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SOLVOPT - SOLver for local OPTimization problems

SOLVOPT is a modified version of Shor’s r–algorithm with space dilation to find a local minimum of nonlinear and non–smooth problems . The algorithm handles constraints using an exact penalization method. [Kuntsevich1997] [LICENSE]

class pySOLVOPT.SOLVOPT(pll_type=None, *args, **kwargs)

Bases: pyOpt.pyOpt_optimizer.Optimizer

SOLVOPT Optimizer Class - Inherited from Optimizer Abstract Class

SOLVOPT 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, 2011 - Peter W. Jansen

Optimizer Options

Name Type Default Value Notes
xtol float 1.0e-4 Variables Tolerance
ftol float 1.0e-6 Objective Tolerance
maxit int 15000 Maximum Number of Iterations
iprint int 1 Output Level (-1-None, 0-Final, N-each Nth iter)
gtol float 1.0e-8 Constraints Tolerance
spcdil float 2.5 Space Dilation
iout int 6 Output Unit Number
ifile str ‘SOLVOPT.out’ Output File Name