NLPQLP - NonLinear Programming with Non-Monotone and Distributed Line Search

NLPQLP is an update of NLPQL for which a non-monotone line search is implemented allowing for increases in the merit function in case of numerical instabilities. The changes made to the original code also enable the ability to perform parallel function evaluations during line search. [Dai2008] and [Schitt2011] [LICENSE]

class pyNLPQLP.NLPQLP(pll_type=None, *args, **kwargs)

Bases: pyOpt.pyOpt_optimizer.Optimizer

NLPQLP Optimizer Class - Inherited from Optimizer Abstract Class

NLPQLP Optimizer Class Initialization

Keyword arguments:

• pll_type -> STR: Parallel Implementation (None, ‘POA’-Parallel Objective Analysis), Default = None

Documentation last updated: Feb. 16, 2010 - Peter W. Jansen

__solve__(opt_problem={}, sens_type='FD', store_sol=True, store_hst=False, hot_start=False, disp_opts=False, sens_mode='', sens_step={}, *args, **kwargs)

Run Optimizer (Optimize Routine)

Keyword arguments:

• opt_problem -> INST: Optimization instance
• sens_type -> STR/FUNC: Gradient type, Default = ‘FD’
• store_sol -> BOOL: Store solution in Optimization class flag, Default = True
• disp_opts -> BOOL: Flag to display options in solution text, Default = False
• store_hst -> BOOL/STR: Flag/filename to store optimization history, Default = False
• hot_start -> BOOL/STR: Flag/filename to read optimization history, Default = False
• sens_mode -> STR: Flag for parallel gradient calculation, Default = ‘’
• sens_step -> FLOAT: Sensitivity setp size, Default = {} [corresponds to 1e-6 (FD), 1e-20(CS)]

Additional arguments and keyword arguments are passed to the objective function call.

Documentation last updated: February. 2, 2013 - Peter W. Jansen

Optimizer Options

Name	Type	Default Value	Notes
ACC	float	1e-8	Convergence Accurancy
ACCQP	float	1e-12	QP Solver Convergence Accurancy
STPMIN	float	1e-10	Minimum Step Length
MAXFUN	int	10	Maximum Number of Function Calls During Line Search
MAXIT	int	100	Maximum Number of Outer Iterations
RHOB	float	0.0	BFGS-Update Matrix Initialization Parameter
IPRINT	int	2	Output Level (0-None, 1-Final, 2-Major, 3-Major/Minor, 4-Full)
MODE	int	0	NLPQL Mode (0 - Normal Execution, 1 to 18 - See Manual)
IOUT	int	6	Output Unit Number|
LQL	bool	True	QP Solver (True - Quasi-Newton, False - Cholesky)
IFILE	str	‘NLPQLP.out’	Output File Name