Add to ORKGIn this paper, we present the formulation and solution of optimization problems with complementarity constraints using an interior-point method for nonconvex nonlinear programming. We identify possible di#culties that could arise, such as unbounded faces of dual variables, linear dependence of constraint gradients and initialization issues. We suggest remedies. We include encouraging numerical results on the MacMPEC test suite of problems
We propose a new approach to convex nonlinear multiobjective optimization that captures the geometry...
An interior point method is proposed for a general nonlinear (nonconvex) minimization with linear in...
Recently, infeasibility issues in interior methods for nonconvex nonlinear programming have been st...
The contribution contains a short description of interior point s methods for nonconvex nonlinear p...
During the last fifteen years we have witnessed an explosive development in the area of optimization...
Interior-point algorithms are among the most efficient techniques for solving complementarity proble...
In this research, we discuss linear and nonlinear programming problems and methods. We have implemen...
The nonlinear complementarity problem is cast as an unconstrained minimization problem that is obtai...
We are interested in the numerical behavior of infeasible Interior-Point meth-ods for nonlinear comp...
A Mathematical Program with Linear Complementarity Constraints (MPLCC) is an optimization problem wh...
International audienceIn nonlinear optimization, interior point methods, also called primal-dual met...
Abstract Linear programming with linear complementarity constraints (LPLCC) is an area of active res...
Abstract. We propose an interior-point algorithm based on an elastic formulation of the `1-penalty m...
The complementarity problem consists in finding x ∈ IR n such that x ≥ 0,F (x) ≥ 0 and x t F (x) =0...
ABSTRACT. The paper considers a current example of Wächter and Biegler which is shown not to converg...
We propose a new approach to convex nonlinear multiobjective optimization that captures the geometry...
An interior point method is proposed for a general nonlinear (nonconvex) minimization with linear in...
Recently, infeasibility issues in interior methods for nonconvex nonlinear programming have been st...
The contribution contains a short description of interior point s methods for nonconvex nonlinear p...
During the last fifteen years we have witnessed an explosive development in the area of optimization...
Interior-point algorithms are among the most efficient techniques for solving complementarity proble...
In this research, we discuss linear and nonlinear programming problems and methods. We have implemen...
The nonlinear complementarity problem is cast as an unconstrained minimization problem that is obtai...
We are interested in the numerical behavior of infeasible Interior-Point meth-ods for nonlinear comp...
A Mathematical Program with Linear Complementarity Constraints (MPLCC) is an optimization problem wh...
International audienceIn nonlinear optimization, interior point methods, also called primal-dual met...
Abstract Linear programming with linear complementarity constraints (LPLCC) is an area of active res...
Abstract. We propose an interior-point algorithm based on an elastic formulation of the `1-penalty m...
The complementarity problem consists in finding x ∈ IR n such that x ≥ 0,F (x) ≥ 0 and x t F (x) =0...
ABSTRACT. The paper considers a current example of Wächter and Biegler which is shown not to converg...
We propose a new approach to convex nonlinear multiobjective optimization that captures the geometry...
An interior point method is proposed for a general nonlinear (nonconvex) minimization with linear in...
Recently, infeasibility issues in interior methods for nonconvex nonlinear programming have been st...