Two Applications of Integer Programming

The purpose of this course is to develop mathematical, modeling, and computational skills for optimization. The emphasis in this video is modeling.

This video introduces two common and powerful techniques for solving problems that involve mixed integer linear programming (MILP). The first is conversion of a nonlinear constrained optimization problem into a MILP by piecewise linear approximation. As a result of the conversion, the original problem can be approximately solved to global optimality. The second is the introduction of binary variables to solve chance constrained optimization problems. As a result, problems involving probabilistic constraints can be solved to global optimality.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s