On deficiencies of common ordering policies for multi-level inventory control

We consider two common types of ordering policies for multi-level inventory control: installation stock (R,Q)-policies and echelon stock (R,Q)-policies. The batch quantities are assumed to be given, but each policy is optimized with respect to its reorder point R. We demonstrate that there is no bound for the worst case performance ratio of these policies when applied to distribution inventory systems with a central warehouse and a number of retailers.     

Nervousness in inventory control: Analytical results

Using a rolling horizon planning framework in inventory control leads to nervousness in the planning system caused by instability of order release decisions in successive planning cycles. For a single-stage inventory system with stochastic demand it is shown analytically, how planning stability is affected by policy parameters if (s, n Q) and (s, S) control rules are applied. It turns out that the reorder points does not influence stability whereas the lot sizeQ and minimum reorder quantityS-s can have a considerable impact. Under the aspect of nervousness the (s, n Q) policy can be assessed to be less risky than the (s, S) rule.     

Optimal batch ordering policies for assembly systems with guaranteed service

For a supply chain modelled as a multi-echelon inventory system, effective management of its inventory at each stock is critical to reduce inventory costs while assuring a given service level to customers. In our previous work, we used the guaranteed-service approach (GSA) to design optimal echelon batch ordering policies for continuous-review serial systems with Poisson customer demand and fixed order costs. The approach assumes that the final customer demand is bounded and each stock has a guaranteed service time in the sense that the demand of its downstream stock can always be satisfied in the service time. This paper extends this work by considering more general assembly systems. We first derive an analytical expression for the total cost of the system in the long run. The problem of finding optimal echelon batch ordering policies for the system can then be decomposed into two independent sub-problems: order size decision sub-problem and reorder point decision sub-problem. We develop efficient dynamic programming algorithms for the two sub-problems. Numerical experiments on randomly generated instances show the effectiveness of the proposed approach.     

An optimised target-level inventory replenishment policy for vendor-managed inventory systems

In vendor-managed inventory (VMI) systems the supplier is responsible for replenishing customers and for deciding when and how much to deliver. One of two inventory policies is typically employed by the supplier. The first one, called the maximum level (ML) policy, gives full freedom to the supplier to deliver any quantity as long as it respects customer inventory capacities. The alternative, which is more constrained, is called the order-up-to (OU) policy. It states that the supplier has to bring the customer inventory up to its maximum capacity level upon delivery. We propose a new tactical policy in the context of VMI systems, called optimised target-level (OTL), under which when the supplier visits a customer, the quantity delivered is such that the final inventory will always be at the same customer-dependent OTL. We perform a computational evaluation of this new policy against both traditional strategies on benchmark instances. We show that it yields lower costs and inventory levels than the OU policy, and is only marginally more expensive than the ML policy, while being easier to implement.     

A prototype knowledge-based system (KBS) for selection of inventory control policies

In a previous paper Parlar presents an expert system for advising on the selection of production/inventory models. A deficiency of this system is that the user must review the reference literature to locate the corresponding inventory control policy. This paper presents a prototype expert system where the knowledge base contains the control policy equations for reorder level (L), reorder quantity (Q) and total system cost (TC). Moreover, after identifying the inventory control policy equations, the expert system then shells to an external computer program to numerically solve the model that the rules select. It is believed that the output of more precise information to the user will lead to more accurate usage of inventory models.     

制造企业库存长鞭效应影响因子分析及控制方法

长鞭效应是供应链管理中由于供应链合作伙伴之间缺乏合作与协调的结果。从理论上刻画了长鞭效应的内在本质,分析了产生长鞭效应的原因,以一个跨国公司的库存管理为例,详细分析了影响长鞭效应三个方面的因子：（1）集中式与分散式管理;（2）需求与供应特征;（3）产品类型与库存再订货点。还从供需合作关系的角度提出了改善长鞭效应的几个控制方法。     

Innovative vendor-managed inventory strategy exploiting interconnected logistics services in the Physical Internet

Traditional supply chain networks are often designed in the interests of a company. Once the network has been defined, the storage and distribution of goods are usually fixed and restricted within the network. This is assumed to be an inherent limit of current inventory control research. Instead of specialised hierarchical storage networks, this paper proposes an innovative vendor-managed inventory strategy exploiting the Physical Internet (PI), which is an open, universal, interconnected logistics system. In such a system, facilities and means of transport are shared and can be allocated according to demands of users. As a result, the PI allows users to stock anywhere in the network and also provides open multisourcing options for orders with on-demand warehousing services within the PI. Inventory decisions can be made dynamically by each player to minimise networkwide inventory levels. A non-linear, simulation-based optimisation model was developed for the vendors’ inventory decision-making when confronted with stochastic demands. A metaheuristic using simulated annealing was applied to solve the problem, and then, the optimised inventory decisions were validated using simulation. The results suggest that the proposed PI inventory model can reduce the total logistics cost while maintaining a comparable or better level of end customers’ services.     

Safety stock determination based on parametric lead time and demand information

In many production environments where demand and lead times are variable, significant levels of safety stock inventory are required to assure timely production and delivery of the final product. Traditional models to determine the appropriate safety stock level may result in more safety stocks at sub-assembly and finished goods levels than necessary and thus lead to higher inventory carrying costs than desired. Such models generally incorrectly assume that the demand during the lead time follows a normal distribution. This paper revisits and analyses a re-ordering point inventory model developed by Estes (1973 Estes, R. 1973. The joint probability approach and reorder point determination. Journal of Production and Inventory Management, 14(2): 50–56.  [Google Scholar]) that accounts for demand and lead time variability without making any particular distributional assumptions. Instead, it focuses on historical data to determine the possible outcomes of the replenishment cycle. We compare the proposed model with the traditional model by conducting simulation analysis using three data sets obtained from an electronics manufacturer. The results indicate that the proposed model yields much closer to target service levels and lower inventory carrying costs than the traditional model, regardless of the data set used.     

A joint replenishment policy with individual control and constant size orders

We consider inventory systems with multiple items under stochastic demand and jointly incurred order setup costs. The problem is to determine the replenishment policy that minimises the total expected ordering, inventory holding, and backordering costs–the so-called stochastic joint replenishment problem. In particular, we study the settings in which order setup costs reflect the transportation costs and have a step-wise cost structure, each step corresponding to an additional transportation vehicle. For this setting, we propose a new policy that we call the (s, 𝒬) policy, under which a replenishment order of constant size 𝒬 is triggered whenever the inventory position of one of the items drops to its reorder point s. The replenishment order is allocated to multiple items so that the inventory positions are equalised as much as possible. The policy is designed for settings in which backorder and setup costs are high, as it allows the items to independently trigger replenishment orders and fully exploits the economies of scale by consistently ordering the same quantity. A numerical study is conducted to show that the proposed (s, 𝒬) policy outperforms the well-known (𝒬, S) policy when backorder costs are high and lead times are small.     

零件寿命函数的备件库存控制

针对价值高、存储时间长的A类备件最佳再订货时间和订货批量问题,通过对零件历史使用寿命进行统计分析,拟合得到了此零件的寿命函数,由此函数得到零件在某一时间段内出现故障的概率,结合此零件备件的缺货损失,计算出这一时间段内缺货损失的期望值,通过权衡缺货损失期望值和存储费用,构建了使总成本最低的库存模型,得到备件的最佳再订货时间和订货批量.经实例验证,使用此模型后存储时间和存储费用降低了76.29%.     

Theory of constraints based mafia offer for supply chains of deteriorating products

Mafia offer is an unbelievably good offer that a company makes to its customers; the attractiveness of the offer makes it impossible for the customers to decline the offer and difficult for the competitors to match it [Cox, James, III, and John Schleier. 2010. Theory of Constraints Handbook. McGraw-Hill]. This study analyses the performance of one such offer that a producer of deteriorating items can make to its customers in the supply chain, such as retailers and distributors. The results from the analytical model show that the mafia offer increases the profits of both the producer and the retailer in a deteriorating items' supply chain. The efficacy of the proposed offer is tested for multiple combinations of ordering cost, wholesale price, and the retailer's cash constraints. The experimental results suggest that the producer would be able to increase its profits by more than 60%, for a given level of retailer's profits, owing to the mafia offer. The availability of the existing items offered by the retailer will increase significantly, despite a reduction in the retailer's inventory levels. The offer will result in an average increase of over 56% in the variety of items held by the retailer. The producer will also be able to command significantly higher margins (more than 44%) from the retailer for the existing items without adversely affecting the retailer's profitability.     

Vendor-managed inventory and the effect of channel power

We analyze decentralized supply chains that follow general continuous review (Q, R) inventory policies subject to vendor-managed inventory agreements where the supplier chooses the order quantity Q, and the retailer chooses the reorder point R. Within the VMI scenario, we explore the effect of divisions of channel power on supply chain and individual agent performance by examining different game theoretic models. Optimal policies and analytical results, including existence and uniqueness proofs for equilibrium solutions under VMI, are derived. Numerical results are provided to compare the effectiveness of VMI and to analyze different channel power relationships under a variety of environmental conditions. We find that VMI can result in considerable supply chain savings over traditional relationships and that the relative division of channel power can significantly effect the performance of VMI. Interestingly, we find that the greatest system benefits from VMI arise in asymmetric channel power relationships, but that individual agents lack the incentive to assume a leadership role.     

Design of an integrated supplier selection and multi-echelon distribution inventory model in a built-to-order supply chain environment

The paper deals with the development of an integrated supplier selection and multi-echelon distribution inventory model (MEDIM) for the original equipment manufacturing company in a built-to-order supply chain environment using fuzzy analytical hierarchy process (FAHP) and a genetic algorithm. The main objective is to design the integrated qualitative decision-making of the supplier selection model using FAHP with that of the quantitative mathematical model for the distribution inventory supply chain using a genetic algorithm to the built-to-order environment. The proposed model is validated by considering the case study in a tyre industry in Southern India. The software used for programming is C++ language.     

基于仿真技术的血液中心库存系统优化研究

提出提前期内等效每日需求的概念,给出紧急采血点的解析求解方法;结合我国某大型血液中心2005~2008年运行实例,建立计算机仿真模型;通过运行该模型为该中心的库存管理工作提出建议,优化后的库存系统服务水平达到99%,并且血液过期浪费量和紧急采血次数均有了明显下降;验证了本仿真模型的可行性和有效性,对其它易腐物库存管理也有一定借鉴作用。     

基于设备使用周期的备件库存控制模型研究

由于设备系统的复杂性、设备故障的随机性,备件的需求难以准确确定,相关费用也难以做出准确评估,从而使得备件这一类库存控制问题变得相当复杂.基于备件的需求量与设备使用周期密切相关这一关键点,从设备的整个使用周期入手,结合设备的使用情况,在备件需求率随时间变化的情况下,对备件库存控制问题进行了研究,建立了在设备整个使用周期内使备件总订货成本和存储费用最低的数学模型,给出了备件最佳订货次数、订货时间和订货批量的计算公式.最后给出了一个算例以证明模型的实用性.     

Performance evaluation for tandem multi-factory supply chains: an approximate solution

Predicting the performance of multistage manufacturing systems is usually viewed as challenging because of unexpected machine breakdowns, random processing times, uncertain inter-factory transportation times, etc. In this paper, the authors formulate an approximate model for the tandem manufacturing systems, where the inventory in each buffer is monitored based on the (s, Q) discipline. This model divides a multistage system into a series of primitive line segments, each of which is characterised by a continuous time discrete state Markov process. The model may be applied in two types of systems: (1) tandem flow lines with batch processing and (2) multi-factory manufacturing supply chain, where inter-factory material transportation is required. Based on the model, a number of commonly used performance measures, including throughput, inventory, transportation frequency, etc., can be estimated. These estimates may enable manufacturers to evaluate the performance of the systems, and hence improve the management of production and inventory.     

The bullwhip effect in hybrid supply chain

As the service is becoming the strategic preference in the manufacturing industry, more and more manufacturing companies provide customers with total solutions by integrating services into their core product offerings, which is usually implemented in so-called hybrid supply chain (HSC). The HSC is formed as a chain by a group of manufacturers and service providers who work together to offer total solutions to customers. In HSC, customers’ responses to variable service levels and the interaction between inventory strategy and service capacity strategy have a great impact on supply chain instability, which represents an important concern in supply chain research. To tackle this problem, we establish a system dynamics model, by taking the HSC for an elevator company in China as an example. Firstly, we analyzed the oscillation characteristics of service flow and product flow. Then, we proposed the performance metrics of bullwhip effect in HSC. Finally, based on the model, we find that the bullwhip effect of HSC could be smoothened by incorporating service capacity adjustment strategy into the inventory replenishment policy.     

Planning stability under (s,S) inventory control rules

The problem of planning instability caused by new and actualized data in material coordination systems with periodic review and replanning activities has been discussed from several viewpoints in literature and it is of great practical importance. The application of a rolling horizon planning framework in forecast-dependent inventory control leads to nervousness in the planning system caused by different order release decisions in successive planning cycles. In this paper a setup-oriented planning stability concerning deviations of planned orders in all periods of a given stability horizon in a single-stage inventory system with arbitrary stochastic demand is analyzed. The influence of an (s, S) control rule on planning stability is derived analytically. It is shown that the reorder points does not affect stability whereas the minimum reorder quantityS-s has a considerable impact. Especially, it is analyzed how planning stability depends on the length of the stability horizon, on period-specific weights, and on the accuracy of demand forecasts.     

零件中心备件库存分类控制的研究

分析了库存ABC分类法存在的问题,提出了基于客户服务水平的库存ABC分类法,给出了相应的订货点、安全库存和订货量的计算模型,实现了提高顾客服务水平、降低库存成本的目标。