CONMIN

CONstrained function MINimization (CONMIN) is a gradient-based optimizer that uses the methods of feasible directions.

Options

CONMIN Default Options

Name	Type	Default value	Description
ITMAX	int	10000	Maximum Number of Iterations
DELFUN	float	1e-06	Objective Relative Tolerance
DABFUN	float	1e-06	Objective Absolute Tolerance
ITRM	int	5	None
NFEASCT	int	20	None
IPRINT	int	4	Print Control (0 - None, 1 - Final, 2,3,4 - Debug)
IOUT	int	6	Output Unit Number
IFILE	str	CONMIN.out	Output File Name

API

class pyoptsparse.pyCONMIN.pyCONMIN.CONMIN(*args, **kwargs)

CONMIN Optimizer Class - Inherited from Optimizer Abstract Class

This is the base optimizer class that all optimizers inherit from. We define common methods here to avoid code duplication.

Parameters:

namestr

Optimizer name

categorystr

Typically local or global

defaultOptionsdictionary

A dictionary containing the default options

informsdict

Dictionary of the inform codes

__call__(optProb, sens=None, sensStep=None, sensMode=None, storeHistory=None, hotStart=None, storeSens=True)

This is the main routine used to solve the optimization problem.

Parameters:

optProbOptimization or Solution class instance

This is the complete description of the optimization problem to be solved by the optimizer

sensstr or python Function.

Specifiy method to compute sensitivities. To explictly use pyOptSparse gradient class to do the derivatives with finite differenes use ‘FD’. ‘sens’ may also be ‘CS’ which will cause pyOptSpare to compute the derivatives using the complex step method. Finally, ‘sens’ may be a python function handle which is expected to compute the sensitivities directly. For expensive function evaluations and/or problems with large numbers of design variables this is the preferred method.

sensStepfloat

Set the step size to use for design variables. Defaults to 1e-6 when sens is ‘FD’ and 1e-40j when sens is ‘CS’.

sensModestr

Use ‘pgc’ for parallel gradient computations. Only available with mpi4py and each objective evaluation is otherwise serial

storeHistorystr

File name of the history file into which the history of this optimization will be stored

hotStartstr

File name of the history file to “replay” for the optimziation. The optimization problem used to generate the history file specified in ‘hotStart’ must be IDENTICAL to the currently supplied ‘optProb’. By identical we mean, EVERY SINGLE PARAMETER MUST BE IDENTICAL. As soon as he requested evaluation point from CONMIN does not match the history, function and gradient evaluations revert back to normal evaluations.

storeSensbool

Flag sepcifying if sensitivities are to be stored in hist. This is necessay for hot-starting only.