In this paper a specific class of convex feasibility problems are considered and tailored algorithms to solve this class of problems are introduced. First, the Nonlinear Cimmino Algorithm is reviewed. Then motivated by the special structure of the problems at hand, a modification to this method is proposed. Next, another method for solving the dual problem of the provided problem is presented. This leads to similar update rules for the variables as in the modified Nonlinear Cimmino Algorithm. Then an application for the proposed algorithms on the robust stability analysis of large scale weakly interconnected systems is presented and the performance of the proposed methods are compared
This paper presents a distributed computational framework for stochastic convex optimization problem...
This paper considers an uncertain convex optimization problem, posed in a locally convex decision sp...
A numerical method is proposed for optimal robust control synthesis. The method applies to the case ...
We consider a class of convex feasibility problems where the constraints that describe the feasible ...
Due to their extraordinary utility and broad applicability in many areas of classical mathematics an...
Abstract: We propose a new way to derive tractable robust counterparts of a linear conic optimizatio...
In this paper, we consider robust stability analysis of large-scale sparsely interconnected uncertai...
In this paper, we consider robust stability analysis of large-scale sparsely interconnected uncertai...
This book presents a number of techniques for robustness analysis of uncertain systems. The theoreti...
This thesis discusses different methods for robust optimization problems that are convex in the unce...
We consider simple projection methods for solving convex feasibility problems. Both successive and s...
stability and robustness analysis problems to nondifferentiable convex programs. They have also prov...
AbstractAn iterative method is proposed for solving convex feasibility problems. Each iteration is a...
The paper deals with optimization problems with uncertain constraints and linear perturbations of th...
In this paper, we propose a new method, which is called the combination projection method (CPM), for...
This paper presents a distributed computational framework for stochastic convex optimization problem...
This paper considers an uncertain convex optimization problem, posed in a locally convex decision sp...
A numerical method is proposed for optimal robust control synthesis. The method applies to the case ...
We consider a class of convex feasibility problems where the constraints that describe the feasible ...
Due to their extraordinary utility and broad applicability in many areas of classical mathematics an...
Abstract: We propose a new way to derive tractable robust counterparts of a linear conic optimizatio...
In this paper, we consider robust stability analysis of large-scale sparsely interconnected uncertai...
In this paper, we consider robust stability analysis of large-scale sparsely interconnected uncertai...
This book presents a number of techniques for robustness analysis of uncertain systems. The theoreti...
This thesis discusses different methods for robust optimization problems that are convex in the unce...
We consider simple projection methods for solving convex feasibility problems. Both successive and s...
stability and robustness analysis problems to nondifferentiable convex programs. They have also prov...
AbstractAn iterative method is proposed for solving convex feasibility problems. Each iteration is a...
The paper deals with optimization problems with uncertain constraints and linear perturbations of th...
In this paper, we propose a new method, which is called the combination projection method (CPM), for...
This paper presents a distributed computational framework for stochastic convex optimization problem...
This paper considers an uncertain convex optimization problem, posed in a locally convex decision sp...
A numerical method is proposed for optimal robust control synthesis. The method applies to the case ...