Note on Linear Programming: A Brief Overview

by: Roman Kapuscinski

Publication Date: November 16, 2012
Length: 4 pages
Product ID#: 1-429-307

Core Disciplines: Operations Management/Supply Chain

Partner Collection:

Available Documents

Click on any button below to view the available document.

Don't see the document you need? Don't See the Document You Need?
Make sure you are registered and/or logged in to our site to view product documents. Once registered & approved, faculty, staff, & course aggregators will have access to full inspection copies and teaching notes for any of our materials.


Need to make copies?

If you need to make copies, you MUST purchase the corresponding number of permissions, and you must own a single copy of the product.

Electronic Downloads are available immediately after purchase. "Quantity" reflects the number of copies you intend to use. Unauthorized distribution of these files is prohibited pursuant to term of use of this website.

Teaching Note

This product does not have a teaching note.


In some situations, the available resources are adequate to carry out the alternative operating plan selected. In others, however, this is not true. For example, a machine has only a certain amount of capacity. If that capacity is entirely used by one product, it cannot be used for another. Similarly, a factory building has room for only so many machines. In these situations, there are constraints on the uses of resources. Linear programming is a model for solving problems that involve several constraints. In it, a series of linear mathematical relationships is developed. The first, called the objective function, is the quantity to be optimized. This is usually a formula for differential costs, which the model will minimize, or one for differential income, which is to be maximized. The other statements express the constraints of the situation.

Teaching Objectives

After reading and discussing the material, students should:

  • Use linear programming to determine constraints.
  • Identify areas of highest contribution.
  • Calculate a shadow price for each constrained resource.