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A primal-infeasible interior point algorithm for linearly constrained convex programming

Yan-jin Wang (wang_jasonyj***at***yahoo.com)
Pu-sheng Fei (wang_jasonyj***at***yahoo.com)

Abstract: In the paper a primal-infeasible interior point algorithm is proposed for linearly constrained convex programming. The starting point is any positive primal-infeasible dual-feasible point in a large region. The method maintains positivity of the iterates which point satisfies primal-infeasible dual-feasible point. At each iterates it requires to solve approximately a nonlinear system. It is shown that, after polynomial iterations a sufficiently good approximation to the optimal point is found, or there is no optimal point in a large nonnegative region.

Keywords:

Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )

Citation:

Download: [PDF]

Entry Submitted: 07/20/2005
Entry Accepted: 07/27/2005
Entry Last Modified: 07/20/2005

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