Interior point methods or barrier methods are a certain class of algorithms to solve linear and nonlinear convex optimization problems. Violation of inequality constraints are prevented by augmenting the objective function with a barrier term that causes the optimal unconstrained value to be in the feasible space.

Interior point methods are best suited for very large-scale problems with many degrees of freedom (design variables). Interior point methods are also relatively simple to code into a mathematical program. We will work with interior point methods to investigate the algorithmic details of constrained optimization.

  1. A. W├Ąchter and L. T. Biegler, On the Implementation of an Interior-Point Filter Line-Search Algorithm for Large-Scale Nonlinear Programming, Mathematical Programming 106(1), pp. 25-57, 2006. Download PDF

The difficulty of the last few assignments has been reduced to allow time for work on the Final Project. Please use the additional time this week to develop your project.


Interior Point Homework

Two exercises involve setting up and solving nonlinear programming problems with the interior point method.


The following animations demonstrate how the barrier term influences the objective contours. As the value of the barrier term (mu) decreases, the contours of the barrier problem approach the original objective contours.



This assignment can be completed in groups of two. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.

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