Reaktoro
A unified framework for modeling chemically reactive systems
OptimumOptions Struct Reference

A type that describes the options of a optimisation calculation. More...

#include <OptimumOptions.hpp>

Collaboration diagram for OptimumOptions:
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Public Attributes

double tolerance = 1.0e-6
 The tolerance for the residual of the optimality conditions.
 
double tolerancex = 0.0
 The tolerance for the variation in primal variables x. More...
 
double tolerancef = 0.0
 The tolerance for the variation in objective value. More...
 
double tolerance_linear_constraints = 1.0e-14
 The tolerance for the linear contraint equations.
 
unsigned max_iterations = 200
 The maximum number of iterations in the optimisation calculations.
 
OptimumOutputOptions output
 The options for the output of the optimisation calculations.
 
OptimumParamsActNewton actnewton
 The parameters for the ActNewton algorithm.
 
OptimumParamsIpAction ipaction
 The parameters for the IpAction algorithm.
 
OptimumParamsIpOpt ipopt
 The parameters for the IpOpt algorithm.
 
OptimumParamsIpNewton ipnewton
 The parameters for the IpNewton algorithm.
 
OptimumParamsIpActive ipactive
 The parameters for the IpActive algorithm.
 
OptimumParamsKarpov karpov
 The parameters for the Karpov algorithm.
 
OptimumParamsRefiner refiner
 The parameters for the Refiner algorithm.
 
OptimumParamsRegularization regularization
 The regularization options for the optimisation calculation.
 
KktOptions kkt
 The options for the KKT calculations.
 

Detailed Description

A type that describes the options of a optimisation calculation.

Member Data Documentation

◆ tolerancex

double tolerancex = 0.0

The tolerance for the variation in primal variables x.

Set this to a value greater than zero to stop the calculation whenever max(abs(dx)) < tolerancex, where dx is the current step of the primal variables.

◆ tolerancef

double tolerancef = 0.0

The tolerance for the variation in objective value.

Set this to a value greater than zero to stop the calculation whenever abs(f - fprev) < tolerancef, where f and fprev are the current and previous value of the objective function.


The documentation for this struct was generated from the following file: