This code implements an SQP approach that is modified to generate feasible iterates. In addition to handling general single objective constrained nonlinear optimization problems, the code is also capable of handling multiple competing linear and nonlinear objective functions (minimax), linear and nonlinear inequality constraints, as well as linear and nonlinear equality constraints. [Lawrence1996] [LICENSE]
Bases: pyOpt.pyOpt_optimizer.Optimizer
FSQP Optimizer Class - Inherited from Optimizer Abstract Class
FSQP 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 - Ruben E. Perez
Name | Type | Default Value | Notes |
---|---|---|---|
mode | int | 100 | FSQP Mode |
iprint | int | 2 | Output Level (0- None, 1- Final, 2- Major, 3- Major Details) |
miter | int | 500 | Maximum Number of Iterations |
bigbnd | float | 1e10 | Plus Infinity Value |
epstol | float | 1e-8 | Convergence Tolerance |
epseqn | float | 0 | Equality Constraints Tolerance |
iout | int | 6 | Output Unit Number |
ifile | str | ‘FSQP.out’ | Output File Name |