summary:The characterization of the solution set of a convex constrained problem is a well-known attempt. In this paper, we focus on the minimum norm solution of a specific constrained convex nonlinear problem and reformulate this problem as an unconstrained minimization problem by using the alternative theorem.The objective function of this problem is piecewise quadratic, convex, and once differentiable. To minimize this function, we will provide a new Newton-type method with global convergence properties
The conventional Lagrangian approach to solving constrained optimization problems leads to optimalit...
In this paper, a method for solving constrained convex optimization problems is introduced. The prob...
A Newton algorithm for solving the problem minimize f(x) subject to g(x) - 0, where f:Rn - R and g:R...
summary:The characterization of the solution set of a convex constrained problem is a well-known att...
This paper describes a new technique to find the minimum norm solution of a linear program. The main...
We discuss some basic concepts and present a numerical procedure for finding the minimum-norm soluti...
. This paper describes a new technique to nd the minimum norm solution of a linear program. The main...
It is shown that the dual of the problem of minimizing the 2-norm of the primal and dual optimal var...
AbstractIt is shown that the dual of the problem of minimizing the 2-norm of the primal and dual opt...
Abstract. A system of linear equations Ax = b, in n unknowns and m equations which has a nonnegative...
We establish new necessary and sufficient optimality conditions for global optimization problems. In...
ABSTRACT In this paper, we consider the problem of minimization of an objective function having cont...
Abstract In this paper, the nonlinear minimax problems with inequality constraints are discussed. Ba...
The problem of minimizing a twice differentiable convex function f is considered, subject to Ax = b,...
In this paper we consider the problem of minimizing a (possibly nonconvex) quadratic function with a...
The conventional Lagrangian approach to solving constrained optimization problems leads to optimalit...
In this paper, a method for solving constrained convex optimization problems is introduced. The prob...
A Newton algorithm for solving the problem minimize f(x) subject to g(x) - 0, where f:Rn - R and g:R...
summary:The characterization of the solution set of a convex constrained problem is a well-known att...
This paper describes a new technique to find the minimum norm solution of a linear program. The main...
We discuss some basic concepts and present a numerical procedure for finding the minimum-norm soluti...
. This paper describes a new technique to nd the minimum norm solution of a linear program. The main...
It is shown that the dual of the problem of minimizing the 2-norm of the primal and dual optimal var...
AbstractIt is shown that the dual of the problem of minimizing the 2-norm of the primal and dual opt...
Abstract. A system of linear equations Ax = b, in n unknowns and m equations which has a nonnegative...
We establish new necessary and sufficient optimality conditions for global optimization problems. In...
ABSTRACT In this paper, we consider the problem of minimization of an objective function having cont...
Abstract In this paper, the nonlinear minimax problems with inequality constraints are discussed. Ba...
The problem of minimizing a twice differentiable convex function f is considered, subject to Ax = b,...
In this paper we consider the problem of minimizing a (possibly nonconvex) quadratic function with a...
The conventional Lagrangian approach to solving constrained optimization problems leads to optimalit...
In this paper, a method for solving constrained convex optimization problems is introduced. The prob...
A Newton algorithm for solving the problem minimize f(x) subject to g(x) - 0, where f:Rn - R and g:R...