16 research outputs found
A Still Simpler Way of Introducing the Interior-Point Method for Linear Programming
Linear programming is now included in algorithm undergraduate and
postgraduate courses for computer science majors. We give a self-contained
treatment of an interior-point method which is particularly tailored to the
typical mathematical background of CS students. In particular, only limited
knowledge of linear algebra and calculus is assumed.Comment: Updates and replaces arXiv:1412.065
An infeasible interior-point method for the -matrix linear complementarity‎ ‎problem based on a trigonometric kernel function with full-Newton‎ ‎step
An infeasible interior-point algorithm for solving the‎
‎-matrix linear complementarity problem based on a kernel‎
‎function with trigonometric barrier term is analyzed‎. ‎Each (main)‎
‎iteration of the algorithm consists of a feasibility step and‎
‎several centrality steps‎, ‎whose feasibility step is induced by a‎
‎trigonometric kernel function‎. ‎The complexity result coincides with‎
‎the best result for infeasible interior-point methods for‎
‎-matrix linear complementarity problem
An Improved and Simplified Full-Newton Step Infeasible Interior-Point Method for Linear Optimization
Convergence of infeasible-interior-point methods for self-scaled conic programming
Convergence of infeasible-interior-point methods for self-scaled conic programmin