📄 gasample.cpp
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{ 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 < pick) && (i < popsize); i++) sum += (float)(oldpop[i].fitness/sumfitness); } else i = rnd(1,popsize); return(i-1);}void statistics(struct individual *pop) /* 计算种群统计数据 */{ int i, j; sumfitness = 0.0; min = pop[0].fitness; max = pop[0].fitness; /* 计算最大、最小和累计适应度 */ for(j = 0; j < popsize; j++) { sumfitness = sumfitness + pop[j].fitness; if(pop[j].fitness > 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("SGA Optimizer"); printf("基本遗传算法");}void repchar (FILE *outfp,char *ch,int repcount){ int j; for (j = 1; j <= repcount; j++) printf("%s", ch);}void skip(FILE *outfp,int skipcount){ int j; for (j = 1; j <= skipcount; j++) printf("\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 = pow(2.0,(double) bitpos); critter->varible = critter->varible + bitpow; } tp = tp>>1; } } 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, temp = 1; for(k = 0; k < chromsize; k++) { mask = 0; if(k == (chromsize-1)) stop = lchrom - (k*(8*sizeof(unsigned))); else stop = 8*sizeof(unsigned); for(j = 0; j < stop; j++) { if(flip(pmutation)) { mask = mask|(temp<<j); nmutation++; } } child[k] = child[k]^mask; }}int crossover (unsigned *parent1, unsigned *parent2, unsigned *child1, unsigned *child2)/* 由两个父个体交叉产生两个子个体 */{ int j, jcross, k; unsigned mask, temp; if(flip(pcross)) { jcross = rnd(1 ,(lchrom - 1));/* Cross between 1 and l-1 */ ncross++; for(k = 1; k <= chromsize; k++) { if(jcross >= (k*32)) { child1[k-1] = parent1[k-1]; child2[k-1] = parent2[k-1]; } else if((jcross < (k*32)) && (jcross > ((k-1)*32))) { mask = 1; for(j = 1; j <= (jcross-1-((k-1)*32)); 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 randomperc(); 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 sqrt(), log(), sin(), cos(); float randomperc(); 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之间产生一个随机整数*/{ 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;}void main(int argc,char *argv[]) /* 主程序 */{ struct individual *temp; // FILE *fopen(); void title(); char *malloc(); /* if((outfp = fopen(argv[1],"w")) == NULL) { printf("Cannot open output file %s\n",argv[1]); exit(-1); }*/ title(); 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<maxgen; gen++) { printf("\n第 %d / %d 次运行: 当前代为 %d, 共 %d 代\n", run,maxruns,gen,maxgen); /* 产生新一代 */ generation(); /* 计算新一代种群的适应度统计数据 */ statistics(newpop); /* 输出新一代统计数据 */ report(); temp = oldpop; oldpop = newpop; newpop = temp; } freeall(); }}
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