AbstractWe propose a new polynomial potential-reduction method for linear programming, which can also be seen as a large-step path-following method. We do an (approximate) linesearch along the Newton direction with respect to Renegar's strictly convex potential function if the iterate is far away from the central trajectory. If the iterate lies close to the trajectory, we update the lower bound for the optimal value. Dependent on this updating scheme, the iteration bound can be proved to be O(nL) or O(nL). Our method differs from the recently published potential-reduction methods in the choice of the potential function and the search direction
Written for specialists working in optimization, mathematical programming, or control theory. The ge...
This paper develops a potential reduction algorithm for solving a linear-programming problem directl...
In this note we show that a simple modification of Ye's "affinely scaled potential reduction" algori...
AbstractWe propose a new polynomial potential-reduction method for linear programming, which can als...
Cover title.Includes bibliographical references (p. 29-32).Research partially supported by the U.S. ...
AbstractIn this paper we propose two potential reduction algorithms, which we call Algorithm 1 and A...
As a natural extension of Roos and Vial\u27s "Long steps with logarithmic penalty barrier function i...
We describe a steepest-descent potential reduction method for linear and convex minimization over a ...
We provide a survey of interior-point methods for linear programming and its extensions that are bas...
This article considers continuous trajectories of the vector fields induced by two different primal-...
AbstractIn this note we show that a simple modification of Ye's “affinely scaled potential reduction...
This paper takes a fresh look at the application of quadratic penalty functions to linear programmin...
In this paper we analyze from a unique point of view the behavior of path-following and primal-dual ...
Abstract: "A local acceleration method for primal-dual potential-reduction algorithms is introduced....
To simplify the analysis of interior-point methods, one commonly formulates the problem so that the ...
Written for specialists working in optimization, mathematical programming, or control theory. The ge...
This paper develops a potential reduction algorithm for solving a linear-programming problem directl...
In this note we show that a simple modification of Ye's "affinely scaled potential reduction" algori...
AbstractWe propose a new polynomial potential-reduction method for linear programming, which can als...
Cover title.Includes bibliographical references (p. 29-32).Research partially supported by the U.S. ...
AbstractIn this paper we propose two potential reduction algorithms, which we call Algorithm 1 and A...
As a natural extension of Roos and Vial\u27s "Long steps with logarithmic penalty barrier function i...
We describe a steepest-descent potential reduction method for linear and convex minimization over a ...
We provide a survey of interior-point methods for linear programming and its extensions that are bas...
This article considers continuous trajectories of the vector fields induced by two different primal-...
AbstractIn this note we show that a simple modification of Ye's “affinely scaled potential reduction...
This paper takes a fresh look at the application of quadratic penalty functions to linear programmin...
In this paper we analyze from a unique point of view the behavior of path-following and primal-dual ...
Abstract: "A local acceleration method for primal-dual potential-reduction algorithms is introduced....
To simplify the analysis of interior-point methods, one commonly formulates the problem so that the ...
Written for specialists working in optimization, mathematical programming, or control theory. The ge...
This paper develops a potential reduction algorithm for solving a linear-programming problem directl...
In this note we show that a simple modification of Ye's "affinely scaled potential reduction" algori...