Stock Allocation in a Two-Echelon Distribution System Or “What to Do Until Your Ship Comes In”

Jackson, Peter L.

doi:10.1287/mnsc.34.7.880

Cited by 151 publications

(68 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But the issue remains as to how to set the service levels. The literature on multiechelon distribution systems (e.g., Jackson 1988, Schwarz 1989, Graves 1995 suggests that, from a system perspective, it often may be better to have low levels of internal service.…”

Section: Discussionmentioning

confidence: 99%

A Dynamic Model for Requirements Planning with Application to Supply Chain Optimization

Graves

Kletter

Hetzel

1998

Operations Research

171

110

View full text Add to dashboard Cite

This paper develops a new model for studying requirements planning in multistage production-inventory systems. We first characterize how most industrial planning systems work, and we then develop a mathematical model to capture some of the key dynamics in the planning process. Our approach is to use a model for a single production stage as a building block for modeling a network of stages. We show how to analyze the single-stage model to determine the production smoothness and stability for a production stage and the inventory requirements. We also show how to optimize the tradeoff between production capacity and inventory for a single stage. We then can model the multistage supply chain using the single stage as a building block. We illustrate the multistage model with an industrial application, and we conclude with some thoughts on a research agenda.M ost discrete parts manufacturing firms plan their production with MRP (materials requirements planning) systems, or at least, with logic based on the underlying assumptions of MRP. A typical planning system starts with a multiperiod forecast of demand for each finished good or end item. The planning system then develops a production plan (or master schedule) for each end item to meet the demand forecast. These production plans for the end items, after offsetting for lead times, then act as the requirement forecasts for the components needed to produce the end items. The requirements forecast for each component gets translated into production plans for the component, similar to how the production plan for the end items was created. The planning system continues in this way, developing requirement forecasts and production plans for each level of the bill of materials.Implicit in this planning process are assumptions about the production and demand process. The production plan is developed assuming that the forecast is accurate and will not change. Within the production process, requirements are generated assuming that there are deterministic production lead times and deterministic yields. Needless to say, these assumptions of a benevolent world do not match reality. Inevitably, the forecast changes, and uncertainties in the production process arise that result in deviations from the plan. To respond to these changes, most planning systems will completely revise their plan after some time period, say a week or a month. Again, the planning process starts with the (new) forecast and repeats the steps necessary to regenerate a plan for each level in the products' bills of materials.The intent of this paper is to present a model that captures the basic flavor of this planning process, and does so in such a way that it can be used to look at various tradeoffs within the production and planning systems. In particular, we model the forecasts for the planning system as a stochastic process. In this way, we try to represent a dynamic input to the planning system, namely, how forecasts change and evolve over time. The forecast process is a key input for the model. Another key...

show abstract

Section: Discussionmentioning

confidence: 99%

A Dynamic Model for Requirements Planning with Application to Supply Chain Optimization

Graves

Kletter

Hetzel

1998

Operations Research

171

110

View full text Add to dashboard Cite

show abstract

“…Eppen and Schrage (1981) use the balance assumption for a distribution system with a stockless warehouse and normally distributed end customer demands. Jackson (1988) extends this work to allow storing inventory at the warehouse. Axsater (2003) reviews the literature related to the balance assumption.…”

Section: Positioning and Literature Reviewmentioning

confidence: 89%

Linear programming based decomposition methods for inventory distribution systems

Kunnumkal

Topaloğlu

2011

European Journal of Operational Research

View full text Add to dashboard Cite

We consider an inventory distribution system consisting of one warehouse and multiple retailers. The retailers face random demand and are supplied by the warehouse. The warehouse replenishes its stock from an external supplier. The objective is to minimize the total expected replenishment, holding and backlogging cost over a finite planning horizon. The problem can be formulated as a dynamic program, but this dynamic program is difficult to solve due to its high dimensional state variable. It has been observed in the earlier literature that if the warehouse is allowed to ship negative quantities to the retailers, then the problem decomposes by the locations. One way to exploit this observation is to relax the constraints that ensure the nonnegativity of the shipments to the retailers by associating Lagrange multipliers with them, which naturally raises the question of how to choose a good set of Lagrange multipliers. In this paper, we propose efficient methods that choose a good set of Lagrange multipliers by solving linear programming approximations to the inventory distribution problem. Computational experiments indicate that the inventory replenishment policies obtained by our approach can outperform several standard benchmarks by significant margins.

show abstract

“…One exception is in serial systems, where Clark and Scarf (1960) gave the form of the optimal policy. Others such as , Jackson (1988), andGraves (1996) propose heuristics for the periodic review case. Authors who consider continuous review (R,Q)-type policies in the multi-echelon setting include Sherbrooke (1968), Deuermeyer and Schwarz (1981), Graves (1985), Moinzadeh and Lee (1986), Lee and Moinzadeh (1987), Svoronos & Zipkin (1988), and Axsater (1993).…”

Section: Related Literaturementioning

confidence: 99%

Network Server Supply Chain at HP: A Case Study

Beyer

Ward

2002

International Series in Operations Research &Amp; Management Science

View full text Add to dashboard Cite

inventory management, supply chain management, stocking policies This chapter describes an inventory management project conducted at Hewlett-Packard Laboratories for HP's Network Server Division (NSD). NSD manufactures a major subassembly of network servers in Singapore and ships it to four distribution centers (DCs) worldwide, where the assembly is completed due to customer specifications. Two modes of transportation are available (air and ocean) between the factory and DCs, and customer demand at the DCs is stochastic and non-stationary. The project goal was to compute inventory policies that reduce inventory-and shipment-related costs for this subassembly by enabling more cost-effective use of ocean shipments, all without compromising order fulfillment. We discuss the challenges this project presented within the context of recent trends in supply chain management. We also describe the approach developed at HP Laboratories, as well as qualitative and quantitative results from its implementation. Abstract: This chapter describes an inventory management project conducted at Hewlett-Packard Laboratories for HP's Network Server Division (NSD). NSD manufactures a major subassembly of network servers in Singapore and ships it to four distribution centers (DCs) worldwide, where the assembly is completed due to customer specifications. Two modes of transportation are available (air and ocean) between the factory and DCs, and customer demand at the DCs is stochastic and non-stationary. The project goal was to compute inventory policies that reduce inventory-and shipment-related costs for this subassembly by enabling more cost-effective use of ocean shipments, all without compromising order fulfillment. We discuss the challenges this project presented within the context of recent trends in supply chain management. We also describe the approach developed at HP Laboratories, as well as qualitative and quantitative results from its implementation.

show abstract

Stock Allocation in a Two-Echelon Distribution System Or “What to Do Until Your Ship Comes In”

Cited by 151 publications

References 12 publications

A Dynamic Model for Requirements Planning with Application to Supply Chain Optimization

A Dynamic Model for Requirements Planning with Application to Supply Chain Optimization

Linear programming based decomposition methods for inventory distribution systems

Network Server Supply Chain at HP: A Case Study

Contact Info

Product

Resources

About