In this paper we consider a linear programming problem with the underlying matrix unimodular, and the other data integer. Given arbitrary near optimum feasible solutions to the primal and the dual problems, we obtain conditions under which statements can be made about the value of certain variables in optimal vertices. Such results have applications to the problem of determining the stopping cr...

SDPA (SemiDe nite Programming Algorithm) is a C++ implementation of a Mehrotra-type primal-dual predictor-corrector interior-point method for solving the standard form semide nite program and its dual. We report numerical results of large scale problems to evaluate its performance, and investigate how major time-consuming parts of SDPA vary with the problem size, the number of constraints and t...

Here we present an implementation of Primal-Dual Affine scaling method to solve linear optimisation problem on GPU based systems. Strategies to convert the system generated by complementary slackness theorem into a symmetric system are given. A new CUDA friendly technique to solve the resulting symmetric positive definite subsystem is also developed. Various strategies to reduce the memory tran...

We present a quadratic Discrete-time Optimal Control problem generator, written in C, with options for Degeneracy, Activity and Conditioning (DOCDAC). We use the generator to investigate badly conditioned and degenerate extended linear-quadratic problems (ELQPs) by solving such problems with primal-dual projected gradient and interior-point methods. The benefit of using second-order information...

We discuss a possibility of the extension of a primal-dual interior-point algorithm suggested recently in 1]. We consider optimization problems deened on the intersection of a symmetric cone and an aane subspace. The question of solvability of a linear system arising in the implementation of the primal-dual algorithm is analyzed. A nondegeneracy theory for the considered class of problems is de...

In this paper, the filter technique of Fletcher and Leyffer (1997) is used to globalize the primaldual interior-point algorithm for nonlinear programming, avoiding the use of merit functions and the updating of penalty parameters. The new algorithm decomposes the primal-dual step obtained from the perturbed first-order necessary conditions into a normal and a tangential step, whose sizes are co...

This paper presents linear algebra techniques used in the implementation of an interior point method for solving linear programs and convex quadratic programs with linear constraints. New regularization techniques for Newton systems applicable to both symmetric positive de nite and symmetric inde nite systems are described. They transform the latter to quaside nite systems known to be strongly ...

Recently much attention was paid to polynomial interior point methods, almost exclusively based on the logarithmic barrier function. Some attempts were made to prove polynomiality of other barrier methods (e.g. the inverse barrier method) but without success. Other interior point methods could be de ned based on CES-functions (CES is the abbreviation of Constant Elasticity of Substitution). The...