chrono::ChOptimizerGenetic Class Reference

Description

Class for global optimization with the genetic method (evolutive simulation).

#include <ChSolvmin.h>

Inheritance diagram for chrono::ChOptimizerGenetic:
Collaboration diagram for chrono::ChOptimizerGenetic:

Public Types

enum  SelectionType { ROULETTE, ROULETTEBEST, NORMGEOMETRIC, TOURNAMENT }
 
enum  CrossoverType {
  ARITMETIC, BLEND, BLEND_RANDOM, HEURISTIC,
  DISABLED
}
 
enum  CrossoverChangeType { NO_CHANGE, DATE, SLOWLY }
 
enum  MutationType { UNIFORM, BOUNDARY }
 
enum  ReplaceMode { PARENTS = 0, WORST }
 

Public Member Functions

 ChOptimizerGenetic (const ChOptimizerGenetic &other)
 
virtual bool DoOptimize () override
 This function computes the optimal xv[]. More...
 
bool CreatePopulation (ChGenotype **&my_population, int my_popsize)
 
bool DeletePopulation (ChGenotype **&my_population, int my_popsize)
 
ChGenotypeSelect_roulette (ChGenotype **my_population)
 
ChGenotypeSelect_best (ChGenotype **my_population)
 
ChGenotypeSelect_worst (ChGenotype **my_population)
 
double Get_fitness_interval (ChGenotype **my_population)
 
double ComputeFitness (ChGenotype *)
 
void ApplyCrossover (ChGenotype *par1, ChGenotype *par2, ChGenotype &child1, ChGenotype &child2)
 
bool InitializePopulation ()
 
bool ComputeAllFitness ()
 
void Selection ()
 
void Crossover ()
 
void Mutation ()
 
void PopulationStats (double &average, double &max, double &min, double &stdeviation)
 
void LogOut (bool filelog)
 
- Public Member Functions inherited from chrono::ChOptimizer
 ChOptimizer (const ChOptimizer &other)
 
virtual void SetObjective (ChFx *mformula)
 Sets the objective function to maximize.
 
virtual ChFxGetObjective () const
 
virtual void SetObjectiveGrad (ChFx *mformula)
 Sets the objective function gradient (not mandatory, because if not set, the default bacward differentiation is used).
 
virtual ChFxGetObjectiveGrad () const
 
virtual void SetNumOfVars (int mv)
 Set the number of optimization variables. More...
 
virtual int GetNumOfVars () const
 Returns the number of optimization variables.
 
double * GetXv () const
 
double * GetXv_sup () const
 
double * GetXv_inf () const
 
void SetXv (double *mx)
 
void SetXv_sup (double *mx)
 
void SetXv_inf (double *mx)
 
double Eval_fx (double x[])
 Returns the value of the functional, for given state of variables and with the given "database" multibody system. More...
 
double Eval_fx (const ChVectorDynamic<> &x)
 
void Eval_grad (double x[], double gr[])
 Computes the gradient of objective function, for given state of variables. More...
 
void Eval_grad (const ChVectorDynamic<> &x, ChVectorDynamic<> &gr)
 
virtual bool PreOptimize ()
 Performs the optimization of the ChSystem pointed by "database" (or whatever object which can evaluate the string "function" and the "optvarlist") using the current parameters. More...
 
virtual bool PostOptimize ()
 Finalization and cleanup.
 
virtual bool Optimize ()
 Does the three steps in sequence PreOptimize, DoOptimize, PostOptimize. More...
 
void DoBreakCheck ()
 Each break_cycles number of times this fx is called, the function break_funct() is evaluated (if any) and if positive, the variable user_break becomes true.
 

Public Attributes

int popsize
 def = 100; initial population size in array "population"
 
ChGenotype ** population
 Array of pointers to population genotypes.
 
ChGenotypebest_indiv
 Copy of the individual with best fitness found in latest optimization.
 
int max_generations
 max number of generations to perform
 
SelectionType selection
 reproduction (selection) type
 
CrossoverType crossover
 crossover type
 
MutationType mutation
 mutation type;
 
bool elite
 if true, best parent is always kept after crossover
 
CrossoverChangeType crossv_change
 see codes above, if NO_CHANGE the crossover type is always the same
 
CrossoverType crossv_changeto
 the type of new crossover if using crossv_change
 
long crossv_changewhen
 generation number, when the "change of crossover type" takes place
 
double mutation_prob
 probability of mutation, 0..1, default = 0.001
 
double crossover_prob
 crossover probability, default = 0.3;
 
bool speciation_mating
 if true, marriage happens between similar individuals;
 
bool incest_taboo
 if true, avoids marriage between individuals too similar
 
ReplaceMode replacement
 replacement mode
 
double eugenetics
 range (0..1); if 0, no eugenetics, otherwise clamp for fitness (normalized in 0..1)
 
bool stop_by_stdeviation
 if true... (def: false)
 
double stop_stdeviation
 stop search if stdeviation becomes lower than this value (def.0)
 
bool stop_by_fitness
 if true... (def. false)
 
double stop_fitness
 stop search if fitness of best individual exceed this value (def.0)
 
double average
 the average fitness of individuals
 
double stdeviation
 the unbiased standard deviation (=sqrt(variance)) of fitness
 
double min_fitness
 
double max_fitness
 
long generations_done
 number of generations performed
 
long mutants
 mutated individuals since start of optimizations
 
ChVectorDynamichis_average
 
ChVectorDynamichis_stdeviation
 
ChVectorDynamichis_maxfitness
 
ChVectorDynamichis_minfitness
 
- Public Attributes inherited from chrono::ChOptimizer
bool minimize
 default = false; just maximize
 
double grad_step
 default = 1.e-12; step size for evaluation of gradient
 
double opt_fx
 best resulting value of objective function
 
char err_message [200]
 the ok/warning/error messages are written here
 
int error_code
 
long fx_evaluations
 number of function evaluations
 
long grad_evaluations
 number of gradient evaluations
 
int(* break_funct )()
 if not null, this function is called each 'break_cycles' evaluations
 
int break_cycles
 how many fx evaluations per check
 
int user_break
 if break_funct() reported true, this flag is ON, and optimizers should exit all cycles
 
int break_cyclecounter
 internal
 

Additional Inherited Members

- Protected Attributes inherited from chrono::ChOptimizer
ChFxafunction
 the function to be maximized
 
ChFxafunctionGrad
 the gradient of the function to be maximized, or null for default BDF.
 
int C_vars
 number of input variables
 
double * xv
 Vector of variables, also 1st approximation.
 
double * xv_sup
 These are the hi/lo limits for the variables,.
 
double * xv_inf
 these are not used by all optimizer, and can be NULL for gradient, but needed for genetic.
 

Member Function Documentation

◆ Crossover()

void chrono::ChOptimizerGenetic::Crossover ( )

if (par1->genes->Equals(par2->genes)) /cout << "\n --incest";

◆ DoOptimize()

bool chrono::ChOptimizerGenetic::DoOptimize ( )
overridevirtual

This function computes the optimal xv[].

It must be implemented by derived classes

Reimplemented from chrono::ChOptimizer.


The documentation for this class was generated from the following files:
  • C:/Users/udarn/Repositories/chrono/src/chrono/solver/ChSolvmin.h
  • C:/Users/udarn/Repositories/chrono/src/chrono/solver/ChSolvmin.cpp