NLPIP: a Fortran implementation of an SQP interior point method for solving large-scale nonlinear optimization problems—user’s guide. The Fortran subroutine NLPIP is designed to solve smooth large scale nonlinear optimization problems. The underlying algorithm is based on an SQP method where the quadratic subproblem is solved by a primal-dual interior point method. A feature of the algorithm is, that the quadratic subproblem is not necessarily solved exactly. To be able to solve large problems it can either use a limited memory BFGS update to approximate the Hessian of the Lagrangian or let the user specify the (possibly sparse) Hessian. The Jacobian of the constraints as well es the Hessian of the Lagrangian may be in any format. The user only has to provide necessary operations concerning the Jacobians and Hessians. Numerical results are included for some elliptic control problems by Maurer and Mittelmann with over 5 million variables and 2.5 million constraints
Keywords for this software
References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Sachsenberg, Björn; Schittkowski, Klaus: A combined SQP-IPM algorithm for solving large-scale nonlinear optimization problems (2015)
- Schittkowski, K.: A robust implementation of a sequential quadratic programming algorithm with successive error restoration (2011)