On finding a vertex solution using interior point methods

On the Solution to the Nonlinear Resource Allocation Problem Using Variable Fixing and Interior-Point Methods

2 Methods 2 2.1 Lagrange Multiplier Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 Pegging Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.3 Interior-Point Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3.1 Optimality Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3.2 Interior-Point Algorithm ....

Interior-point Methods

Interior-Point Methods

The modern era of interior-point methods dates to 1984, when Karmarkar proposed his algorithm for linear programming. In the years since then, algorithms and software for linear programming have become quite sophisticated, while extensions to more general classes of problems, such as convex quadratic programming, semide nite programming, and nonconvex and nonlinear problems, have reached varyin...

Interior Point Methods

In this section we will give an (extremely) brief Introduction to the concept of interior point methods • Logarithmic Barrier Method • Method of Centers We have previously seen methods that follow a path On the boundary of the feasible region (Simplex). As the name suggest, interior point methods instead Follow a path through the interior of the feasible region.

Efficient solution of two-stage stochastic linear programs using interior point methods

Solving deterministic equivalent formulations of two-stage stochastic linear programs using interior point methods may be computationally diflicult due to the need to factorize quite dense search direction matrices (e.g., AAT). Several methods for improving the algorithmic efficiency of interior point algorithms by reducing the density of these matrices have been proposed in the literature. Ref...