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 the simplest to code into a mathematical program. We will work with interior point methods to investigate the algorithmic details of constrained optimization.
- A. Wächter 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 a project scope.
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