AbstractOur goal in this work is to give an optimum correction of the infeasible absolute value equations (AVE). In order to make the mentioned system feasible, we apply the minimal correction using the l2 norm by changing just the right hand vector. We will show that this problem can be formulated as an unconstrained optimization problem with a quadratic objective function. We propose an extension of Newton’s method for solving unconstrained objective optimization. Some examples are provided to illustrate the efficiency and validity of our proposed method
AbstractMost “quasi-Newton” methods in common use for function minimisation use a quadratic model to...
AbstractThe alternating direction method is an attractive approach for large problems. The convergen...
AbstractThis paper describes a class of variable penalty methods for solving the general nonlinear p...
AbstractOur goal in this work is to give an optimum correction of the infeasible absolute value equa...
By utilizing a dual complementarity condition, we propose an iterative method for solving the NPhard...
AbstractWe investigate existence and nonexistence of solutions for NP-hard equations involving absol...
AbstractWe present an algorithm for the quadratic programming problem of determining a local minimum...
We describe a modified Newton type algorithm for the solution of linear inequality systems in the se...
In this work we give a detailed look to the Practical implementation of unconstrained optimization t...
The aim of this paper is twofold. Firstly, we consider the unique solvability of absolute value equa...
summary:When a system of one-sided max-plus linear equations is inconsistent, its right-hand side ve...
We investigate existence and nonexistence of solutions for NP-hard equations in- volving absolute v...
AbstractBy the use of a nonlinear model for the gradient of the objective function along a chosen di...
We present a numerical method for the minimization of objectives that are augmented with linear ineq...
AbstractWe present a way of solving the problem of minimizing the root of quadratic functional subje...
AbstractMost “quasi-Newton” methods in common use for function minimisation use a quadratic model to...
AbstractThe alternating direction method is an attractive approach for large problems. The convergen...
AbstractThis paper describes a class of variable penalty methods for solving the general nonlinear p...
AbstractOur goal in this work is to give an optimum correction of the infeasible absolute value equa...
By utilizing a dual complementarity condition, we propose an iterative method for solving the NPhard...
AbstractWe investigate existence and nonexistence of solutions for NP-hard equations involving absol...
AbstractWe present an algorithm for the quadratic programming problem of determining a local minimum...
We describe a modified Newton type algorithm for the solution of linear inequality systems in the se...
In this work we give a detailed look to the Practical implementation of unconstrained optimization t...
The aim of this paper is twofold. Firstly, we consider the unique solvability of absolute value equa...
summary:When a system of one-sided max-plus linear equations is inconsistent, its right-hand side ve...
We investigate existence and nonexistence of solutions for NP-hard equations in- volving absolute v...
AbstractBy the use of a nonlinear model for the gradient of the objective function along a chosen di...
We present a numerical method for the minimization of objectives that are augmented with linear ineq...
AbstractWe present a way of solving the problem of minimizing the root of quadratic functional subje...
AbstractMost “quasi-Newton” methods in common use for function minimisation use a quadratic model to...
AbstractThe alternating direction method is an attractive approach for large problems. The convergen...
AbstractThis paper describes a class of variable penalty methods for solving the general nonlinear p...