Economic ordering policy of deteriorated item for vendor and buyer: An integrated approach

This study develops an economic ordering policy of a deteriorating item with a constant production and demand rate. By considering the view of both the vendor and buyer, a mathematical model subject to single-vendor-single-buyer and multiple deliveries per order is developed. It can be shown that the integrated approach results in an impressive cost-reduction compared with an independent decision by the buyer.     

A mixed inventory model with variable lead time and random supplier capacity

In this paper, we have studied analytically the implication of a controllable lead-time and a random supplier capacity on the continuous review inventory policy, in which the order quantity, reorder point and lead-time are decision variables. Two models are considered: the normal lead-time demand and lead-time demand is distributed free. For both cases, after formulating the general model, some properties of the optimal ordering policy have been developed. Particularly, we have shown that the expected annual total cost is a unimodal function and quasi-convex in the order quantity. When the variable capacity distribution is exponential, we develop effective procedures for finding the optimal solutions. Furthermore, the effects of parameters are also performed.     

Emergency inventory ordering assuming Poisson demands

Abstract

Most business and industrial firms use some procedure for emergency ordering. If independent demand for low-volume, high-cost items is Poisson distributed, subsequent analyses reveal that emergency ordering may be less expensive than carrying extra safety stock. Emergency ordering reduces the out-of-stock cost as well as the required safety stock. Total cost is sensitive to the lead time required for emergency orders. The results are particularly applicable to maintenance inventory. Under the assumptions of this study, the conclusion may be drawn that an emergency ordering system may approach the theoretical minimum for operating an inventory system.     

A discussion on economic ordering policy of deteriorated item for vendor and buyer

Yang and Wee (Economic ordering policy of deteriorated item for vendor and buyer: an integrated approach. Prod. Plan. & Cont., 2000, 11(5), 474–480) proposed an ordering policy for a vendor--buyer integrated model. This note examines the cost component of Yang and Wee's model and gives some insight on the derivation of the holding cost function. We have discovered that their model violates the positive holding cost characteristic and the total quantity-equality characteristic. A proposal to eradicate the problem is given.     

The resource constrained single-item inventory problem with demand-dependent unit cost

In this paper, we present an economic order quantity (EOQ) with both demand-dependent unit cost and restrictions. An analytical solution of the EQO is derived using a recent and simple method, which isthe geometric programming approach. The EOQ inventory model with demand-dependent unit cost without any restriction and the classical EOQ inventory model are obtained.     

具有多元马氏需求的多产品多阶段库存优化模型

本文研究一类新的多产品库存控制策略,即具有多元马氏需求特征的多产品多阶段的订货点订货量(Q, R, SS)策略,该策略考虑市场需求在不同产品之间具有多元马氏转移特征,并考虑缺货因素设置安全库存。论文首先建立了多产品多阶段的多元马氏需求预测模型,并通过该模型确定了各种产品需求之间的关系。同时,在该模型的理论基础上,提出了多产品多阶段的总期望成本模型及其最优(Q, R, SS)策略,进而结合算例给出模型的最优策略的数值解。     

Distribution lot-sizing models for arborescent supply chains with discrete-period variable demand

This study formulates a novel mixed-integer programming lot-sizing model for arborescent supply chains with discrete-period variable demand and then develops an efficient two-phase heuristic method, in which a combined multi-period demand ordering policy, rather than the lot-for-lot ordering policy usually assumed in previous papers, is adopted. Two important properties are introduced and used to obtain a better initial feasible solution. The good performance of the proposed heuristic method is verified through a comparison with the optimal solution method. It is also shown that the performance of the proposed combined multi-period demand ordering method is superior to that of the lot-for-lot ordering method. Sensitivity analysis is conducted to explore the impacts of changing the values of relevant parameters on the total supply chain cost, the total number of orders and the total number of opened members. Finally, a well-known logistics company in Taiwan is chosen to demonstrate the excellent performance and the aptness of the proposed ordering method.     

The Effects of Sharing Upstream Information on Product Rollover

The process of introducing new and phasing out old products is called product rollover. This paper considers a periodic‐review inventory system consisting of a manufacturer and a retailer, where the manufacturer introduces new and improved products over an infinite planning horizon using the solo‐roll strategy. We consider two scenarios: (1) the manufacturer does not share the upstream information about new‐product introduction with the retailer and (2) the manufacturer shares the information. For each scenario, we first derive the decentralized ordering policy and the system‐optimal ordering policy with given cost parameters. We then devise an optimal supply chain contract that coordinates the inventory system. We demonstrate that when the inventory system is coordinated, information sharing improves the performance of both supply chain entities. However, this may not be true if the inventory system is not coordinated. We also show that under the optimal contract, the manufacturer has no incentive to mislead the retailer about new‐product information in the information‐sharing model. When demand variability increases, information sharing adds more benefits to the coordinated supply chain. Our research provides insights about coordinating product, financial, and information flows in supply chains with product rollover.     

Myopic Analysis for Multi‐Echelon Inventory Systems with Batch Ordering and Nonstationary/Time‐Correlated Demands

We provide an exact myopic analysis for an N‐stage serial inventory system with batch ordering, linear ordering costs, and nonstationary demands under a finite planning horizon. We characterize the optimality conditions of the myopic nested batching newsvendor (NBN) policy and the myopic independent batching newsvendor (IBN) policy, which is a single‐stage approximation. We show that echelon reorder levels under the NBN policy are upper bounds of the counterparts under both the optimal policy and the IBN policy. In particular, we find that the IBN policy has bounded deviations from the optimal policy. We further extend our results to systems with martingale model of forecast evolution (MMFE) and advance demand information. Moreover, we provide a recursive computing procedure and optimality conditions for both heuristics which dramatically reduces computational complexity. We also find that the NBN problem under the MMFE faced by one stage has one more dimension for the forecast demand than the one faced by its downstream stage and that the NBN policy is optimal for systems with advance demand information and stationary problem data. Numerical studies demonstrate that the IBN policy outperforms on average the NBN policy over all tested instances when their optimality conditions are violated.     

Studies of optimal ordering policies for perishable commodities

Abstract

Problems associated with perishable or outdating products arise in many areas of inventory and production man agement. Many commodities exist whose value does not remain constant over time during transportation, holding stock, etc. Significant work has been done to describe optimal ordering policies for items which have a fixed lifetime. In this paper, per ishable inventory models subject to stochastic procurement leadtinie both on LIFO (Last In First Out) and FIFO (First In First Out) issuing policies are considered with cither zero or 1 unit leadtinie. First, assumptions and notation used throughout the paper are given. FIFO and LIFO models are then con structed, and the existence of the optimal ordering policies and theirpropertiesare clarified. Finally, significantresults are illustrated for the relationship among inventory on hand, delay probability of procurement and optimal ordering policies.     

一类供应链中多产品的订购策略及实证研究

本文针对变质产品供应链,建立了多产品的库存模型,分析了基于五种不同订购策略下总成本函数的性质,提出了多种变质商吕的近似最优订购策略.并且运用本文的理论,对南京市某花卉礼品公司2004年9月的鲜切花订购决策进行了实证分析.     

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 Comparison of Three Joint Ordering Inventory Policies*

This paper evaluates the performance of a joint ordering inventory policy which was first suggested and characterized by Renberg and Planche [14]. This paper shows that the policy is easily characterized for Poisson demands. This policy is then compared with two other joint ordering policies—the well-known (S, c, s) or can-order policy of Balintfy [3] and the recent periodic policies suggested by Atkins and lyogun [2]. For a continuous review operating environment, the Renberg and Planche policy utilizes a group reorder point and a combined order quantity (Q), with each item maintaining an order-up-to level (S). For the can-order policy, each item in the product group has a must-order point (s), a can-order point (c) and an order-up-to level (S). The periodic policies require that item orders be grouped at some fixed scheduled intervals. Using long-run total average costs as the basis, it is shown that no one policy is superior to the others in all the examples tested. In some cases, the Renberg and Planche policy performs surprisingly well.     

The disassembly line: balancing and modeling,by S.M. McGovern and S.M. Gupta

This note addresses a problem faced by an actual firm. The problem is to decide on the optimal level of product quality. In performing the economic analysis to determine product quality level, the firm considers revenue, production costs, and research and development costs. However, this note shows that ignoring inventory costs in the analysis will lead to suboptimal product quality levels. Also, including inventory costs in the analysis will lead to reduced production lot sizes. Numerical examples are used to illustrate the results of the model.     

An inventory model with lot-size dependent ordering cost

The classical Harris - Wilson inventory model assumes that the ordering cost is constant and does not depend on the quantity ordered. There are, however, many practical situations where this is not true. This paper considers an inventory model where the ordering cost depends on the size of the lot and increases in steps as the lot size increases. An algorithm is developed to determine the economic order quantity and is illustrated by a numerical example.     

Impact of Retailers with Knowledge of Supplier's Inventory on Supply Chain Performance

We model a supply chain consisting of a supplier and multiple retailers facing deterministic demand. We denote some retailers as strategic in the sense that given the supplier inventory information, they will implement the optimal stocking policy by incorporating such information. On the other hand, some retailers are denoted as naïve in the sense that they ignore supply information and resort to a simplistic ordering policy. Naïve retailers learn the optimal policy over time and adjust their orders accordingly. We study the dynamics of this game and investigate the impact of such strategic and naïve retailers on the cost, ordering pattern and stocking policies of all parties. We analyze the supply chain under two scenarios: the centralized supply chain where the objective is to minimize the total supply chain cost, and the decentralized supply chain where each self‐interested player minimizes its own cost in a Stackelberg game setting. We fully characterize the optimal policies under both centralized and decentralized scenarios and show that, surprisingly, the supply chain might be better off by virtue of naïve retailers. The result is driven by the fact that strategic and naïve players’ decisions shift the positioning of inventory in the supply chain with its final impact being determined by the relative costs of different retailer‐types. Our results also offer managerial insights into how access to supply information can improve supply chain performance.     

A partial backordering approach to inventory control

We study the effects of using a partial backordering approach to controlling inventories under deterministic and stochastic demands, respectively. With a deterministic demand, our model is built with the objective of minimizing the total cost of ordering, holding, backordering and lost sales. The conditions for the partial backordering policy to be feasible are identified and a pair-wise comparison among the no-backordering, complete backordering, and partial backordering doctrines is conducted. In the stochastic case, we focus on a make-to-stock system with a Poisson demand and exponential production time, which allows us to establish a queuing model to examine the cost-effectiveness of using partial backorders. The conditions under which the partial backordering policy outperforms the complete backordering policy are identified.     

An EOQ model with deteriorating items in response to a temporary sale price

In economic order quantity models, it is often assumed that the unit purchase cost is constant. Such an assumption is usually not fulfilled in many practical situations. In practice, it is observed that suppliers sometimes offer temporary price discounts to stimulate demand, boost market share or decrease inventories of certain items. In this paper, a deteriorating inventory model with a temporary sale price has been developed. We shall be concerned with finding the optimal total cost saving for deteriorating items during the special replenishment period. Numerical examples are presented to illustrate the proposed model.     

Sourcing from Multiple Suppliers for Price‐Dependent Demands

We analyze a model that integrates demand shaping via dynamic pricing and risk mitigation via supply diversification. The firm under consideration replenishes a certain product from a set of capacitated suppliers for a price‐dependent demand in each period. Under deterministic capacities, we derive a multilevel base stock list price policy and establish the optimality of cost‐based supplier selection, that is, ordering from a cheaper source before more expensive ones. With general random capacities, however, neither result holds. While it is optimal to price low for a high inventory level, the optimal order quantities are not monotone with respect to the inventory level. In general, a near reorder‐point policy should be followed. Specifically, there is a reorder point for each supplier such that no order is issued to him when the inventory level is above this point and a positive order is placed almost everywhere when the inventory level is below this point. Under this policy, it may be profitable to order exclusively from the most expensive source. We characterize conditions under which a strict reorder‐point policy and a cost‐based supplier‐selection criterion become optimal. Moreover, we quantify the benefit from dynamic pricing, as opposed to static pricing, and the benefit from multiple sourcing, as opposed to single sourcing. We show that these two strategies exhibit a substitutable relationship. Dynamic pricing is less effective under multiple sourcing than under single sourcing, and supplier diversification is less valuable with price adjustments than without. Under limited supply, dynamic pricing yields a robust, long‐term profit improvement. The value of supply diversification, in contrast, mainly comes from added capacities and is most significant in the short run.     

EOQ-based inventory management in single-machine multi-item systems

The present paper proposes an approach for including the finite capacity constraint in the EOQ model (and, in more general terms, in inventory systems) to study the context of single-machine multi-item systems. In particular, the proposed approach regulates the processing of different items by a shared resource according to a control model based on an ordering policy that combines the Economic Order Quantity with a policy based on minimum and maximum inventory levels (min–max policy). To achieve such a challenging result, the present work exploits the analogy between “switched arrival systems” (a particular class of hybrid systems) and min-max inventory systems. The development and parameterization of the abovementioned control model, therefore, refers to switched arrival systems control theory and mixed-integer linear programming. The present work also contributes to the integration of static tools (i.e., the EOQ model) and control tools, approaching these areas. The paper concludes with a real case application that illustrates the proposed approach and allows for a future research path to be drawn.