无人零售业态下自动售卖机联合补货策略研究

研究无人零售业态下自动售卖机的多产品联合补货问题，建立由补货成本、库存持有成本、缺货成本构成的平均补货成本模型，分析容量约束与固定补货阈值下的最优补货策略。结果表明，企业会倾向于在剩余较少产品时进行补货，剩余的产品往往是投影面积最小使得相同面积可容纳最多数量的产品；比较最优补货时间与平均补货成本发现，延长补货时间可以降低平均补货成本，在补货阈值越大、固定补货成本越低或售卖机容量越小时，最优补货时间会降低，反之，平均补货成本会增加。此外，分析不同成本变动对平均成本的影响发现，单位成本变动均会引起平均补货成本的增加，且在单位库存持有成本变动时，最优补货策略会发生转移，向单位库存持有成本降低至一定程度的产品或向投影面积最低即相同面积可容纳数量最小的产品转移。     

产品回收直接再利用的管理决策研究:基于回收品品质的分析

回收品品质下降是一个客观事实,部分企业为了在成本支付和产品可靠性之间达成均衡,抛弃当期未投入使用的旧产品,并设置一个回收品可靠性阈值以降低回收成本、回收清洁成本和潜在风险成本等。本文考察电子产品的新购和回收再利用过程,以新产品订购成本、新产品库存持有成本、旧产品回收成本、旧产品清洁成本、短缺成本和潜在风险成本为目标函数,获得"可靠性阈值-补货策略"的优解。公司案例表明,(s,Q)补货策略优于(s,S)补货策略;敏感性分析表明,新购单位变动成本对总成本的影响最为明显,旧产品单位回收成本次之。     

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。     

单位保管和短缺成本均为时变的生产库存模型

基于短缺量拖后率不相同时的边生产边需求库存模型,进一步考虑单位保管和缺货成本与时间呈线性或非线性关系,建立了相应的生产库存模型.运用Mathematica5.0对模型进行仿真寻优和主要参数的灵敏度分析,结果表明,单位保管和缺货成本对库存系统各项成本影响较大,在制定库存控制策略时必须重点考虑这两个因素.     

基于顾客策略性购买和退货行为的缺货保障策略价值研究

针对产品缺货, 本文基于顾客策略性行为在存在顾客无理由退货的条件下对两类缺货保障策略(即公开库存策略和缺货补偿策略)的价值进行了深入研究。本文分别建立了不提供任何缺货保障策略、公开库存保障策略和缺货补偿保障策略的理性预期均衡模型, 通过对模型进行最优化分析发现产品缺货对最优无理由退货价格没有影响;顾客策略购买行为会破坏公开库存策略对销量的积极作用, 但这种破坏作用可以通过提供慷慨的无理由退货服务来弥补, 并且公开真实库存策略的价值优于公开虚假库存;当缺货补偿效用高于补偿成本时(称为有效的缺货补偿), 缺货补偿策略的价值优于公开库存策略。最后, 本文用Matlab软件对上述模型进行算例分析, 验证了文中理论模型的正确性。     

基于PI的企业动态库存补货模型与算法

PI(physical internet)环境下的物流网络具有互联、开放和共享的特点,缺货的PI-枢纽或零售商可根据货源选择策略动态选择为其补货的供应商或PI-枢纽。为解决PI环境下库存补货问题,提出了IB-EB(installation-echelon)混合补货策略。以最小化库存补货成本为目标,补货量和再订购点为决策变量,构建了PI环境下的动态库存补货模型。针对该混合整数非线性规划模型,应用粒子群优化算法求解出多个补货预案,再将其带入仿真环境循环优化求解。最后,以中国航空器材进出口公司为例,验证了模型可解性及算法的可行性。结果表明PI环境下货源策略的选择对库存补货成本和补货策略具有十分重要的影响,为企业在不同补货条件下选择货源提供了参考依据。     

基于需求预测的短生命周期产品订货策略研究

本文针对短生命周期产品的特点,考虑与需求因子相关的库存短缺拖后和无形变质,根据缺货时间点、订货时间点与产品到达成熟期的时间点之间的关系,建立基于短生命周期产品需求预测的3种订货策略模型:乐观订货策略,悲观订货策略和中庸订货策略模型,对模型进行了分析求解,对最优解的存在性进行了证明.然后根据实际销售数据进行需求预测和算例分析,分析各因子对于总库存成本、订货量、短缺拖后量、销售损失量以及最优订货策略的影响.最后通过订货策略分析,分析各因子对于最优订货策略的影响,并将它们划分为3种订货策略影响因子,分析结果可以指导企业在不同因子水平情况下如何调整订货策略,以降低总库存成本.     

考虑随机且可控提前期的时基补货发货策略

研究了随机且可控提前期情况下"库存补货与运输排程"(SRSS)的时基补货发货策略,在"允许缺货,缺货不补"的传统假设基础上,结合使用随机过程更新理论和优化方法,建立了扩展模型;使用仿真方法跟踪了优化策略的长期执行效果,以验证模型有效性.     

针对等待敏感顾客的缺货补偿与库存策略研究

随着企业竞争的激烈化,顾客对于等待时间越来越敏感,产品对于他的效用不仅与价格有关,而且也与获得该产品的等待时间相关.考虑了等待敏感型顾客的选择行为,针对一个生产与需求过程都存在随机性的企业,研究了差异定价及相应的库存策略.当企业持有库存时,顾客不需要等待;而当企业发生缺货时,如果顾客购买,就需要等待企业生产;企业需针对这两种情况进行差异定价.然而差异定价策略可能导致顾客采取投机的行为.文章首先推导了不存在投机行为时企业的最优策略,分析了企业实行差异定价策略的条件;进一步,还给出了防止投机行为的条件,以及存在投机行为时企业的最优策略.     

连续生产模式下的不常用备件联合采购优化分析

针对连续性生产企业不常用备件管理缺货费用难以确定的实际情况,讨论了服务水平约束的基于随机连续盘点策略的联合补充(s,C,S)随机库存问题,经与单独补充策略相比,发现其经济效益明显。同时对影响备件联合采购费用节约的因素进行敏感性分析,指出了进行此类备件库存优化的方向。     

OPTIMALITY OF STATE-DEPENDENT (s,S) POLICIES IN INVENTORY MODELS WITH MARKOV-MODULATED DEMAND AND LOST SALES

Markov-modulated processes have been used in stochastic inventory models with setup costs for modeling demand under the influence of uncertain environmental factors, such as fluctuating economic and market conditions. The analyses of these models have been carried out in the literature only under the assumption that unsatisfied demand is fully backlogged. The lost sales situation occurs in many retail establishments such as department stores and supermarkets. We use the analysis of the Markovian demand model with backlogging to analyze the lost sales case; in particular, we establish the optimality of an (s, S)-type policy under fairly general conditions.     

持有成本和变质率时变的非立即变质品库存策略

本文主要研究非立即变质品的库存策略设计问题。以平均利润最大化为决策目标,构建了一个一般化的库存模型,假设需求受即时库存水平影响且在保鲜期和变质期内库存水平对需求的影响系数不同,持有成本和变质期内的变质率均随时间发生变化,系统允许缺货且短缺量部分延迟订购。进一步证明了当参数满足一定条件时,模型存在唯一的最优解。最后,采用牛顿法给出一些具体的数值算例,并对模型中主要参数的灵敏度进行了分析。结果显示:延长物品的保鲜期将有助于增加系统的平均利润;增加变质期内的需求比增加保鲜期内的需求更有利于增加系统的平均利润;对于变质率高的产品来说,其变质处理成本对最优策略和平均利润的影响不容忽视。此外,本文所构建的模型具有一般性,因此,其应用范围更加广泛。     

库存成本变化的VMI供应链协调

提出了库存成本变化的经济订货批量(EOQ)模型，基于该模型研究了库存成本变化时供应商管理库存(VMI)系统的最优协议问题。在该系统中，订货商和供应商达成缺货成本共担协议：当缺货发生时，供应商需要向订货商支付缺货补偿。订货商和供应商分散决策，订货商通过设计协议来减少其成本，而供应商通过制定补货决策来缩小自身成本。通过与传统系统和整合系统的比较，得出了库存成本变化时VMI系统的最优补货决策和缺货成本共担协议。采用数值算例验证了分析结果。结果表明，当且仅当供应商预期成本等于整合系统的最小总成本与固定缺货罚金之和时，VMI系统与整合系统具有相同的补货决策和系统绩效，即能够实现供应链协调。     

Multi-item inventory model with quantity-dependent inventory costs and demand-dependent unit cost under imprecise objective and restrictions: A geometric programming approach

A multi-item inventory model with constant demand and infinite replenishment is developed under the restrictions on storage area, total average shortage cost and total average inventory investment cost. These restrictions may be precise or imprecise. Here, it is assumed that inventory costs are directly proportional to the respective quantities, and unit purchase/production cost is inversely related to the demand. Restricted shortages are allowed but fully backlogged. First, the problem is formulated in crisp environment taking the deterministic and precise inventory parameters. It is solved by both geometric programming (GP) and gradient-based non-linear programming (NLP) methods. Later, the problem is formulated with fuzzy goals on constraints and objectives where impreciseness is introduced through linear membership functions. It is solved using the fuzzy geometric programming (FGP) method. The inventory models are illustrated with numerical values and compared with the crisp results. A sensitivity analysis on the optimum order quantity and average cost is also presented due to the variation in the tolerance of total average inventory investment cost and total average shortage cost following Dutta et al., 1993, Fuzzy Sets and Systems, 55, 133-142.     

Combined Pricing and Portfolio Option Procurement

In this paper, we study a single‐product periodic‐review inventory system that faces random and price‐dependent demand. The firm can purchase the product either from option contracts or from the spot market. Different option contracts are offered by a set of suppliers with a two‐part fee structure: a unit reservation cost and a unit exercising cost. The spot market price is random and its realization may affect the subsequent option contract prices. The firm decides the reservation quantity from each supplier and the product selling price at the beginning of each period and the number of options to exercise (inventory replenishment) at the end of the period to maximize the total expected profit over its planning horizon. We show that the optimal inventory replenishment policy is order‐up‐to type with a sequence of decreasing thresholds. We also investigate the optimal option‐reservation policy and the optimal pricing strategy. The optimal reservation quantities and selling price are shown to be both decreasing in the starting inventory level when demand function is additive. Building upon the analytical results, we conduct a numerical study to unveil additional managerial insights. Among other things, we quantify the values of the option contracts and dynamic pricing to the firm and show that they are more significant when the market demand becomes more volatile.     

Coordinating replenishments in a supply chain with quality control considerations

We study the impact of coordinated replenishment, a popular supply chain initiative, on a quality control system. We use the (Q, S) policy to manage a two-item inventory control system. If the items are jointly replenished, the number ordered for each item varies from lot to lot. As the number varies, the sampling plan will also be changed. Companies have to determine sampling plans to minimize quality cost when the order is mixed with several items and the number of each item varies from order to order. Management's primary concern is to determine the optimal sampling sizes and acceptance numbers for all items in an order.     

Point‐of‐Use Hybrid Inventory Policy for Hospitals

Modern point‐of‐use technology at hospitals has enabled new replenishment policies for medical supplies. One of these new policies, which we call the hybrid policy, is currently in use at a large U.S. Midwest hospital. The hybrid policy combines a low‐cost periodic replenishment epoch with a high‐cost continuous replenishment option to avoid costly stockouts. We study this new hybrid policy under deterministic and stochastic demand. We develop a parameter search engine using simulation to optimize the long‐run average cost per unit time and, via a computational study, we provide insights on the benefits (reduction in cost, inventory, and number of replenishments) that hospitals may obtain by using the hybrid policy instead of the commonly used periodic policies. We also use the optimal hybrid policy parameters from the deterministic analysis to propose approximate expressions for the stochastic hybrid policy parameters that can be easily used by hospital management.      

On the Issuing Policies for Perishable Items such as Red Blood Cells and Platelets in Blood Service

Red blood cells (RBCs) and platelets are examples of perishable items with a fixed shelf life. Recent studies show that transfusing fresh RBCs may lead to an improvement of patient outcomes. In addition, to better manage their inventory, hospitals prefer to receive fresh RBCs and platelets. Therefore, as well as minimizing outdates and shortages, reducing the average age of issue is a key performance criterion for blood banks. The issuing policy in a perishable inventory system has a substantial impact on the age of issue and outdate and shortage rates. Although several studies have compared the last in first out (LIFO) and the first in first out (FIFO) policies for perishable products, only a few studies have considered the situation of blood banks where replenishment is not controllable. In this study, we examine various issuing policies for a perishable inventory system with uncontrollable replenishment, and outline a modified FIFO policy. Our proposed modified FIFO policy partitions the inventory into two parts such that the first part holds the items with age less than a threshold. It then applies the FIFO policy in each part and the LIFO policy between the parts. We present two approximation techniques to estimate the average age of issue, the average time between successive outdates and the average time between successive shortages of the modified FIFO policy. Our analysis shows in several cases that where the objective function is a single economic function, or it is formulated as a multiobjective model, the modified FIFO policy outperforms the FIFO and LIFO policies.     

Information‐Sensitive Replenishment when Inventory Records Are Inaccurate

Inspired by recent empirical work on inventory record inaccuracy, we consider a periodic review inventory system with imperfect inventory records and unobserved lost sales. Record inaccuracies are assumed to arrive via an error process that perturbs physical inventory but is unobserved by the inventory manager. The inventory manager maintains a probability distribution around the physical inventory level that he updates based on sales observations using Bayes Theorem. The focus of this study is on understanding, approximating, and evaluating optimal forward‐looking replenishment in this environment. By analyzing one‐ and two‐period versions of the problem, we demonstrate several mechanisms by which the error process and associated record inaccuracy can impact optimal replenishment. Record inaccuracy generally brings an incentive for a myopic manager to increase stock to buffer the added uncertainty. On the other hand, a forward‐looking manager will stock less than a myopic manager, in part to improve information content for future decisions. Using an approximate partially observed dynamic programming policy and associated bound, we numerically corroborate our analytical findings and measure the effectiveness of an intelligent myopic heuristic. We find that the myopic heuristic is likely sufficiently good in practical settings targeting high service levels.