Interior-point method for LP

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Authors: John Plaxco, Alex Valdes, Wojciech Stojko. (ChE 345 Spring 2014)
Steward: Dajun Yue, Fengqi You
Date Presented: May 25, 2014



Interior point methods are a type of algorithm that are used in solving both linear and nonlinear convex optimization problems that contain inequalities as constraints. The LP Interior-Point method relies on having a linear programming model with the objective function and all constraints being continuous and twice continuously differentiable. The problem is solved (assuming there IS a solution) either by iteratively solving for Karun-Kush-Tucker (KKT) conditions or to the original problem with equality instead of inequality constraints, and then applying Newton's method to these conditions.






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