We consider the generalization of a variant of Karmarkar's algorithm to semi-infinite programming. The extension of interior point methods to infinite-dimensional linear programming is discussed and an algorithm is derived. An implementation of the algorithm for a class of semi-infinite linear programs is described and the results of a number of test problems are given. We pay particular attent...

We consider a primal interior point algorithm for LP. The method uses a search direction obtained by minimizing the original objective over a linearly transformed section of the circular cone circumscribed around the nonnegative orthant. If the latter problem has a finite solution, it provides a lower bound for the optimal objective and a target point specifying a descent direction. Otherwise, ...

Standard interior-point algorithms usually show a poor performance when applied to multicommodity network flows problems. A recent specialized interior-point algorithm for linear multicommodity network flows overcame this drawback, and was able to efficiently solve large and difficult instances. In this work we perform a computational evaluation of an extension of that specialized algorithm for...

Automated inspection of Printed Circuit Boards(PCB's) is essential if 100% repeatible inspection is to be carried out. The cost of most commercially available systems for automatic visual inspection of PCB's are beyond the reach of many small to medium manufacturers. The principle objectives of our research is to develop and integrate a micro-computer based image analysis system specifically fo...

We present a new algorithm for nonlinear semidefinite programming, based on the iterative solution in the primal and dual variables of Karush-KuhnTucker optimality conditions, which generates a feasible decreasing sequence. At each iteration, two linear systems with the same matrix are solved to compute a feasible descent direction and then an inexact line search is performed in order to determ...

In this paper, a new interior algorithm for tracing the combined homotopy path of the variational inequality problems is proposed, and its global convergence is established under some conditions. The residual control criteria, which ensures that the obtained iterative points are interior points, is given by the condition that ensures the β-cone neighborhood to be included in the interior part o...

The paper describes an interior–point algorithm for nonconvex nonlinear programming which is a direct extension of interior–point methods for linear and quadratic programming. Major modifications include a merit function and an altered search direction to ensure that a descent direction for the merit function is obtained. Preliminary numerical testing indicates that the method is robust. Furthe...

We present a modified version of the infeasible-interiorpoint algorithm for monotone linear complementary problems introduced by Mansouri et al. (Nonlinear Anal. Real World Appl. 12(2011) 545–561). Each main step of the algorithm consists of a feasibility step and several centering steps. We use a different feasibility step, which targets at the μ-center. It results a better iteration bound.

There has been a great deal of success in the last twenty years with the use of cutting plane algorithms to solve specialized integer programming problems. Generally, these algorithms work by solving a sequence of linear programming relaxations of the integer programming problem, and they use the simplex algorithm to solve the relaxations. In this paper, we describe experiments using a predicto...

We present a primal-dual interior point algorithm of line-search type for nonlinear programs, which uses a new decomposition scheme of sequential quadratic programming. The algorithm can circumvent the convergence difficulties of some existing interior point methods. Global convergence properties are derived without assuming regularity conditions. The penalty parameter ρ in the merit function i...