ALGENCAN solves the general non-linear constrained optimization problem without resorting to the use of matrix manipulations. It uses instead an Augmented Lagrangian approach which is able to solve extremely large problems with moderate computer time. [Andreani2007] [LICENSE]
Bases: pyOpt.pyOpt_optimizer.Optimizer
ALGENCAN Optimizer Class - Inherited from Optimizer Abstract Class
ALGENCAN Optimizer Class Initialization
Keyword arguments:
Documentation last updated: Feb. 16, 2010 - Peter W. Jansen
Run Optimizer (Optimize Routine)
Keyword arguments:
Additional arguments and keyword arguments are passed to the objective function call.
Documentation last updated: February. 2, 2011 - Peter W. Jansen
Name | Type | Default Value | Notes |
---|---|---|---|
epsfeas | float | 1e-8 | Feasibility Convergence Accurancy |
epsopt | float | 1e-8 | Optimality Convergence Accurancy |
efacc | float | 1e-4 | Feasibility Level for Newton-KKT Acceleration |
eoacc | float | 1e-4 | Optimality Level for Newton-KKT Acceleration |
checkder | bool | False | Check Derivatives Flag |
iprint | int | 2 | Output Level (0 - None, 10 - Final, >10 - Iter Details) |
ifile | str | ‘ALGENCAN.out’ | Output File Name |
ncomp | int | 6 | Print Precision |