Capacitated Supply Research Articles

Optimal Stock Allocation for a Capacitated Supply System

We consider a capacitated supply system that produces a single item that is demanded by several classes of customers. Each customer class may have a different backorder cost, so stock allocation arises as a key decision problem. We model the supply system as a multi customer make-to-stock queue. Using dynamic programming, we show that the optimal allocation policy has a simple and intuitive structure. In addition, we present an efficient algorithm to compute the parameters of this optimal allocation policy. Finally, for a typical supply chain design problem, we illustrate that ignoring the stock allocation dimension—a frequently encountered simplifying assumption—can lead to incorrect managerial decisions.

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.

Information Flows in Capacitated Supply Chains with Fixed Ordering Costs

Many organizations have only recently recognized that sharing information with other members in their supply chain can lead to signficant reduction in the total costs.Usually these information flows are incorporated into existing operating policies at the various parties.In this paper we argue that, in some cases, it may be necessary to change the way the supply chain is managed to make complete use of the information flows. We support this argument by analyzing a supply chain containing a capacitated supplier and a retailer facing i.i.d. demands. In addition there are fixed ordering costs between the retailer and the supplier.In this setting, we consider two models: (1) the retailer is using the optimal (s,S) policy and providing the supplier information about her inventory levels; and (2) the retailer, still sharing information on her inventory levels, orders in a period only if by the previous period the cumulative end-customer demand since she last ordered was greater than δ. Thus, in Model 1, information sharing is used to supplement existing policies; while, in Model 2, we have redefined operating policies to make better use of the information flows. We will show, via a detailed computational study, that the total supply chain costs of Model 2 are 10.4% lower, on the average, than that of Model 1. We noticed that this reduction in costs is higher at higher capacities, higher supplier penalty costs, lower retailer penalty costs, moderate values of set-up cost, and at lower end-customer demand variances.

The Impact of Forecast Errors on Early Order Commitment in a Supply Chain*

ABSTRACTSupply chain partnership involves mutual commitments among participating firms. One example is early order commitment, wherein a retailer commits to purchase a fixed‐order quantity and delivery time from a supplier before the real need takes place. This paper explores the value of practicing early order commitment in the supply chain. We investigate the complex interactions between early order commitment and forecast errors by simulating a supply chain with one capacitated supplier and multiple retailers under demand uncertainty. We found that practicing early order commitment can generate significant savings in the supply chain, but the benefits are only valid within a range of order commitment periods. Different components of forecast errors have different cost implications to the supplier and the retailers. The presence of trend in the demand increases the total supply chain cost, but makes early order commitment more appealing. The more retailers sharing the same supplier, the more valuable for the supply chain to practice early order commitment. Except in cases where little capacity cushion is available, our findings are relatively consistent in the environments where cost structure, number of retailers, capacity utilization, and capacity policy are varied.

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.

Channel Strategies and Stocking Policies in Uncapacitated and Capacitated Supply Chains*

ABSTRACTA supply chain consisting of a single supplier distributing two independent products through multiple retailers is analyzed in this paper. The supplier needs to incentivize its retailers to adopt stocking policies that are mutually advantageous and that result in the optimal level of market coverage. The focus is on determining the optimal stocking policies for retailers and the resulting distribution strategy given that the supplier has either unlimited or limited capacity. The results provide insights on the optimal distribution strategy and stocking policies for the supply chain. In general, the paper shows that it is optimal for the supplier to use an intensive distribution strategy (i.e., the products are stocked by all retailers). Selective or exclusive strategies are optimal only when retailers are risk averse, stocking synergies exist, and there are differences in demand or supply uncertainties across products. The analysis also shows that retailers hold larger stocks of a product which generates higher supplier margins but only when the supplier has unlimited capacity. If the supplier has limited capacity, then their margins have no effect on retailers' stocking decisions. Contrary to conventional wisdom, retailers hold larger stocks of a product that has less demand uncertainty as compared to one that has more demand uncertainty.

Benefits of co-operation in a production distribution environment

We model co-operation in a typical production distribution setting that contains one capacitated supplier producing and distributing a single product to many identical retailers who are facing i.i.d. end-item demands from the consumers. We consider three inventory allocation mechanisms, representing varying degrees of co-operation, at the supplier: (1) the orders from the retailers are filled in a predetermined sequence; (2) the orders from the retailers are filled after taking into account their current inventories; and (3) the orders from the retailers are filled assuming that the product can also be shipped from one retailer to another. We estimate the benefits due to co-operation in this supply chain and study the effect of various system parameters on these benefits. An extensive computational study indicated that the benefits of co-operation in this production distribution environment decrease with increase in the supplier capacity, increase in the number of retailers, decrease in penalty cost, and decrease in consumer demand variance.

An efficient heuristic for inventory control when the customer is using a ( s, S) policy

We consider a capacitated supply chain in which the supplier has the information of the ( s, S) policy used by the retailer as well as the end-customer demand distribution. For the resulting inventory control problem at the supplier, optimal policies and structural properties were presented by Gavirneni et al. (Management Sci. 45(1) (1999) 16). They detailed an efficient solution procedure for the uncapacitated problem and resorted to computationally expensive infinitesimal perturbation analysis (IPA) for the capacitated situation. In this paper, we study a heuristic, based on the uncapacitated solution, for the capacitated situation. A detailed computational study showed that this heuristic is very efficient in that the costs increased by only 3.3% on the average. The heuristic was especially effective at higher capacities, lower holding costs, and extreme values of demand variance.

A Heuristic Algorithm for the Capacitated Multiple Supplier Inventory Grouping Problem

A Heuristic Algorithm for the Capacitated Multiple Supplier Inventory Grouping Problem