Add to ORKGWe present a successive linear programming algorithm for solving constrained nonlinear optimization problems. The algorithm employs an Armijo procedure for updating a trust region radius. We prove the linear convergence of the method by relating the solutions of our subproblems to standard trust region and gradient projection subproblems and adapting an error bound analysis due to Luo and Tseng. Computational results are provided for polyhedrally constrained nonlinear programs
AbstractWe present a class of trust region algorithms without using a penalty function or a filter f...
A trust-region algorithm for solving the equality constrained optimization problem is presented. Thi...
. In this paper, we propose a sequential linear programming hybrid algorithm to minimize a nonlinear...
We present a successive linear programming algorithm for solving constrained nonlinear optimization ...
AbstractIn this paper an algorithm for solving a linearly constrained nonlinear programming problem ...
We analyze the global convergence properties of a class of penalty methods for nonlinear programming...
AbstractIn this paper an algorithm for solving a linearly constrained nonlinear programming problem ...
A model algorithm based on the successive quadratic programming method for solving the general nonli...
Projet PROMATHIn this paper we study the convergence of sequential quadratic programming algorithms ...
Abstract. We describe an algorithm for smooth nonlinear constrained optimization problems in which a...
The global convergence properties of a class of penalty methods for nonlinear pro-gramming are analy...
In this paper a linear programming-based optimization algorithm called the Sequential Cutting Plane ...
A class of trust region based algorithms is presented for the solution of nonlinear optimization pro...
In this paper, we propose a trust-region algorithm to minimize a nonlinear function f: R^n -> R subj...
An algorithm for minimizing a nonlinear function subject to nonlinear equality and inequality constr...
AbstractWe present a class of trust region algorithms without using a penalty function or a filter f...
A trust-region algorithm for solving the equality constrained optimization problem is presented. Thi...
. In this paper, we propose a sequential linear programming hybrid algorithm to minimize a nonlinear...
We present a successive linear programming algorithm for solving constrained nonlinear optimization ...
AbstractIn this paper an algorithm for solving a linearly constrained nonlinear programming problem ...
We analyze the global convergence properties of a class of penalty methods for nonlinear programming...
AbstractIn this paper an algorithm for solving a linearly constrained nonlinear programming problem ...
A model algorithm based on the successive quadratic programming method for solving the general nonli...
Projet PROMATHIn this paper we study the convergence of sequential quadratic programming algorithms ...
Abstract. We describe an algorithm for smooth nonlinear constrained optimization problems in which a...
The global convergence properties of a class of penalty methods for nonlinear pro-gramming are analy...
In this paper a linear programming-based optimization algorithm called the Sequential Cutting Plane ...
A class of trust region based algorithms is presented for the solution of nonlinear optimization pro...
In this paper, we propose a trust-region algorithm to minimize a nonlinear function f: R^n -> R subj...
An algorithm for minimizing a nonlinear function subject to nonlinear equality and inequality constr...
AbstractWe present a class of trust region algorithms without using a penalty function or a filter f...
A trust-region algorithm for solving the equality constrained optimization problem is presented. Thi...
. In this paper, we propose a sequential linear programming hybrid algorithm to minimize a nonlinear...