Inventory Replenishment Decisions Research Articles

A simulation-optimization approach for integrated sourcing and inventory decisions

In this paper, we study a generalized vendor selection problem that integrates vendor selection and inventory replenishment decisions of a firm. In addition to vendor-specific procurement and management costs, we consider inventory replenishment, holding, and backorder costs explicitly to meet stationary stochastic demand faced by the firm. Our goal is to select the best set of vendors along with the optimum inventory decisions at each plant of the firm so that we minimize the system-wide total costs and achieve desired service and reliability levels. Due to uncertainties inherent in the problem related to demand observed by the firm, quality provided by vendors, and disruptions observed by vendors, we utilize a simulation-optimization approach to solve the problem. More specifically, we build a discrete-event simulation model to evaluate the objective function of the problem that works in concert with a scatter search-based metaheuristic optimization approach to search the solution space. Computational results not only provide managerial insights and measure the significance of intangible factors in the vendor selection process but also highlight the importance of computational tools such as simulation-optimization for the vendor selection problem.

Estimating freight rates in inventory replenishment and supplier selection decisions

Given the impact of transportation costs on both supplier selection and inventory replenishment decisions in today’s enterprises, this article addresses both problems simultaneously by proposing a mixed integer nonlinear programming model to properly allocate order quantities to the selected set of suppliers while taking into account the purchasing, holding and transportation costs under suppliers’ capacity and quality constraints. It is shown that incorporating transportation costs in the process of selecting suppliers and establishing an inventory policy, not only affects the order quantity shipped from selected suppliers, but also the actual selection of suppliers. Because of the difficulty that arises when working with actual transportation freight rates in large-scale problems, two continuous functions that estimate actual freight rates are analyzed. It is shown that the use of these functions is very practical and easy to implement.

Note—Pricing and Inventory Control for a Perishable Product

In this note, we study the concurrent determination of pricing and inventory replenishment decisions for a perishable product in an infinite horizon. Demands in consecutive periods are independent and influenced by prices charged in each period. In particular, we treat price as a decision variable to maximize the total discounted profit. We analyze the optimal solution-structure of a two-period lifetime problem and from insights gained in numerical experiments, develop a base-stock/list-price heuristic policy for products with arbitrary fixed lifetimes. Experiments show this policy to be effective.

Stocking policy in a two-party vendor managed channel with space restrictions

In a two-party VMI channel, the vendor operates the basic stocking and delivery functions and makes inventory replenishment decisions while the retailer is responsible for customer acquisition and in-store services. This paper focuses on such retail channel and proposes an analytical model for the partners in supply channel to determine the inventory policy with the objective of optimizing system net profit. The model explicitly incorporates issues from both the vendor and the retailer in order to derive a policy for mutual benefits. To illustrate and obtain insights from the proposed solution procedure, we devise a set of numerical analyses based on various scenarios. Factors such as shelf-space-dependent demand, shelf-space capacity, demand pattern, logistics characteristics, and disparity between holding costs of the warehouse and the retail store are also investigated.

Order Progress Information: Improved Dynamic Emergency Ordering Policies

Technologies such as radio‐frequency identification and global positioning systems can provide improved real‐time tracking information for products and replenishment orders along the supply chain. We call this type of visibility order progress information. In this paper, we investigate how order progress information can be used to improve inventory replenishment decisions. To this end, we examine a retailer facing a stochastic lead time for order fulfillment. We characterize a replenishment policy that is based on the classical ( Q, R) policy and that allows for releasing emergency orders in response to the order progress information. We show that the optimal structure of this policy is given by a sequence of threshold values dependent on order progress information. In a numerical study we evaluate the cost savings due to this improved replenishment policy.

A duality‐based relaxation and decomposition approach for inventory distribution systems

AbstractWe propose a new method for making the inventory replenishment decisions in distribution systems. In particular, we consider distribution systems consisting of multiple retailers that face random demand and a warehouse that supplies the retailers. The method that we propose is based on formulating the distribution problem as a dynamic program, and relaxing the constraints that ensure the nonnegativity of the shipments to the retailers, by associating Lagrange multipliers with them. We show that our method provides lower bounds on the value functions, and a good set of values for the Lagrange multipliers can be obtained by maximizing a concave function in a relatively straightforward manner. Computational experiments indicate that our method can provide significant improvements over the traditional approaches for making the inventory replenishment decisions, in terms of both the tightness of the lower bounds on the value functions and the performance of the policies. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008

Integrated warehouse location and inventory decisions in a three-tier distribution system

A three-tier distribution network which consists of a single supplier at a given location, a single intermediate warehouse whose location is to be determined, and multiple retailers at given locations is examined. The problem is the integration of warehouse location and inventory replenishment decisions with the objective of minimizing the system-wide transportation and inventory-related costs. The case where the inventory replenishment decisions are coordinated using a power-of-two policy is considered and a mathematical model for the simultaneous computation of the warehouse coordinates and coordinated replenishment policy parameters is developed. The analytical properties of the integrated location-inventory model are characterized and efficient solution methods that rely on these properties are developed. Computational results demonstrating the performance of the proposed heuristic methods and the potential practical impact of integrated decision making for location and inventory decisions are reported. These results indicate that the proposed methods are capable of effectively producing high-quality power-of-two solutions within 6% of the lower bound for the instances tested. The presented analysis is also useful for identifying: (i) the level of interaction between these two types of decisions that are treated separately in the traditional literature; and (ii) problem settings where the integrated location–inventory model offers significant cost savings.

Contracting Under Vendor Managed Inventory Systems Using Holding Cost Subsidies

Vendor managed inventory systems are becoming increasingly popular. An important issue in implementing a vendor managed inventory scheme is the contracting terms that dictate the ownership of the inventory and the responsibility of inventory replenishment decisions. Thus the performance of a vendor managed system crucially depends on these terms and on how inventory‐related costs are shared in a supply chain. We consider a system where a manufacturer supplies a single product to a retailer who faces random demand in a competitive market. The retailer incurs a fixed cost per order, inventory holding cost, and a penalty cost for a stockout (unsatisfied demand is back‐ordered). Further, the manufacturer incurs a penalty cost when there is a stockout at the retailer and a fixed replenishment cost. We assume that the players are rational and act noncooperatively. We compare the performance of retailer managed inventory systems, where the retailer places orders and makes replenishment decisions, with vendor managed inventory systems, wherein the vendor or manufacturer makes inventory and replenishment decisions. Specifically, in the vendor managed inventory system, we propose and evaluate holding cost subsidy‐type contracts on inventories offered by the retailer to improve system performance. We evaluate this contract in the context of three widely used inventory systems—deterministic economic order quantity, continuous review ( Q, r) policies, and periodic review policies—and show when such contracts may improve channel performance.

Inventory Management for Customers with Alternative Lead Times

This paper considers a multiperiod inventory model in which a supplier provides alternative lead-time choices to customers: a short or a long lead time. The supplier operates in a batch-production mode. Orders from slow customers can be taken by the supplier and included in the next production cycle, while orders from fast customers have to be satisfied from the onhand inventory. We denote the action of providing a short lead-time product to a long lead-time customer as the inventory-commitment decision, and we also denote the initial inventory stocking as the inventory-replenishment decision. We first characterize the optimal inventory-commitment policy. We then prove that the optimal inventory-replenishment policy is a base-stock type. We extend our analysis to models to consider a multicycle setting, a case of a supply capacity constraint, and a case in which the inventory holding cost is charged in real time. We also compare the performances of the optimal inventory-commitment policy and the inventory-rationing policy. Finally, we use the customer-choice model to characterize the demand-induction and demand-cannibalization effects.

A stochastic model for joint inventory and outbound shipment decisions

In this paper, we consider a vendor realizing a sequence of random order arrivals in random sizes. The vendor has the autonomy to hold/consolidate small orders until an economical dispatch quantity accumulates. Consequently, the actual inventory requirements at the vendor are in part determined by the parameters of the shipment release policy in use. In this context, we investigate the impact of shipment consolidation on the expected long-run average cost by simultaneously computing the optimal order quantity for inventory replenishment at the vendor and the optimal dispatch quantity for outbound shipments. Since we consider the case where demand follows a general stochastic bulk arrival process, obtaining exact analytical expressions for some key operating characteristics of the cost function is intractable. Hence, we provide easy-to-compute approximations which enable efficient numerical solutions for the problem. We also investigate: (i) the cases where consolidated shipments are preferred over immediate deliveries; (ii) the sensitivity of optimal integrated policy variables to demand/cost parameters; (iii) the potential savings that can be obtained by shipment consolidation; and (iv) the tradeoffs between the waiting time induced by shipment consolidation and costs saved. Our results provide insights into the impact of outbound transportation operations on inventory replenishment decisions and outbound distribution system design. Moreover, numerical testing suggests that significant cost savings (up to 57%) are possible with shipment consolidation.

Inventory control of perishables in supermarkets

In the last decade large supermarket chains have started developing and implementing automated store ordering (ASO) systems in order to improve both the quality and efficiency of the inventory replenishment decisions in their stores. These ASO systems have been developed mainly for non-perishables. The aims of this paper are 1. to better understand the product, sales and supply characteristics of perishables in supermarkets, 2. to define and operationalise relevant concepts in controlling the inventories of perishables, 3. to investigate how the intelligence in ASO systems in supermarkets can be further improved, 4. to give academics empirically based insight in the relevance of the inventory models that are currently available in the literature, insight in relevant parameter settings and insight in which models are needed. The research is carried out in cooperation with two Dutch supermarket chains and focusses on perishable items. To further improve the intelligence in the ASO systems, we will classify the items in a supermarket, based on the notion that different items need different inventory control rules. For every class of items, we describe the main logistic characteristics; moreover, for the perishable items we describe the inventory control rules which are currently being applied and we discuss the desired inventory control strategy for these items.

The impact of forecasting model selection on the value of information sharing in a supply chain

This paper presents a study on the impact of forecasting model selection on the value of information sharing in a supply chain with one capacitated supplier and multiple retailers. Using a computer simulation model, this study examines demand forecasting and inventory replenishment decisions by the retailers, and production decisions by the supplier under different demand patterns and capacity tightness. Analyses of the simulation output indicate that the selection of the forecasting model significantly influences the performance of the supply chain and the value of information sharing. Furthermore, demand patterns faced by retailers and capacity tightness faced by the supplier also significantly influence the value of information sharing. The result also shows that substantial cost savings can be realized through information sharing and thus help to motivate trading partners to share information in the supply chain. The findings can also help supply chain managers select suitable forecasting models to improve supply chain performance.

The impact of information sharing and ordering co‐ordination on supply chain performance

This paper presents a study on the impacts of information sharing and ordering co‐ordination on the performance of a supply chain with one capacitated supplier and multiple retailers under demand uncertainty. In particular, a computer model is proposed to simulate inventory replenishment decisions by the retailers and production decisions by the supplier under different demand patterns and capacity tightness. It is found that information sharing and ordering co‐ordination significantly impact the supply chain performance in terms of both total cost and service level. It is also found that the value of sharing information and ordering co‐ordination is significantly affected by demand patterns and capacity tightness. Guidelines are developed for companies to share information and co‐ordinate orders under different conditions. These guidelines can help companies reduce costs and improve customer service levels in the supply chain.

Incorporating transportation costs into inventory replenishment decisions

Dating to the origination of economic order quantity (EOQ) models, the objective of inventory replenishment decisions has centered on the minimization of total annual logistics cost. Accurate solutions require that all relevant costs be appropriately incorporated into the total annual logistics cost function to determine purchase quantities. Depending on the estimates used, upwards of 50% of the total annual logistics cost of a product can be attributed to transportation. Any consideration of purchase quantities should therefore consider transportation costs. To appropriately incorporate transportation cost into the total annual logistics cost function, it must first be possible to identify transportation cost functions that emulate reality and simultaneously provide a straightforward representation of actual freight rates. This study demonstrates that straightforward freight rate functions presented in the literature can be incorporated into inventory replenishment decisions without compromising the accuracy of the decision. Equally important, these functions can be incorporated without adding undue complexity to the decision process.

Investing in ordering cost reduction for integrated inventory systems

In this paper, we investigate an integrated inventory system where a single vendor purchases and processes raw materials in oreler to deliver finished items to multiple buyers. The vendor and all buyers jointly invest in reducing the ordering cost (e.g., establishing electronic data interchange based ordering systems) to decrease their joint total cost. The amount of investment determines the planned ordering cost and hence affects their inventory replenishment decisions. An analytical model is developed to decide the optimal investment amount and lot sizes for both vendor and buyers. In addition, we apply an exponential ordering cost function to our general model to provide interesting insights of the model. Numerical results show that the integrated inventory system can benefit substantially from this ordering cost reduction investment.

Improving the supply chain performance: Use of forecasting models versus early order commitments

This paper evaluates the impact of forecasting models and early order commitment in a supply chain with one capacitated manufacturer and four retailers under demand uncertainty. Computer simulation models were used to simulate different demand forecasting and inventory replenishment decisions by the retailers as well as production decisions by the manufacturer under a variety of demand patterns and capacity tightness scenarios. This study found that early order commitments significantly affected the total costs and service levels, to various degrees, for the manufacturer and the retailers, suggesting that the benefits of early order commitment could be influenced by a combination of forecasting models, demand patterns and capacity tightness.

An Evaluation of Proactive vs. Reactive Replenishment Systems

Traditional inventory replenishment decisions in distribution systems have been reactive, but the availability of information throughout the distribution system means that other methods should be considered.

A Simple Inventory Replenishment Decision Rule for a Linear Trend in Demand

A Simple Inventory Replenishment Decision Rule for a Linear Trend in Demand

A Simple Inventory Replenishment Decision Rule for a Linear Trend in Demand

We consider the situation of a deterministic demand pattern having a linear trend. The problem is to select the timing and sizes of replenishments so as to keep the total of replenishment and carrying costs as low as possible. An earlier developed heuristic for the general case of a deterministic, time-varying, demand pattern is specialized to the case of a linear trend. The simple decision rule is shown to lead to small cost penalties in two examples that have been exactly analyzed in an earlier article in this journal.