Augmented Lagrangian method for nonlinear programming problems
Project description
TANGO (Trustable Algorithms for Nonlinear General Optimization) is a set of Fortran routines for Optimization developed at the Department of Applied Mathematics of the State University of Campinas and at the Department of Computer Science of the University of São Paulo, under the coordination of Professor J. M. Martínez. Only well-established methods are included. The codes are easy to use and require minimum previous knowledge. On-line support is provided.
ALGENCAN: Fortran code for general nonlinear programming that does not use matrix manipulations at all and, so, is able to solve extremely large problems with moderate computer time. The general algorithm is of Augmented Lagrangian type and the subproblems are solved using GENCAN. GENCAN (included in ALGENCAN) is a Fortran code for minimizing a smooth function with a potentially large number of variables and box-constraints. ALGENCAN has interfaces with AMPL, C/C++, CUTEr, Matlab, Python, Octave and R (statistical computing).
