sga_auto.c.c

本压缩包内有三个遗传算法文件

/**********************************************************************/
/*        基于基本遗传算法的自适应遗传优化算法函数最优化   SGA_AUTO.C */
/*     A Function Optimizer using Simple Genetic Algorithm            */
/* developed from the Pascal SGA code presented by David E.Goldberg   */
/**********************************************************************/
#include <stdio.h>
#include <math.h>
/* 全局变量 */
struct individual                       /* 个体*/
{
    unsigned *chrom;                    /* 染色体 */
    double   fitness;                   /* 个体适应度*/
    double   varible;                   /* 个体对应的变量值*/   
    int      xsite;                     /* 交叉位置 */
    int      parent[2];                 /* 父个体  */
    int      *utility;                  /* 特定数据指针变量 */
};
struct bestever                         /* 最佳个体*/
{
    unsigned *chrom;                    /* 最佳个体染色体*/
    double   fitness;                   /* 最佳个体适应度 */
    double   varible;                   /* 最佳个体对应的变量值 */
    int      generation;                /* 最佳个体生成代 */
};
 struct individual *oldpop;             /* 当前代种群 */
 struct individual *newpop;             /* 新一代种群 */
 struct bestever bestfit;               /* 最佳个体 */
 double sumfitness;                     /* 种群中个体适应度累计 */
 double max;                            /* 种群中个体最大适应度 */
 double avg;                            /* 种群中个体平均适应度 */
 double min;                            /* 种群中个体最小适应度 */
 float  pcross;                         /* 交叉概率 */
 float  pmutation;                      /* 变异概率 */
 int    popsize;                        /* 种群大小  */
 int    lchrom;                         /* 染色体长度*/
 int    chromsize;                      /* 存储一染色体所需字节数 */
 int    gen;                            /* 当前世代数 */
 int    maxgen;                         /* 最大世代数   */
 int    run;                            /* 当前运行次数 */
 int    maxruns;                        /* 总运行次数   */
 int    printstrings;                   /* 输出染色体编码的判断，0 -- 不输出, 1 -- 输出 */
 int    nmutation;                      /* 当前代变异发生次数 */
 int    ncross;                         /* 当前代交叉发生次数 */
 float	pc1;
 float	pc2;
 float	pm1;
 float	pm2;
 int	temp_mate1;
 int	temp_mate2;
/* 随机数发生器使用的静态变量 */
static double oldrand[55];
static int jrand;
static double rndx2;
static int rndcalcflag;
/* 输出文件指针 */
FILE *outfp ;
/* 函数定义 */
void advance_random();
int flip(float);rnd(int, int);
void randomize();
double randomnormaldeviate();
float randomperc(),rndreal(float,float);
void warmup_random(float);
void initialize(),initdata(),initpop();
void initreport(),generation(),initmalloc();
void freeall(),nomemory(char *),report();
void writepop(),writechrom(unsigned *);
void preselect();
void statistics(struct individual *);
void title(),repchar (FILE *,char *,int);
void skip(FILE *,int);
int select();
void objfunc(struct individual *);
int crossover (unsigned *, unsigned *, unsigned *, unsigned *);
void mutation(unsigned *);


void initialize()      /* 遗传算法初始化 */
{
    /* 键盘输入遗传算法参数 */
    initdata();
    /* 确定染色体的字节长度 */
    chromsize = (lchrom/(8*sizeof(unsigned)));
    if(lchrom%(8*sizeof(unsigned))) chromsize++;
    /*分配给全局数据结构空间 */
    initmalloc();
    /* 初始化随机数发生器 */
    randomize();
    /* 初始化全局计数变量和一些数值*/
    nmutation = 0;
    ncross = 0;
    bestfit.fitness = 0.0;
    bestfit.generation = 0;
    /* 初始化种群，并统计计算结果 */
    initpop();
    statistics(oldpop);
    initreport();
}

void initdata()           /* 遗传算法参数输入 */
{
   char  answer[2];
    popsize=30;
    if((popsize%2) != 0)
      {
	fprintf(outfp, "种群大小已设置为偶数\n");
	popsize++;
      };
   lchrom=22;
   printstrings=1;
   maxgen=150;
   pcross=0.8;
   pc1=0.8;
   pc2=0.6;
   pmutation=0.05;
   pm1=0.05;
   pm2=0.005;
}

void initpop()           /* 随机初始化种群 */
{
    int j, j1, k, stop;
    unsigned mask = 1;
    for(j = 0; j < popsize; j++)
    {
        for(k = 0; k < chromsize; k++)
        {
            oldpop[j].chrom[k] = 0;
            if(k == (chromsize-1))
                stop = lchrom - (k*(8*sizeof(unsigned)));
            else
                stop =8*sizeof(unsigned);
            for(j1 = 1; j1 <= stop; j1++)
            {
               oldpop[j].chrom[k] = oldpop[j].chrom[k]<<1;
               if(flip(0.5))
                  oldpop[j].chrom[k] = oldpop[j].chrom[k]|mask;
            }
        }
        oldpop[j].parent[0] = 0;     /* 初始父个体信息 */
        oldpop[j].parent[1] = 0;
        oldpop[j].xsite = 0;
        objfunc(&(oldpop[j]));       /* 计算初始适应度*/
    }
}

void initreport()               /* 初始参数输出 */
{
    void   skip();
    skip(outfp,1);
    fprintf(outfp,"             基本遗传算法参数\n");
    fprintf(outfp," -------------------------------------------------\n");
    fprintf(outfp,"    种群大小(popsize)     =   %d\n",popsize);
    fprintf(outfp,"    染色体长度(lchrom)    =   %d\n",lchrom);
    fprintf(outfp,"    最大进化代数(maxgen)  =   %d\n",maxgen);
    fprintf(outfp,"    交叉概率(pcross)      =   %f\n",pcross);
    fprintf(outfp,"    变异概率(pmutation)   =   %f\n",pmutation);
    fprintf(outfp," -------------------------------------------------\n");
    skip(outfp,1);
    fflush(outfp);
}

void generation()
{
  int mate1, mate2, jcross, j = 0;
  /*  每代运算前进行预选 */
  preselect();
  /* 选择, 交叉, 变异 */
  do
    {
      /* 挑选交叉配对 */
      mate1 = select();
	  temp_mate1 = mate1;
      mate2 = select();
	  temp_mate2 = mate2;
      /* 交叉和变异 */
      jcross = crossover(oldpop[mate1].chrom, oldpop[mate2].chrom, newpop[j].chrom, newpop[j+1].chrom);
      /* 自适应变异概率 */
	  if(gen!=0)
	  {
		if(newpop[j].fitness>=avg)
			pmutation = pm1-(pm1-pm2)*(max-newpop[j].fitness)/(max-avg);
		else
			pmutation = pm1;
	  }
	  mutation(newpop[j].chrom);
	  if(gen!=0)
	  {
		if(newpop[j+1].fitness>=avg)
			pmutation = pm1-(pm1-pm2)*(max-newpop[j+1].fitness)/(max-avg);
		else
			pmutation = pm1;
	  }
      mutation(newpop[j+1].chrom);
      /* 解码, 计算适应度 */
      objfunc(&(newpop[j]));
      /*记录亲子关系和交叉位置 */
      newpop[j].parent[0] = mate1+1;
      newpop[j].xsite = jcross;
      newpop[j].parent[1] = mate2+1;
      objfunc(&(newpop[j+1]));
      newpop[j+1].parent[0] = mate1+1;
      newpop[j+1].xsite = jcross;
      newpop[j+1].parent[1] = mate2+1;
      j = j + 2;
    }
  while(j < (popsize-1));

}

void initmalloc()              /*为全局数据变量分配空间 */
{
  unsigned nbytes;
  char  *malloc();
  int j;
  /* 分配给当前代和新一代种群内存空间 */
  nbytes = popsize*sizeof(struct individual);
  if((oldpop = (struct individual *) malloc(nbytes)) == NULL)
    nomemory("oldpop");
  if((newpop = (struct individual *) malloc(nbytes)) == NULL)
    nomemory("newpop");
  /* 分配给染色体内存空间 */
  nbytes = chromsize*sizeof(unsigned);
  for(j = 0; j < popsize; j++)
    {
      if((oldpop[j].chrom = (unsigned *) malloc(nbytes)) == NULL)
	nomemory("oldpop chromosomes");
      if((newpop[j].chrom = (unsigned *) malloc(nbytes)) == NULL)
	nomemory("newpop chromosomes");
    }
  if((bestfit.chrom = (unsigned *) malloc(nbytes)) == NULL)
    nomemory("bestfit chromosome");

}

void freeall()               /* 释放内存空间 */
{
  int i;
   for(i = 0; i < popsize; i++)
    {
      free(oldpop[i].chrom);
      free(newpop[i].chrom);
    }
  free(oldpop);
  free(newpop);
  free(bestfit.chrom);
   }

void nomemory(string)        /* 内存不足，退出*/
  char *string;
{
  fprintf(outfp,"malloc: out of memory making %s!!\n",string);
  exit(-1);
}

void report()                /* 输出种群统计结果 */
{
    void  repchar(), skip();
    void  writepop(), writestats();
    repchar(outfp,"-",80);
    skip(outfp,1); 
    if(printstrings == 1)
    {
        repchar(outfp," ",((80-17)/2));
        fprintf(outfp,"模拟计算统计报告  \n");
        fprintf(outfp, "世代数 %3d", gen);
        repchar(outfp," ",(80-28));
        fprintf(outfp, "世代数 %3d\n", (gen+1));
        fprintf(outfp,"个体  染色体编码");
        repchar(outfp," ",lchrom-5);
        fprintf(outfp,"适应度    父个体 交叉位置  ");
        fprintf(outfp,"染色体编码 ");
        repchar(outfp," ",lchrom-5);
        fprintf(outfp,"适应度\n");
        repchar(outfp,"-",80);
        skip(outfp,1);
        writepop(outfp);
        repchar(outfp,"-",80);
        skip(outfp,1);
     }
    fprintf(outfp,"第 %d 代统计: \n",gen);
    fprintf(outfp,"总交叉操作次数 = %d, 总变异操作数 = %d\n",ncross,nmutation);
    fprintf(outfp," 最小适应度：%f 最大适应度：%f  平均适应度 %f\n", min,max,avg);
    fprintf(outfp," 迄今发现最佳个体 =>  所在代数： %d  ", bestfit.generation);
    fprintf(outfp," 适应度：%f  染色体：", bestfit.fitness);
    writechrom((&bestfit)->chrom);
    fprintf(outfp," 对应的变量值: %f", bestfit.varible);
    skip(outfp,1);
    repchar(outfp,"-",80);
    skip(outfp,1);  
}

void writepop()
{
    struct individual *pind;
    int j;
    for(j=0; j<popsize; j++)
    {
        fprintf(outfp,"%3d)  ",j+1);
        /* 当前代个体 */
        pind = &(oldpop[j]);
        writechrom(pind->chrom);
        fprintf(outfp,"  %8f | ", pind->fitness);
        /* 新一代个体 */
        pind = &(newpop[j]);
        fprintf(outfp,"(%2d,%2d)   %2d   ",
        pind->parent[0], pind->parent[1], pind->xsite);
        writechrom(pind->chrom);
        fprintf(outfp,"  %8f\n", pind->fitness);
    }
}

void writechrom(chrom)           /* 输出染色体编码 */
unsigned *chrom;
{
    int j, k, stop;
    unsigned mask = 1, tmp;
    for(k = 0; k < chromsize; k++)
    {
        tmp = chrom[k];
        if(k == (chromsize-1))
            stop = lchrom - (k*(8*sizeof(unsigned)));
        else
            stop =8*sizeof(unsigned);
        for(j = 0; j < stop; j++)
        {
            if(tmp&mask)
                fprintf(outfp,"1");
            else
                fprintf(outfp,"0");
            tmp = tmp>>1;
        }