In the previous chapter we introduced MAUT as a decision modeling technique that focus on problems with a discrete number of alternatives. In this chapter, we will discuss Linear Programming (LP) as a technique to model decision problems with a continuous number of alternatives. Linear Programming is most useful when chosing for the best possible option given a list of resource constraints that can be described as linear functions of the decision alternatives. Given that the emphasis of this mathematical technique is on the best possible option, LP is an optimization technique.

The chapter begins with a warming up exercise, followed by a core introduction to main concepts of linear programing, followed by examples of problems that can be solved using linear programming. The chapter will end with additional practice problems.

Attribution

By Luis F. Luna-Reyes, Erika Martin and Mikhail Ivonchyk, and licensed under  CC BY-NC-SA 4.0.