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EOQ Model

  • John A. Muckstadt
  • Amar Sapra
Chapter
Part of the Springer Series in Operations Research and Financial Engineering book series (ORFE)

Abstract

The first model we will present is called the economic order quantity (EOQ) model. This model is studied first owing to its simplicity. Simplicity and restrictive modeling assumptions usually go together, and the EOQ model is not an exception. However, the presence of these modeling assumptions does not mean that the model cannot be used in practice. There are many situations in which this model will produce good results. For example, these models have been effectively employed in automotive, pharmaceutical, and retail sectors of the economy for many years. Another advantage is that the model gives the optimal solution in closed form. This allows us to gain insights about the behavior of the inventory system. The closed-form solution is also easy to compute (compared to, for example, an iterative method of computation).

In this chapter, we will develop several models for a single-stage system in which we manage inventory of a single item. The purpose of these models is to determine how much to purchase (order quantity) and when to place the order (the reorder point). The common thread across these models is the assumption that demand occurs continuously at a constant and known rate. We begin with the simple model in which all demand is satisfied on time. In Section 2.2, we develop a model in which some of the demand could be backordered. In Section 2.3, we consider the EOQ model again; however, the unit purchasing cost depends on the order size. In the final section, we briefly discuss how to manage many item types when constraints exist that link the lot size decisions across items.

Keywords

Order Quantity Average Inventory Economic Order Quantity Quantity Discount Optimal Order Quantity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.School of Operations Research and Information EngineeringCornell UniversityIthacaUSA
  2. 2.Department of Quantitative Methods and Information SystemsIndian Institute of Management BangaloreBangaloreIndia

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