遗传算法-SGA代码实现

#include
#include
#include
#include
#include
/* 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 */

/* 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);
int 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量*/
	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];
	printf("种群大小(20-100): ");
	scanf("%d",&popsize);
	if((popsize%2) != 0)
	{
		fprintf(outfp, "种群大小已设置为偶数\n");
		popsize++;
	}
	printf("染色体长度(8-40):");
	scanf("%d", &lchrom);
	printf("是否输出染色体编码(y/n):");
	printstrings = 1;
	scanf("%s", &answer);
	if(strncmp(answer,"n",1) == 0)
		printstrings = 0;
	printf("最大世代数(100-300):");
	scanf("%d", &maxgen);
	printf("交叉率(0.2-0.9):");
	scanf("%f", &pcross);
	printf("变异率(0.01-0.1):");
	scanf("%f",&pmutation);
}

void initpop()   /*随机初始化种群*/
{
	int j,j1, k,stop;
	unsigned mask = 1;
	for(j=0; j 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,"-", 88);
	skip(outfp,1);
}


void writepop()
{
	struct individual *pind;
	int j;
	for(j=0; jchrom);
		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(unsigned *chrom)    /*输出染色体编码*/
{
	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> 1;
		}
	}
}

void  preselect()
{
	int j;
	sumfitness = 0;
	for(j=0; j< popsize; j++)
		sumfitness +=oldpop[j].fitness;

}

int select()    /*轮盘赌选择*/
{
	extern float randomperc();
	float sum, pick;
	int i;
	pick = randomperc();
	sum = 0;
	if(sumfitness != 0)
	{
		for(i=0; (sum max)
			max = pop[j].fitness;
		if(pop[j].fitness < min)
			min = pop[j].fitness;
		/*new global best -fit individual */
		if(pop[j].fitness > bestfit.fitness)
		{
			for(i=0; i< chromsize; i++)
				bestfit.chrom[i] = pop[j].chrom[i];
			bestfit.fitness = pop[j].fitness;
			bestfit.varible = pop[j].varible;
			bestfit.generation = gen;
		}
	}
	/*计算平均适应度*/
	avg = sumfitness/popsize;
}


void  title()
{
	//printf("基本遗传算法");
}

void repchar(FILE *outfp, char *ch, int repcount)
{
	int j;
	for(j=1; j<= repcount; j++)
		fprintf(outfp, "%s", ch);
}

void skip(FILE *fp, int skipcount)    //换行数
{
	int j;
	for(j=1; j<= skipcount; j++)
		fprintf(outfp,"\n");
}

void objfunc(struct individual *critter)   /*计算适应度函数值*/
{
	unsigned mask = 1;
	unsigned bitpos;
	unsigned tp;
	double  bitpow;
	int j,k, stop;
	critter->varible = 0.0;
	for(k=0; k< chromsize; k++)
	{
		if( k== (chromsize-1))
			stop = lchrom -k*(8*sizeof(unsigned));
		else
			stop = 8*sizeof(unsigned);
		tp = critter->chrom[k];
		for(j=0; j< stop; j++)
		{
			bitpos = j+(8*sizeof(unsigned)) *k;
			if((tp & mask) == 1)
			{
				bitpow =(unsigned) pow(2.0, (double)bitpos);
				critter->varible = critter->varible+bitpow;
			}
			tp = tp >> 1;
		}

	}
    //这里目标函数采用函数f(x)=xsin(10πx)+2
	critter->varible = -1 + critter->varible*3/(pow(2.0,(double)lchrom) -1);
	critter->fitness = critter->varible*sin(critter->varible*10*atan(1)*4 )+ 2.0;
}


void mutation(unsigned *child)   /*变异操作*/
{
	int j,k,stop;
	unsigned mask, tmp =1 ;
	for(k=0; k= k*(8*sizeof(unsigned)))
			{
				child1[k-1] = parent1[k-1];
				child2[k-1] = parent2[k-1];
			}
			else if((jcross <(k*(8*sizeof(unsigned)))) && (jcross >((k-1)*(8*sizeof(unsigned)))))
			{
				mask = 1;
				for(j=1; j<=(jcross-1-((k-1)*(8*sizeof(unsigned)))); j++)
				{
					temp = 1;
					mask = mask << 1;
					mask = mask | temp;
				}
				child1[k-1] = (parent1[k-1] & mask )|(parent2[k-1]&(~mask));
				child2[k-1] = (parent1[k-1] & (~mask) )|(parent2[k-1]&mask);
			}
			else
			{
				child1[k-1] = parent2[k-1];
				child2[k-1] = parent1[k-1];
			}
		}
	}
	else
	{
		for(k=0; k< chromsize; k++)
		{
			child1[k] = parent1[k];
			child2[k] = parent2[k];
		}
		jcross = 0;
	}
	return jcross;
}


void advance_random()   /*产生55个随机数*/
{
	int j1;
	double new_random;
	for(j1 = 0; j1<24; j1++)
	{
		new_random = oldrand[j1] - oldrand[j1+31];
		if(new_random< 0.0)
			new_random = new_random + 1.0;
		oldrand[j1] = new_random;
	}
	for(j1 = 24; j1<55; j1++)
	{
		new_random = oldrand[j1] - oldrand[j1-24];
		if(new_random<0.0)
			new_random = new_random +1.0;
		oldrand[j1] = new_random;
	}
}

int flip(float prob)   /*以一定概率产生0 或 1*/
{
	float radomperc();
	if(randomperc() <= prob)
		return (1);
	else
		return (0);
}


void randomize( )   /*设定随机数种子并初始化随机数发生器*/
{
	float randomseed;
	int j1;
	for(j1 = 0; j1<=54; j1++)
		oldrand[j1] = 0.0;
	jrand = 0;
	do
	{
		printf("随机数种子[0-1]:");
		scanf("%f", &randomseed);
	}while((randomseed<0.0) || (randomseed > 1.0));
	warmup_random(randomseed);
}

double randomnormaldeviate()      /*产生随机标准差*/
{
	double t,rndx1;
	if(rndcalcflag)
	{
		rndx1 = sqrt(-2.0*log((double) randomperc()));
		t = 6.2831853072*(double)randomperc();
		rndx2 = rndx1 *sin(t);
		rndcalcflag = 0;
		return rndx1*cos(t);
	}
	else
	{
		rndcalcflag = 1;
		return rndx2;
	}
}

float randomperc()   /*与库函数random()作用相同,产生[0,1]之间一个随机数*/
{
	jrand ++;
	if(jrand >= 55)
	{
		jrand = 1;
		advance_random();
	}
	return ((float)oldrand[jrand]);
}

int rnd(int low,int high)  /*在整数low和high之间产生一个随机数*/
{
	int i;
	float randomperc();
	if(low >= high)
		i = low;
	else
	{
		i = (int)(randomperc()*(high - low +1)) + low;
		if(i> high)
			i = high;
	}

	return i;
}

void warmup_random(float random_seed)   /*初始化随机数发生器*/
{
	int j1, ii;
	double new_random, prev_random;

	oldrand[54] = random_seed;
	new_random = 0.000000001;
	prev_random = random_seed;
	for(j1 = 1; j1<= 54; j1++)
	{
		ii = (21*j1)%54;
		oldrand[ii] = new_random;
		new_random = prev_random-new_random;
		if(new_random <0.0) new_random = new_random + 1.0;
		prev_random = oldrand[ii];
	}
	advance_random();
	advance_random();
	advance_random();
	jrand = 0;
}

int main()
{
	struct individual *temp;

	/*if(2 > argc)
	{
		printf("缺少输出文件参数\n");
		exit(-1);
	}*/

	/*if((outfp = fopen(argv[1], "w")) == NULL)
	{
		fprintf(stderr,"Cannot open output file %s\n", argv[1]);
		exit(-1);
	}*/
	printf("输入遗传算法执行次数(1-5):");
	scanf("%d", &maxruns);
	for(run =1; run <= maxruns; run ++)
	{
		initialize();
		for(gen = 0; gen

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