Interior-point method for LP
Claimed by John Plaxco, Alex Valdes, Wojciech Stojko.
Interior point methods are a type of algorithm that are used in solving both linear and nonlinear convex optimization problems. More specifically, convex optimization problems that contain inequalities as constraints. The Interior-Point method relies on having a linear programming model with the objective function and all constraints being continuous and twice continuously differentiable.
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