ga.c

基于遗传算法的无功优化matlab实现方法软件包

#include <graphics.h>
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>
#include <conio.h>
#include <dos.h>

#define NAME_MAX 80


void
ga(char *datFile)
{
	/* request autodetection */
	int gdriver=DETECT,gmode,errorcode;
	int prex,bprey,curx,bcury,mprey,mcury,
			wprey,wcury,vprey,vcury;
  //	int maxcolor,ystep;
	double temp;

	time_t	begin,finish;

	char    Msg[NAME_MAX];
	char    patternFile[NAME_MAX], weightFile[NAME_MAX],
			resultFile[NAME_MAX];
	int     **population;
	double  **pattern, **target;
	double *fit;
	int     M,N,H,iter,P,K;  /* K: each weight represented by K bits */
			/*  M: pattern no.;  N: input dim;  H: hidden No. */
			/* iter: generation number;  P: output dim */
	int  status, popsize,length,total,TOTAL;
		/* total: total pattern number */
	double c_rate, m_rate,criti; /* crossover and mutate rate */
	int i,j,te;    /* te: flag for termination (1) */
	int     ind;    /* index for the best fitness */
	double max,mean,worst;
	int	 m_t;
	int flag_m;     /* flag for mutatation, 1, variable, 0 cons */
	int flag_c;		/* 0: one, 1: uniform, 2: two */
	int fit_shift;  /* shift fitness, 1:yes, 0:no */
	int true;
	char condition;
	double *gau;    /* store gaussian function value */
	double vari;	/* variance value of fitness vector */
	double rm_rate;	/* real mutate probability */

	FILE *fp1;

	extern void initiali(int **,int,int);
	extern void fitness(int **,double *,int,int,double **,double **,
			int,int,int,int,int,int *, char *,char *,double,int,int);
	extern void selectio(int **,double *,int,int,int,int);
	extern void crossove(int **,int,int,double,int,int);
	extern void Bmutate(int *,double,int,int,int,double *);

	extern int maximum(double *,int);
	extern double average(double *,int);
	extern double minimial(double *,int);
	extern double gaussian(double);
	extern double variance(double *,double,int);

	
	int getParams(char *,char *,char *,char *, int *,
					int *,int *,int *,int *,int *,int *,int *,
					double *,double *,double *,int *,int *,int *,
					int *);
	void savePara(FILE *,char *,char *,char *,char *, int ,
					int,int,int,int,int,int,int ,int,
					double,double,double,int,int,int,
					int);
	int getPattern(char *,double **,double **,int *,int,int,int);
	/* get parameters from runFile */

	int c_break(void);


	begin=time(NULL);

	status=getParams(datFile,patternFile,weightFile,resultFile,
					&H,&iter,&K,&N,&P,&M,&total,&popsize,&c_rate,&m_rate,
					&criti,&flag_m,&fit_shift,&m_t,&flag_c);
	if (status!=1)
	{
		printf("something wrong with open %s\n",datFile);
		exit(1);
	}

	if (M>total)
	{
		printf("training patterns should be less than total patterns\n");
		exit(1);
	}

	length=((N+1)*H+(H+1)*P)*K;      /* length of indiviudal */

	savePara(stderr,datFile,patternFile,weightFile,resultFile,
					H,iter,K,N,P,M,total,popsize,length,c_rate,m_rate,
					criti,flag_m,fit_shift,m_t,flag_c);

	do
	{
		printf("check, then selection, c: continue; q:quit\n");
		scanf("%c",&condition);
		switch(condition)
		{
			case 'c': true=0;
				break;
			case 'C': true=0;
				break;
			case 'q': exit(1);
			case 'Q': exit(1);
			default: true=1;

		}
	}
	while (true==1);

	/* assign space to matrix and vector */

	pattern=(double **)calloc(total,sizeof(double *));
	for (i=0;i<total;i++)
		pattern[i]=(double *)calloc(N,sizeof(double));

	target=(double **)calloc(total,sizeof(double *));
	for (i=0;i<total;i++)
		target[i]=(double *)calloc(P,sizeof(double));

	population=(int **)calloc(popsize,sizeof(int *));
	for (i=0;i<popsize;i++)
		population[i]=(int *)calloc(length,sizeof(int));

	fit=(double *)calloc(popsize,sizeof(double));

	gau=(double *)calloc(K,sizeof(double));

	/* obtain training pattern pair from pattern file */
	status=getPattern(patternFile,pattern,target,&TOTAL,N,P,total);

	if (status!=1)
	{
		printf("something wrong with open %s\n",patternFile);
		exit(1);
	}

	/* begin generation  */

	/* itilialization of population */
	initiali(population,popsize,length);


	/* calculate Gaussian fun. as mutation probability */

	for (i=0;i<K;i++)
		gau[i]=gaussian(sqrt(i));

	/* initialize graphics and local variables */
	initgraph(&gdriver,&gmode,"");

	/* read result of initialization */
	errorcode=graphresult();
	if (errorcode !=grOk)
	{
		/* an error occurred */
		printf("Graphics error: %s\n",grapherrormsg(errorcode));
		exit(1);
	}

	ctrlbrk(c_break);
	/* draw x-y */
	line(50,80,50,400);
	line(50,400,500,400);
	prex=50;
	bprey=400;
	mprey=400;
	wprey=400;
	vprey=400;
	moveto(40,80);
	outtext("1");
	moveto(50,70);
	outtext("fitness");
	moveto(25,240);
	outtext("0.5");
	moveto(45,405);
	outtext("0");
	moveto(505,390);
	outtext("generation");
	moveto(500,405);
	sprintf(Msg,"%d",iter);
	outtext(Msg);
	moveto(275,405);
	sprintf(Msg,"%d",iter/2);
	outtext(Msg);
	moveto(500,80);
	setcolor(RED);
	sprintf(Msg,"Best    : ----");
	outtext(Msg);
	moveto(500,110);
	setcolor(YELLOW);
	sprintf(Msg,"Mean    : ----");
	outtext(Msg);
	moveto(500,140);
	setcolor(BLUE);
	sprintf(Msg,"Worst   : ----");
	outtext(Msg);
	moveto(500,170);
	setcolor(WHITE);
	sprintf(Msg,"Variance: ----");
	outtext(Msg);

/*	maxcolor=getmaxcolor();

	moveto(500,200);
	ystep=0;
	for (i=0;i<=maxcolor;i++)
	{
		if (getx()>630)
		{
			ystep++;
			moveto(500,(200+ystep*20));
		}
		setcolor(i);
		sprintf(Msg,"%d ",i);
		outtext(Msg);

	}
*/

	gotoxy(5,2);
	printf(" Index     Best      Mean       Worst     Variance ");

	te=0;
	for (i=0;i<=iter;i++)
	{
		fitness(population,fit,popsize,length,pattern,target,N,H,P,K,M,
				&te,weightFile,resultFile,criti,total,i);

		if ((te==1)||((i%10)==0))
		{
			ind=maximum(fit,popsize);
			max=fit[ind];
			mean=average(fit,popsize);
			worst=minimial(fit,popsize);
			vari=variance(fit,mean,popsize);
			temp=(450*1.0)/iter;
			temp *=i;
			curx =50+(int)temp;
			bcury=400-(int)((400-80)*max);
			mcury=400-(int)((400-80)*mean);
			wcury=400-(int)((400-80)*worst);
			vcury=400-(int)((400-80)*vari);
			gotoxy(5,3);
			printf(" %4.4d  %10.6f %10.6f %10.6f %10.6f  ",i,max,mean,worst,vari);
			if (i!=0)
			{
				setcolor(RED);
				line(prex,bprey,curx,bcury);
				setcolor(YELLOW);
				line(prex,mprey,curx,mcury);
				setcolor(BLUE);
				line(prex,wprey,curx,wcury);
				setcolor(WHITE);
				line(prex,vprey,curx,vcury);
			}
			prex=curx;
			bprey=bcury;
			mprey=mcury;
			wprey=wcury;
			vprey=vcury;
		}

		if ((te==1)||(i==iter))
		{
			gotoxy(5,4);
			printf(" completed\t");
			if ((fp1=fopen(resultFile,"a"))==NULL)
			{
				fprintf(stderr,"cannot open %s for writing\n",resultFile);
				exit(1);
			}
			savePara(fp1,datFile,patternFile,weightFile,resultFile,
					H,iter,K,N,P,M,total,popsize,length,c_rate,m_rate,
					criti,flag_m,fit_shift,m_t,flag_c);

			fprintf(fp1,"generation: %d\n",i);
			fprintf(fp1,"begin time at: %s\n",ctime(&begin));
			finish=time(NULL);
			fprintf(fp1,"finish time at: %s\n",ctime(&finish));
			fclose(fp1);


			printf(" Press any key to quit");
			getch();
			closegraph();
			exit(1);
		}

		selectio(population,fit,popsize,length,ind,fit_shift);

		crossove(population,length,popsize,c_rate,ind,flag_c);

		rm_rate=m_rate;
		if (m_t==1)
		{
			mean=average(fit,popsize);
			vari=variance(fit,mean,popsize);
			if (vari<0.05)
			{
				status=(int)((0.05-vari)*100) +1;
				rm_rate=status*m_rate;
			}
		}

		for (j=0;j<popsize;j++)
		{
			if (j!=ind)
				Bmutate(population[j],rm_rate,length,K,flag_m,gau);
		}
	}
	/* release the asigned space */
	for (i=0;i<total;i++)
	{
		free(pattern[i]);
		free(target[i]);
	}
	free(pattern);
	free(target);
	free(fit);
	for (i=0;i<popsize;i++)
		free(population[i]);
	free(population);
	free(gau);

	/* clean up */
	gotoxy(5,4);
	printf(" Press any key to quit");
	getch();
	closegraph();

}

int
getParams(char *fileName,char *pFileName,char *wFileName,char *eFileName,
				 int *h,int *cycle,int *k,int *n,int *p,
				 int *m,int *total,int *p_size, double *c_rate,
				 double *m_rate,double *cri,int *f_m,
				 int *f_s,int *m_t,int *flag_c)
/* char *fileName;
char *pFileName;
char *wFileName;
char *eFileName;
int  *h;
int     *cycle;
int     *k;
int     *n;
int     *p;
int     *m;
int     *p_size;
double *c_rate;
double *m_rate;
double *cri; */
{
	FILE    *fp;

	if ((fp=fopen(fileName,"rt"))==NULL)
	{
		fprintf(stderr,"cannot open %s file \n",fileName);
		return 0;
	}


	if (fscanf(fp,"%s",pFileName)==NULL)
	{
		fprintf(stderr,"Error reading patternFileName in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%s",wFileName)==NULL)
	{
		fprintf(stderr,"Error reading weightFileName in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%s",eFileName)==NULL)
	{
		fprintf(stderr,"Error reading errorFileName in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",h)==NULL)
	{
		fprintf(stderr,"Error reading H in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",cycle)==NULL)
	{
		fprintf(stderr,"Error reading Iteration in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",k)==NULL)
	{
		fprintf(stderr,"Error reading K in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",n)==NULL)
	{
		fprintf(stderr,"Error reading N in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",p)==NULL)
	{
		fprintf(stderr,"Error reading P in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",m)==NULL)
	{
		fprintf(stderr,"Error reading M in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",total)==NULL)
	{
		fprintf(stderr,"Error reading total in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",p_size)==NULL)
	{
		fprintf(stderr,"Error reading popsize in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%lf",c_rate)==NULL)
	{
		fprintf(stderr,"Error reading c_rate in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%lf",m_rate)==NULL)
	{
		fprintf(stderr,"Error reading m_rate in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%lf",cri)==NULL)
	{
		fprintf(stderr,"Error reading crition in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",f_m)==NULL)
	{
		fprintf(stderr,"Error reading flag_m in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",f_s)==NULL)
	{
		fprintf(stderr,"Error reading fit_shift in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",m_t)==NULL)
	{
		fprintf(stderr,"Error reading m_t in file %s\n",fileName);
		return 0;
	}

	if (fscanf(fp,"%d",flag_c)==NULL)
	{
		fprintf(stderr,"Error reading flag_c in file %s\n",fileName);
		return 0;
	}
	fclose(fp);

	return 1;
}

void
savePara(FILE * ff,char *fileName,char *pFileName,char *wFileName,char *eFileName,
				 int h,int cycle,int k,int n,int p,
				 int m,int total,int p_size,int len, double c_rate,
				 double m_rate,double cri,int f_m,
				 int f_s,int m_t,int flag_c)
{
	fprintf(ff,"\tdataFile ...................%s\n",fileName);
	fprintf(ff,"\tpatternFile ................%s\n",pFileName);
	fprintf(ff,"\tweightFile .................%s\n",wFileName);
	fprintf(ff,"\tresultFile .................%s\n",eFileName);
	fprintf(ff,"\tH (number of hidden) .......%d\n",h);
	fprintf(ff,"\titer (generation) ..........%d\n",cycle);
	fprintf(ff,"\tK (K bits for eachPara).....%d\n",k);
	fprintf(ff,"\tN (input dim) ..............%d\n",n);
	fprintf(ff,"\tP (output dim) .............%d\n",p);
	fprintf(ff,"\tM (total training pats) ....%d\n",m);
	fprintf(ff,"\ttotal (total pats) .........%d\n",total);
	fprintf(ff,"\tpopsize ....................%d\n",p_size);
	fprintf(ff,"\tlength .....................%d\n",len);
	fprintf(ff,"\tc_rate (crossover) .........%f\n",c_rate);
	fprintf(ff,"\tm_rate (mutation) ..........%f\n",m_rate);
	fprintf(ff,"\tcriti (mean square) ........%f\n",cri);
	fprintf(ff,"\tflag_m (1:var;0:cons) ......%d\n",f_m);
	fprintf(ff,"\tfit_shift (1:yes,0:no) .....%d\n",f_s);
	fprintf(ff,"\tm_t (m_rate(t), 1:y,0:n) ...%d\n",m_t);
	fprintf(ff,"\tflag_c (0:one,1:unif,2:two).%d\n",flag_c);

}


int getPattern(char *fileName,double **in,double **out,int *TOTAL,int n,int p,int total)
/* char *fileName;
double  **in;
double  **out;
int     *TOTAL;
int     n;
int     p;
int     total; */
{

	FILE *fp;

	int i,j;

	if ((fp=fopen(fileName,"rt"))==NULL)
	{
		fprintf(stderr,"Error opening %s\n",fileName);
		return 0;
	}

	fscanf(fp,"%d",TOTAL);

	if(total !=(*TOTAL))
	{
		fprintf(stderr,"total patterns in %s file not match\n",fileName);
		return 0;
	}



	for (i=0;i<total;i++)
	{
		for (j=0;j<n;j++)
			fscanf(fp,"%lf",&(in[i][j]));
		for (j=0;j<p;j++)
			fscanf(fp,"%lf",&(out[i][j]));
	}
	fclose(fp);

	return 1;
}

int c_break(void)
{
	closegraph();
	return 0;
}