间的关系,主要结论有:配送商的补货次数越大,零售商库存成本越小;补货次数优化后零售商与配送商的库存成本明显下降。     

模糊需求信息条件下风险规避型分销商的库存决策研究

着重研究模糊需求信息条件下风险规避型分销商库存决策问题,利用模糊理论的基本运算规则、扩展原理及Markowitz提出的均值一方差模型建立两类模糊需求信息条件下风险规避型分销商库存决策模型风险规避型分销商在可接受的库存成本基础上追求库存成本方差最小的模型;风险规避型分销商在可接受的库存成本方差基础上追求库存成本最小的模型.并以数值分析的方式来分析模型内在涵义.     

基于瓶颈负荷的BTO供应链响应时间优化

供应商生产的低效率是BTO供应链实际运作过程中的瓶颈,主要表现为供应链整体响应时间长和在制品库存高.针对该类供应链的瓶颈特点,利用排队模型建立了一种基于瓶颈负荷的BTO供应链响应时间优化策略.然后,通过算例分析了订单数量、等待订单数量和产能利用率,以及系统内的概率分布等参数对在制品库存水平和供应链整体响应时间的影响.最后,得出的结论表明,基于瓶颈负荷的控制对缩短供应链整体响应时间和在制品库存水平的控制均是有效的.     

需求替代情形下反应能力的价值分析

本文通过对竞争报童模型加以拓展以研究需求替代情形下企业运用反应能力产生的价值。文中考虑了两种不同的需求结构:第一种中企业总需求是竞争双方库存量的分段线性函数,第二种中企业总需求的均值是双方库存水平任意形式的函数。根据需求结构的不同,建立了不同的库存竞争模型并提出了相应的均衡库存策略。基于这些均衡结论,进一步探讨了反应能力的价值。分析表明运用反应能力能在降低企业库存水平的同时提高顾客服务水平。此外,在不同的需求结构下,运用反应能力产生的价值均随可用反应能力以及缺货惩罚成本递增,而随单位反应能力的使用成本递减。     

航空公司机上周转品多基地库存优化模型

在民航业日益激烈的市场竞争环境下，航空公司对成本控制的精细化管理显得尤为重要。本文基于航空公司的实际背景，针对为旅客提供的机上周转品，建立了一个多基地库存系统的库存优化模型。该模型以系统的总库存成本最小为目标，在考虑需求、回收、调运、安全库存等因素下，决策一个订货周期内的订货及调运方案。基于最优解的分析，在成本参数满足一定条件下，可以得到系统最优的期初订货量；在此基础上，可以将该模型转化为一个网络流模型，参考最小费用最大流算法，设计了一个多项式求解算法来求解该网络流模型，进而得到各基地之间的最优调运量，并证明该算法的最优性；此外，根据期初订货量可行解的范围，设计了一个求解原库存模型的启发式算法。通过实例分析，验证了该模型与两种算法的有效性。     

A coordination mechanism with fair cost allocation for divergent multi-echelon inventory systems

In this paper we study the coordination of inventory control in divergent multi-echelon inventory systems under periodic review and decentralized control. Under decentralized control the installations decide upon replenishment policies that minimize their individual inventory costs. In general these policies do not coincide with the optimal policies of the system under centralized control. Hence, the total cost under decentralized control is larger than under centralized control. We present a simple coordination mechanism that removes this cost inefficiency. The upstream installations increases its base stock level while the downstream installations compensate their supplier for increased costs and provide it with additional side payments. We show that this mechanism coordinates the system; the global optimal policy of the system is the unique Nash equilibrium of the corresponding strategic game. Furthermore, the mechanism results in a fair allocation of the costs; all installations enjoy cost savings.     

A simulation-based multi-objective optimization framework: A case study on inventory management

We propose a simulation-based solution framework for tackling the multi-objective inventory optimization problem. The goal is to find appropriate settings of reorder point and order quantity to minimize three objective functions simultaneously, which are the expected values of the total inventory cost, the average inventory level, and the frequency of inventory shortage. We develop new algorithms that can exploit statistically valid ranking and selection (R&S) procedures and the desirable mechanics of conventional multi-objective optimization techniques. Two simulation algorithms are proposed to be applied in different scenarios depending on the preference information that is revealed either during or after the actual optimization process. Experimental results are provided to evaluate the efficiency of the developed algorithms and other existing solution frameworks.     

含服务水平约束的可控提前期供应链Staekelberg模型与协调机制研究

为了有效地缩短订货提前期与降低库存成本,首先从Stackelberg主从对策角度建立了含服务水平约束的可控提前期供应链库存优化模型,提出了该模型的求解算法;然后从集中决策角度建立了另一类含服务水平约束的可控提前期供应链库存优化模型,并提出该模型的求解算法。利用数值分析对两类模型的优化效果进行比较,结果表明:集中决策模式下的优化效果明显优于Stackelberg主从对策模式下的优化效果,但在缺乏合理的激励机制情形下,供应链各参与方未必有足够积极性接受集中决策模式。为此,提出一种库存费用分担机制来激励供应链各参与方接受集中决策模式。     

Inventory Positioning/Partitioning for Backorders Optimization for a Class of Multi-Echelon Inventory Problems*

Inventory management has undergone significant philosophical changes in recent decades such as the advent of the zero inventory concept. However, as attractive as the concept of minimal inventories may be, it is often unrealistic in application. Attention to basic features of inventory control systems such as order quantities, base stock levels, and reorder points remain crucial to ensure customer service at minimal cost. A nonlinear optimization model for determining base stock levels in a multi-echelon inventory network is presented. Lagrangian relaxation results in (1) newsboy-style relations that provide the optimal solutions, and (2) instantaneous shadow prices for the budget constraint. Sensitivity analysis of this model will facilitate making decisions concerning the desired investment in inventory for the entire system. This model may be solved on standard nonlinear programming software and is generalizable to problems in both production and distribution settings.     

考虑碳税对备件联合订购决策影响的研究

针对价格适中、消耗量高、对装备运行起重要作用的不可修备件的库存管理问题,构建了碳税政策下由多个基层站点和一个基地站点组成的两级保障链联合库存决策模型。模型以基层站点再申请点r_i、申请量Q_i和基地站点补给次数m_i为决策变量、以备件满足率为约束、以成本为目标。最后通过策略迭代方法对模型求解,并在数值分析中研究碳税对保障链决策的影响,结果表明：碳税政策虽然增加了保障链成本,但减少了碳排放,并且在合理的税费下能够实现显著的减排效果,有助于环境成本的降低。     

A Production–Inventory Model for a Push–Pull Manufacturing System with Capacity and Service Level Constraints

We study a hybrid push–pull production system with a two‐stage manufacturing process, which builds and stocks tested components for just‐in‐time configuration of the final product when a specific customer order is received. The first production stage (fabrication) is a push process where parts are replenished, tested, and assembled into components according to product‐level build plans. The component inventory is kept in stock ready for the final assembly of the end products. The second production stage (fulfillment) is a pull‐based assemble‐to‐order process where the final assembly process is initiated when a customer order is received and no finished goods inventory is kept for end products. One important planning issue is to find the right trade‐off between capacity utilization and inventory cost reduction that strives to meet the quarter‐end peak demand. We present a nonlinear optimization model to minimize the total inventory cost subject to the service level constraints and the production capacity constraints. This results in a convex program with linear constraints. An efficient algorithm using decomposition is developed for solving the nonlinear optimization problem. Numerical results are presented to show the performance improvements achieved by the optimized solutions along with managerial insights provided.     

Optimal Ordering Policies for Inventory Problems With Dynamic Information Delays

Information delays exist when the most recent inventory information available to the Inventory Manager (IM) is dated. In other words, the IM observes only the inventory level that belongs to an earlier period. Such situations are not uncommon, and they arise when it takes a while to process the demand data and pass the results to the IM. We introduce dynamic information delays as a Markov process into the standard multiperiod stochastic inventory problem with backorders. We develop the concept of a reference inventory position. We show that this position along with the magnitude of the latest observed delay and the age of this observation are sufficient statistics for finding the optimal order quantities. Furthermore, we establish that the optimal ordering policy is of state‐dependent base‐stock type with respect to the reference inventory position (or state‐dependent (s, S) type if there is a fixed ordering cost). The optimal base stock and (s, S) levels depend on the magnitude of the latest observed delay and the age of this observation. Finally, we study the sensitivity of the optimal base stock and the optimal cost with respect to the sufficient statistics.     

A New Two‐Bin Policy for Inventory Systems with Differentiated Demand Classes

We consider an inventory system under continuous review with two demand classes that are different in terms of service level required (or penalty cost incurred for backordering of demand). Prior literature has proposed the critical level rationing (CLR) policy under which the demand from the lower priority class is backordered once inventory falls below the critical level. While this reduces the penalty cost for the higher demand class, the fill rate achieved for the lower priority demand class gets compromised. In this study, we propose a new class of two‐bin (2B) policy for the problem. The proposed 2B policy assigns separate bins of inventory for the two demand classes. The demand for each class is fulfilled from its assigned bin. However, when the bin intended for the higher demand class is empty, the demand from the higher class can still be fulfilled with the inventory from the other bin. The advantage of the 2B policy is that better fill rates are achieved, especially for the lower demand class. Computational results show that the proposed policy is able to provide a much higher service level for the lower priority class demand without increasing the total cost too much and without affecting the service level for the higher priority class. When a service level constrained optimization problem is considered, the 2B policy dominates the CLR policy when the service level difference for the two classes is not too high or the service levels required for both the classes are relatively lower.