Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertainties are column-wise and reside in general convex sets, we show that the intersection of the set of possible solutions and any orthant is convex. We derive a convex representation of this intersection to calculate the ranges of the coordinates. Secondly, we propose two new methods for obtaining robust solutions of systems of uncertain linear equations. The first method calculates the center of the maximum inscribed ellipsoid of the set of possible solutions. The second method minimizes the expected violations with respect to the worst-case distribution. We compare these two new methods both theoretically and numerically with an existing metho...
In the design of a robust control system, one needs a nominal model together with a quantitative bou...
We present an exact formula for the radius of robust feasibility of uncertain linear programs with a...
This paper presents a robust stability and performance analysis for an uncertainty set delivered by ...
Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertain...
Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertain...
We treat in this paper Linear Programming (LP) problems with uncertain data. The focus is on uncerta...
We treat in this paper linear programming (LP) problems with uncertain data. The focus is on uncerta...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids t...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids th...
Robust optimization is a rapidly developing methodology for handling optimization problems affected ...
Abstract: We propose a new way to derive tractable robust counterparts of a linear conic optimizatio...
Abstract This paper deals with convex optimization problems in the face of data uncertainty within t...
This paper addresses the estimation of the set of admissible solutions of uncertain polynomial syste...
We derive computationally tractable formulations of the robust counterparts of convex quadratic and ...
AbstractLeast squares solution of linear inequalities appears in many disciplines such as linear sep...
In the design of a robust control system, one needs a nominal model together with a quantitative bou...
We present an exact formula for the radius of robust feasibility of uncertain linear programs with a...
This paper presents a robust stability and performance analysis for an uncertainty set delivered by ...
Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertain...
Our contribution is twofold. Firstly, for a system of uncertain linear equations where the uncertain...
We treat in this paper Linear Programming (LP) problems with uncertain data. The focus is on uncerta...
We treat in this paper linear programming (LP) problems with uncertain data. The focus is on uncerta...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids t...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids th...
Robust optimization is a rapidly developing methodology for handling optimization problems affected ...
Abstract: We propose a new way to derive tractable robust counterparts of a linear conic optimizatio...
Abstract This paper deals with convex optimization problems in the face of data uncertainty within t...
This paper addresses the estimation of the set of admissible solutions of uncertain polynomial syste...
We derive computationally tractable formulations of the robust counterparts of convex quadratic and ...
AbstractLeast squares solution of linear inequalities appears in many disciplines such as linear sep...
In the design of a robust control system, one needs a nominal model together with a quantitative bou...
We present an exact formula for the radius of robust feasibility of uncertain linear programs with a...
This paper presents a robust stability and performance analysis for an uncertainty set delivered by ...