基于可控提前期和服务水平约束的(Q,r)库存问题

本文研究了存在顾客流失情况下，基于可控提前期和服务水平约束的连续盘点（Q，r）库存管理同题。当市场需求分布未知时采用MiniMax方法建立年总成本函数表达式，修正以往研究中对安全系数取值范围错误判断，推导出合理的安全系数取值范围，并给出最优解的计算方法。     

大规模定制背景下可控提前期通用件安全库存优化算法

随着买方市场的形成,大规模定制生产模式已为企业广为采用,其中基于时间的竞争成为企业保持持续竞争优势的关键.通用件作为一种生产运作方式,它在降低企业内部的零部件多样性的同时,也促使企业向市场提供大量多样化的产品,提高响应市场的速度.合理控制提前期则能够减少安全库存和缺货损失、提高顾客服务水平和企业的竞争力.研究结合大规模生产特点,探索了模式下零件的组配流程及生产阶段,对可控提前期通用件安全库存管理方法进行了深入分析,构建了一个基于可控提前期的通用件安全库存模型及算法,并通过算例验证求得使提前期成本最低时的最优安全库存量.     

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.     

提前期可控的模糊需求周期盘点补充订货模型研究

为解决具有模糊需求的可控提前期库存管理问题,建立了提前期和盘点周期作为决策变量的周期性盘点补充订货模型,采用符号距离方法对模型进行反模糊化求解,并设计了一确定其最优存储策略的算法。结合算例分析了需求的模糊性对最优盘点周期和最小成本的影响。     

弹性需求下可控提前期供应链库存优化的信用期机制

研究了弹性需求下可控提前期供应链库存优化的信用期机制,在一个固定订货间隔期模型中,假设需求与价格相依,且提前期可以通过额外的赶工成本进行压缩的情况下,分别考虑了买卖双方合作和不合作情形下的最优定价、订货和信用期决策.最后通过数值分析进行验证,并建立Nash协商模型进行利益分配.     

制造企业库存管理与企业绩效的实证研究——基于沪深制造类上市公司1997-2010年的面板数据

本文以国内256家沪深制造类上市公司1997-2010年的年度财务数据为样本,利用Panel Data分析方法对国内制造业库存水平的变动趋势及关键影响因素进行了实证研究。结果发现制造企业库存水平与库存比重、毛利率、公司规模和提前期显著正相关,控制相关因素后修正库存水平逐年上升,库存周转居中企业的总资产报酬率低于库存周转较慢和较快的企业,与相关研究结论不一致。本文还分行业对这一问题展开了研究,其结论能为制造企业库存管理活动提供有益建议。     

基于多重指标下ABC分类法的煤矿库存物资分类

传统的ABC分类法基于年销售额单一度量标准,容易忽视其它影响库存物资的因素。鉴于此,本文应用多重指标的ABC分类法对郑州煤电物资供销公司的库存物资进行分类。文中比较了两个指标(月平均使用金额与提前期)、三个指标(月平均使用金额、月平均单位库存成本或月平均单位成本与提前期)及五个指标(月平均使用数量、提前期、供应商数量、月平均单位库存成本、月平均销售成本)的分类效果,另外,提前期的取值也分别采用最大值、最小值、平均值进行了计算。与现场管理者的经验值比较,结果表明采用两个指标(月平均使用金额与提前期)且提前期取最小值的吻合效果最好。本研究成果可应用于煤矿物资的分类,可根据具体实际情况,添加度量物资重要性的指标。     

模糊环境下提前期对安全库存的影响

设置安全库存可以有效管理供应链的不确定性,提高服务水平,降低缺货风险.本文基于可信性理论,研究了当需求为模糊变量,提前期分别为固定值和模糊变量时.节点企业安全库存量的确定问题.通过实际算例,分析了模糊环境下提前期对安全库存量的影响.     

条件延期付款下一体化可控提前期模型研究

在一体化决策的供应链中,假设提前期与提前期成本服从幂函数关系,生产商允许零售商延期付款,但需要在订货时预付部分货款。首先,在延迟付款期给定时,通过建立该问题的数学模型,证明了不考虑决策变量整数约束时,系统存在唯一最优生产量、提前期和生产商每个生产周期内的运输批次,使得供应链总成本最小,并设计求解算法对问题进行了求解。以此为基础,假设延迟付款期是零售商订货量的增函数,结合模型的解析性质,给出了新的求解算法。最后通过数值算例和敏感性分析,说明了所得结论及其管理启示。     

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。     

Reducing lost-sales rate in (T, R, L) inventory model with controllable lead time

In order to establish a good image and to enhance customer’s loyalty, many efforts such as upgrading the servicing facilities, maintaining a high quality of products and increasing expenditure on advertisement could be made by a selling shop. Naturally, an extra-added cost must be spent for these efforts and it is expected to have a result to reduce the shortage cost of lost-sales and the total expected annual cost. This paper explores a probabilistic inventory model with optimal lost-sales caused by investment due to two different types of cost functions. We consider that the lead time can be shortened at an extra crashing cost, which depends on the length of the lead time. Moreover, we assume that the lost-sales rate can also be reduced by capital investment. The purpose of this paper is to establish a (T, R, L) inventory model with controllable lead time and to analyze the effects of increasing two different types of investments to reduce the lost-sales rate, in which the review period, lead time and lost-sales rate are treated as decision variables. We first formulate the basic periodic review model mathematically with the capital investment to reduce lost-sales rate. Then two models are discussed, one with normally distributed protection interval demand and another with distribution-free case. For each model, two investment cost functional forms, logarithmic and power, are employed for lost-sales rate reduction. Two computational algorithms with the help of the software Matlab are furnished to determine the optimal solution. In addition, six numerical examples and sensitivity analysis are presented to illustrate the theoretical results and obtain some managerial insights. Finally, the effect of lost-sales rate reduction is investigated. By framing this new model, we observe that a significant amount of savings can be easily achieved to increase the competitive edge in business. The results in the numerical examples indicate that the savings of expected annual total cost are realized through lost-sales reduction.     

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.     

Determining optimal order splitting and reorder level for N-supplier inventory systems

This paper considers multiple-supplier single-item inventory systems, where the item acquisition lead times of suppliers and demand arrival are random, and backorder is allowed. The acquisition takes place when the inventory level depletes to a reorder level, and the order is split among multiple suppliers. The acquisition lead times may have different distributions, the unit purchasing prices from suppliers may be different, and thus the order quantities for different suppliers may be different. The problem is to determine the reorder level and order quantity for each supplier so that the expected total cost per unit time, consisting of the fixed ordering cost, procurement cost, inventory holding cost and shortage cost, is minimized. We develop a mathematical model describing the system in detail. We also conduct extensive numerical experiments to analyze the advantages and distinct characteristics of multiple-supplier systems.     

An inventory model for slow moving items subject to obsolescence

In this paper, we consider a continuous review inventory system of a slow moving item for which the demand rate drops to a lower level at a known future time instance. The inventory system is controlled according to a one-for-one replenishment policy with a fixed lead time. Adapting to lower demand is achieved by changing the control policy in advance and letting the demand take away the excess stocks. We show that the timing of the control policy change primarily determines the tradeoff between backordering penalties and obsolescence costs. We propose an approximate solution for the optimal time to shift to the new control policy minimizing the expected total cost during the transient period. We find that the advance policy change results in significant cost savings and the approximation yields near optimal expected total costs.     

Simultaneous optimization of capacity and planned lead time in a two-stage production system with different customer due dates

We consider a two-stage make-to-order manufacturing system with random demands, processing times, and distributed customer due dates. The work to each stage is released based on a planned lead time. A general approach to minimize total inventory holding and customer order tardiness cost is presented to find the optimal manufacturing capacities and planned lead times for each manufacturing stage. Expressions are derived for work-in process inventories, finished-goods-inventory and expected backorders under the assumption of a series of M/M/1 queuing systems and exponentially distributed customer required lead times. We prove that the distribution of customer required lead time has no influence on the optimal planned lead times whenever capacity is predefined but it influences the optimal capacity to invest into. For the simultaneous optimization of capacity and planned lead times we present a numerical study that shows that only marginal cost decreases can be gained by setting a planned lead time for the upstream stage and that a considerable cost penalty is incurred if capacity and planned lead time optimization are performed sequentially.     

An inventory system with investment to reduce yield variability and set-up cost

The set-up cost and yield variability are given and fixed in existing production/inventory models with random yields. However, in many practical situations, they can be reduced by investment in modern production technology. In this paper, we consider an inventory system with random yield in which both the set-up cost and yield variability can be reduced through capital investment. The objective is to determine the optimal capital investment and ordering policies that minimize the expected total annual costs for the system. In addition, an iterative solution procedure is presented to find the optimal order quantity and reorder point and then the optimal set-up cost and yield standard deviation. Numerical examples are given to illustrate the results obtained and assess the cost savings by adopting capital investments. Managerial implications are also included.     

An (s,S) random lifetime inventory model with a positive lead time

Positive lead times substantially complicate the modeling and analysis of inventory systems with finite shelf lifetimes and they have not been sufficiently addressed in the existing literature. In this paper, we analyze an (s, S) continuous review model with a positive lead time. We assume an exponential lifetime and an exponential lead time. Matrix-geometric solutions can be obtained for the steady state probability distribution of the inventory level. We then derive the total expected cost function. We carry out numerical studies and gain insights to the selection of system parameters. The findings on the impact of a positive lead time on the optimal reorder point and reorder batch size will be useful in developing strategies in handling inventory problems with finite lifetimes and positive lead times.     

A stochastic periodic review integrated inventory model involving defective items, backorder price discount, and variable lead time

The purpose of this article is to investigate a stochastic integrated supplier-retailer inventory problem. The model analyzed in this article explores the problem of the protection interval, the backorder price discount, the lead time, and the numbers of shipments from the supplier to the retailer in one production run as control variables to widen applications for an integrated periodic review inventory model. We consider the situation in which the supplier and the retailer establish a long-term strategic partnership and contract to jointly determine the best strategy. We assume that the protection interval demand follows a normal distribution. Our objective is to determine the optimal review period, the optimal backorder price discount, the optimal lead time, and the optimal number of shipments from the supplier to the retailer in one production run, so that the joint expected annual total cost incurred has the minimum value. Furthermore, an algorithm of finding the optimal solution is developed. Also, the sensitivity analysis included and a numerical example is given to illustrate the results of the proposed model.     

在预报更新的环境下具有两种配送方式的供应链模型

本文研究在预报更新环境下具有快、慢两种配送方式和需求预报更新的库存系统，为了得到更多关于费用参数和预报改进对最优定货量以及最优的平均费用的影响，我们考虑两个周期的情形．以动态规划为工具我们得到了系统的最优策略．对于需求预报服从均匀分布情形，本文得到了最优定货量和最优的平均总费用的精确表达式．我们通过一些数值例子来说明库存费用、罚金、需求的预报改进和预报误差对最优定货量和最优的