diffev.c File Reference

#include "diffev.h"
#include "misc.h"
#include "simsched.h"
#include "pointbuff.h"
#include "jobqueue.h"
#include <gsl/gsl_rng.h>
#include <limits.h>
#include <float.h>
#include <math.h>
#include <memory.h>
#include <stdio.h>
#include <stdlib.h>
#include <signal.h>
#include "dprintf.h"

Data Structures
struct	TaskArg

Macros
#define	DPRINTF_ON
#define	PRARRAY(nn, xx)
	Macro to print array. More...

Functions
static void	assignd (int dim, double a[], double b[])
void	sample (int k, int rtn[k], int n, int array[n], const gsl_rng *rng)
	Choose at random k distinct integers from array of n, placing result in "rtn". More...
TaskArg *	TaskArg_new (int dim, double(*objfun)(int xdim, double x[xdim], void *jdat, void *tdat), void *jobData)
	TaskArg constructor.
static void	TaskArg_setArray (TaskArg *self, int dim, double v[dim])
	Set the array within a TaskArg equal to an external array, v.
void	TaskArg_free (TaskArg *self)
	TaskArg destructor. More...
void	TaskArg_print (TaskArg *self, FILE *fp)
	Print a TaskArg.
int	taskfun (void *voidPtr, void *tdat)
	Called by JobQueue.
void	printState (int nPts, int nPar, double par[nPts][nPar], double cost[nPts], int imin, FILE *fp)
	Print current state. Current optimal point is printed first.
void	stratDE_best_1_exp (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/best/1/exp Our oldest strategy but still not bad. More...
void	stratDE_rand_1_exp (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/rand/1/exp This is one of my favourite strategies. More...
void	stratDE_rand_to_best_1_exp (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/rand-to-best/1/exp This strategy seems to be one of the best strategies. More...
void	stratDE_best_2_exp (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/best/2/exp is another powerful strategy worth trying.
void	stratDE_rand_2_exp (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/rand/2/exp seems to be a robust optimizer for many functions.
void	stratDE_best_1_bin (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	Remaining strategies have binomial crossover. More...
void	stratDE_rand_1_bin (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/rand/1/bin.
void	stratDE_rand_to_best_1_bin (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/rand-to-best/1/bin.
void	stratDE_best_2_bin (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/best/2/bin.
void	stratDE_rand_2_bin (int dim, double tmp[dim], int nPts, int ndx[nPts], double bestit[dim], double F, double CR, double(*pold)[nPts][dim], gsl_rng *rng)
	DE/rand/2/bin.
void *	getStratFun (int strategy)
	Return pointer to function implementing given strategy.
void	sighandle (int signo)
	Signal handler.
void	handleSIGTERM (int signo)
	SIGTERM is translated to SIGINT.
const char *	diffEvStrategyLbl (int i)
	Return a const pointer to the label of the i'th strategy.
static void	assignd (int dim, double a[dim], double b[dim])
	Assigns dim-dimensional vector b to vector a.
DEStatus	diffev (int dim, double estimate[dim], double *loCost, double *yspread, DiffEvPar dep, gsl_rng *rng)
	The diffev optimizer.

Variables
pthread_mutex_t	outputLock
volatile sig_atomic_t	sigstat =0
static const char *	stratLbl []

Macro Definition Documentation

PRARRAY

#define PRARRAY	(		nn,
			xx
	)

Value:

    do { \
      printf("%s:%s:%d:", __FILE__,__func__,__LINE__);    \
      int ii; \
      for(ii=0; ii < (nn); ++ii) \
          printf(" %lf", (xx)[ii]); \
      putchar('\n'); \
    }while(0);

Macro to print array.

Function Documentation

sample()

void sample	(	int	k,
		int	rtn[k],
		int	n,
		int	array[n],
		const gsl_rng *	rng
	)

Choose at random k distinct integers from array of n, placing result in "rtn".

The function can be called repeatedly without re-initializing "array".

Side Effects:\n Re-orders entries of array.

Referenced by stratDE_best_1_bin(), stratDE_best_1_exp(), stratDE_best_2_bin(), stratDE_best_2_exp(), stratDE_rand_1_bin(), stratDE_rand_1_exp(), stratDE_rand_2_bin(), stratDE_rand_2_exp(), stratDE_rand_to_best_1_bin(), and stratDE_rand_to_best_1_exp().

stratDE_best_1_bin()

void stratDE_best_1_bin	(	int	dim,
		double	tmp[dim],
		int	nPts,
		int	ndx[nPts],
		double	bestit[dim],
		double	F,
		double	CR,
		double(*)	pold[nPts][dim],
		gsl_rng *	rng
	)

Remaining strategies have binomial crossover.

DE/best/1/bin

References sample().

Referenced by getStratFun().

stratDE_best_1_exp()

void stratDE_best_1_exp	(	int	dim,
		double	tmp[dim],
		int	nPts,
		int	ndx[nPts],
		double	bestit[dim],
		double	F,
		double	CR,
		double(*)	pold[nPts][dim],
		gsl_rng *	rng
	)

DE/best/1/exp Our oldest strategy but still not bad.

However, we have found several optimization problems where misconvergence occurs. strategy DE0 (not in our paper)

References sample().

Referenced by getStratFun().

stratDE_rand_1_exp()

void stratDE_rand_1_exp	(	int	dim,
		double	tmp[dim],
		int	nPts,
		int	ndx[nPts],
		double	bestit[dim],
		double	F,
		double	CR,
		double(*)	pold[nPts][dim],
		gsl_rng *	rng
	)

DE/rand/1/exp This is one of my favourite strategies.

It works especially well when the "bestit[]"-schemes experience misconvergence. Try e.g. F=0.7 and CR=0.5. as a first guess. strategy DE1 in the techreport

References sample().

Referenced by getStratFun().

stratDE_rand_to_best_1_exp()

void stratDE_rand_to_best_1_exp	(	int	dim,
		double	tmp[dim],
		int	nPts,
		int	ndx[nPts],
		double	bestit[dim],
		double	F,
		double	CR,
		double(*)	pold[nPts][dim],
		gsl_rng *	rng
	)

DE/rand-to-best/1/exp This strategy seems to be one of the best strategies.

Try F=0.85 and CR=1. If you get misconvergence try to increase nPts. If this doesn't help you should play around with all three control variables. similiar to DE2 but generally better

References sample().

Referenced by getStratFun().

TaskArg_free()

void TaskArg_free

(

TaskArg *

self

)

TaskArg destructor.

Doesn't free self->jobData or self->objfun, which are not locally owned.

Variable Documentation

stratLbl

const char* stratLbl[]

static

Initial value:

= 
{ "", "DE/best/1/exp", "DE/rand/1/exp", "DE/rand-to-best/1/exp",
    "DE/best/2/exp", "DE/rand/2/exp", "DE/best/1/bin",
    "DE/rand/1/bin", "DE/rand-to-best/1/bin", "DE/best/2/bin",
    "DE/rand/2/bin"
}