Chapter 7 Linear Programming Models: Graphical and Computer Methods

Learning Objectives

After completing this chapter, students will be able to:

  1. 7.1 Identify the basic assumptions and properties of linear programming (LP).

  2. 7.2 Formulate a linear programming problem algebraically.

  3. 7.3 Graphically solve any LP problem that has only two variables by both the corner point and the isoprofit line methods.

  4. 7.4 Use Excel spreadsheets to solve LP problems.

  5. 7.5 Understand the difference between minimization and maximization objective functions.

  6. 7.6 Understand special issues in LP such as infeasibility, unboundedness, redundancy, and alternative optimal solutions.

  7. 7.7 Understand the role of sensitivity analysis.

Many management decisions involve trying to make the most effective use of an organization’s resources. Resources typically include machinery, labor, money, time, warehouse space, and raw materials. These resources may be used to make products (such as machinery, furniture, food, or clothing) or services (such as schedules for airlines or production, advertising policies, or investment decisions). Linear programming (LP) is a widely used mathematical modeling technique designed to help managers in planning and decision making relative to resource allocation. We devote this and the next chapter to illustrating how and why linear programming works.

Despite its name, LP and the more general category of techniques called mathematical programming have very little to do with computer programming. In the world of management science, programming refers to modeling and solving a problem mathematically. Computer programming has, of course, played an important role in the advancement and use of LP. Real-life LP problems are too cumbersome to solve by hand or with a calculator. So throughout the chapters on LP, we give examples of how valuable a computer program can be in solving an LP problem.

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