Unlimited Stock Research Articles

A new replenishment policy based on emergency orders for a family of products

This paper considers a two-echelon supply chain with several distribution centres (DCs) and a number of retailers or consumption centres (CCs). Several products are managed and supplied in this chain, but we focus on a family of perishable products (drugs) with a high cost, particularly variable demand and transiting from the same supplier to the same consumption centres. We also assume that the suppliers have an unlimited stock, the delivery time is close to zero (a few hours) and shortages are not authorised at the CCs. In this case, where the constitution of a large safety stock (SS) is not cost-effective, we propose a new ordering policy based on 'replenishment driven by shortage'. This method consists in waiting for a shortage of one product, triggering an emergency order for this product and, at the same time, replenishing other items of the same family. This replenishment policy is based on the mathematical function for calculating the optimal level of each product of the same family by using the probability of not having any shortage before time t. Numerical experimentation compares the total expected costs of the proposed method with a traditional order-up-to-level policy.

A new replenishment policy based on emergency orders for a family of products

This paper considers a two-echelon supply chain with several distribution centres (DCs) and a number of retailers or consumption centres (CCs). Several products are managed and supplied in this chain, but we focus on a family of perishable products (drugs) with a high cost, particularly variable demand and transiting from the same supplier to the same consumption centres. We also assume that the suppliers have an unlimited stock, the delivery time is close to zero (a few hours) and shortages are not authorised at the CCs. In this case, where the constitution of a large safety stock (SS) is not cost-effective, we propose a new ordering policy based on 'replenishment driven by shortage'. This method consists in waiting for a shortage of one product, triggering an emergency order for this product and, at the same time, replenishing other items of the same family. This replenishment policy is based on the mathematical function for calculating the optimal level of each product of the same family by using the probability of not having any shortage before time t. Numerical experimentation compares the total expected costs of the proposed method with a traditional order-up-to-level policy.

Near-optimal ( r, Q) policies for a two-stage serial inventory system with Poisson demand

We consider a two-stage serial inventory system whose cost structure exhibits economies of scale in both stages. In the system, stage 1 faces Poisson demand and replenishes its inventory from stage 2, and the latter stage in turn orders from an outside supplier with unlimited stock. Each shipment, either to stage 2 or to stage 1, incurs a fixed setup cost. We derive important properties for a given echelon-stock ( r, Q) policy for an approximation of the problem where all states are continuous. Based on these properties, we design a simple heuristic algorithm that can be used to find a near-optimal ( r, Q) policy for the original problem. Numerical examples are given to demonstrate the effectiveness of the algorithm.

Optimal Policies for Multiechelon Inventory Problems with Markov-Modulated Demand

This paper considers a multistage serial inventory system with Markov-modulated demand. Random demand arises at Stage 1, Stage 1 orders from Stage 2, etc., and Stage N orders from an outside supplier with unlimited stock. The demand distribution in each period is determined by the current state of an exogenous Markov chain. Excess demand is backlogged. Linear holding costs are incurred at every stage, and linear backorder costs are incurred at Stage 1. The ordering costs are also linear. The objective is to minimize the long-run average costs in the system. The paper shows that the optimal policy is an echelon base-stock policy with state-dependent order-up-to levels. An efficient algorithm is also provided for determining the optimal base-stock levels. The results can be extended to serial systems in which there is a fixed ordering cost at stage N and to assembly systems with linear ordering costs.

Effectiveness of (R, Q) policies in one‐warehouse multiretailer systems with deterministic demand and backlogging

Consider a distribution system with a central warehouse and multiple retailers. Customer demand arrives at each of the retailers continuously at a constant rate. The retailers replenish their inventories from the warehouse which in turn orders from an outside supplier with unlimited stock. There are economies of scale in replenishing the inventories at both the warehouse and the retail level. Stockouts at the retailers are backlogged. The system incurs holding and backorder costs. The objective is to minimize the long-run average total cost in the system. This paper studies the cost effectiveness of (R, Q) policies in the above system. Under an (R, Q) policy, each facility orders a fixed quantity Q from its supplier every time its inventory position reaches a reorder point R. It is shown that (R, Q) policies are at least 76% effective. Numerical examples are provided to further illustrate the cost effectiveness of (R, Q) policies. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 422–439, 2000

A Staggered Ordering Policy for One-Warehouse, Multiretailer Systems

We consider a one-warehouse, N-identical-retailer model. Random demands occur at the retailers with complete backlogging. The retailers replenish their inventories from the warehouse, which in turn orders from an outside supplier with unlimited stock. Each retailer places an order every N periods according to a base-stock policy, and the reorder intervals of the retailers are staggered so that only one retailer places an order in each period. The warehouse orders according to an (s, S) policy based on its own inventory position. We consider two allocation policies, past priority allocation (PPA) and current priority allocation (CPA), which specify how the retailer orders are filled at the warehouse. For the PPA model, we provide an exact procedure for computing the long-run average total cost. Based on the exact procedure, we develop an approximate model that can be used to determine near-optimal control parameters for both the PPA and the CPA model. We conduct a computational study to test the effectiveness of the approximate model and to compare the performance of the two allocation policies.

Effectiveness of (R, Q) policies in one-warehouse multiretailer systems with deterministic demand and backlogging

Consider a distribution system with a central warehouse and multiple retailers. Customer demand arrives at each of the retailers continuously at a constant rate. The retailers replenish their inventories from the warehouse which in turn orders from an outside supplier with unlimited stock. There are economies of scale in replenishing the inventories at both the warehouse and the retail level. Stockouts at the retailers are backlogged. The system incurs holding and backorder costs. The objective is to minimize the long-run average total cost in the system. This paper studies the cost effectiveness of (R, Q) policies in the above system. Under an (R, Q) policy, each facility orders a fixed quantity Q from its supplier every time its inventory position reaches a reorder point R. It is shown that (R, Q) policies are at least 76% effective. Numerical examples are provided to further illustrate the cost effectiveness of (R, Q) policies. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 422–439, 2000

94%-Effective Policies for a Two-Stage Serial Inventory System with Stochastic Demand

A two-stage inventory system is considered where Poisson demand occurs at Stage 1, and Stage 1 replenishes its inventory from Stage 2, which in turn orders from an outside supplier with unlimited stock. Each shipment, either to Stage 2 or to Stage 1, incurs a fixed setup cost. Under the assumption that the supply leadtime at Stage 2 is zero, we characterize a simple heuristic policy whose long-run average cost is guaranteed to be within 6% of optimality, i.e., a 94%-effective policy. The paper also provides heuristic policies for more general inventory systems and reports computational results.

Worst-case analysis of ( R, Q) policies in a two-stage serial inventory system with deterministic demand and backlogging

This paper considers a two-stage inventory system where customer demand arises at stage 1, stage 1 replenishes its inventory from stage 2, and stage 2 orders from an outside supplier with unlimited stock. Customer demand is assumed to arrive continuously at a constant rate and is backlogged when stage 1 runs out of stock. There are economies of scale in transferring inventories from the outside supplier to stage 2 or from stage 2 to stage 1. We show that ( R, Q) policies are 86%-effective. Numerical examples are provided to further demonstrate the cost effectiveness of ( R, Q) policies.

L'information généralisée comme procédure d'éradication du monde social

The information highway, and networks like Internet, aim to provide direct access to a potentially unlimited stock of information, and they intend to do this through standardized procedures. This is their real goal, rather than simply increasing the rapidity of the communication process. Thus they seem to operate a double process of rupture - with an initial elaboration (contextually situated) of the data involved (demateriali- zation of supply) and with the experimental process of know- ledge which leads to questioning (deserialization of demand, or inquiry). Both thus create a fictitious context in which a universal and timeless "right" to information is supposed to occur, within a general process of simulation of the real world. This leads to an eradication of the process of information of the practical social system, transporting it into a uni-demensional world of simulacrum: this is the very image which the major science fiction novels have always given us, dominated by a huge, omnipotent computer.