The fundamental theorem of linear programming guarantees the existence of an extreme point solution provided there is some (interior point or otherwise) feasible solution. The converse is certainly not true. This paper derives necessary and sufficient conditions for the existence of positive non‐extremal (interior) solutions within the feasible region of a linear program
This paper presents the convergence proof and complexity analysis of an interior-point framework tha...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
Currently, the simplex method and the interior point method are indisputably the most popular algori...
AbstractThis paper studies the difference between finite-dimensional linear programming problems and...
Two different definitions of extreme points, one of them taking the strict convex combination of two...
A weak version of what is sometimes called the fundamental theorem of linear programming states that...
We study interior-point methods for optimization problems in the case of infeasibility or unboundedn...
In Semidefinite programming one minimizes a linear function sub-ject to the constraint that an affin...
AbstractThe problem of finding the middle of a feasible region defined by solutions to a set of line...
We present a primal method for the solution of the semi-infinite linear programming problem with con...
AbstractIn this paper, we design an algorithm for solving linear semi-infinite programming problems ...
Various algorithms can compute approximate feasible points or approximate solutions to equality and ...
During the last fifteen years we have witnessed an explosive development in the area of optimization...
During the last fifteen years we have witnessed an explosive development in the area of optimization...
In this paper we consider a linear programming problem with the underlying matrix unimodular, and th...
This paper presents the convergence proof and complexity analysis of an interior-point framework tha...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
Currently, the simplex method and the interior point method are indisputably the most popular algori...
AbstractThis paper studies the difference between finite-dimensional linear programming problems and...
Two different definitions of extreme points, one of them taking the strict convex combination of two...
A weak version of what is sometimes called the fundamental theorem of linear programming states that...
We study interior-point methods for optimization problems in the case of infeasibility or unboundedn...
In Semidefinite programming one minimizes a linear function sub-ject to the constraint that an affin...
AbstractThe problem of finding the middle of a feasible region defined by solutions to a set of line...
We present a primal method for the solution of the semi-infinite linear programming problem with con...
AbstractIn this paper, we design an algorithm for solving linear semi-infinite programming problems ...
Various algorithms can compute approximate feasible points or approximate solutions to equality and ...
During the last fifteen years we have witnessed an explosive development in the area of optimization...
During the last fifteen years we have witnessed an explosive development in the area of optimization...
In this paper we consider a linear programming problem with the underlying matrix unimodular, and th...
This paper presents the convergence proof and complexity analysis of an interior-point framework tha...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
Currently, the simplex method and the interior point method are indisputably the most popular algori...