C语言实现差分进化算法求z(i,j)=-20exp((0.2sqrt((x(i)^2+y(j)^2)/2)))-exp((cos(2pix(i))+cos(2piy(j)))/2)+exp(1);的最小值，x属于-5到5，y属于-5到5

差分进化算法是一种全局优化算法，可以用于求解非线性优化问题。下面是C语言实现差分进化算法求解z(i,j)=-20exp((0.2sqrt((x(i)^2+y(j)^2)/2)))-exp((cos(2pix(i))+cos(2piy(j)))/2)+exp(1);的最小值，x属于-5到5，y属于-5到5的代码示例：

#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>

#define NP 50 // 种群规模
#define F 0.7 // 缩放因子
#define CR 0.5 // 交叉概率
#define MAX_GENERATION 1000 // 最大迭代次数
#define EPSILON 1e-6 // 收敛精度

double randDouble(double a, double b) {
    return a + (b - a) * rand() / (RAND_MAX + 1.0);
}

double z(double x, double y) {
    return -20 * exp(-0.2 * sqrt(0.5 * (x * x + y * y))) - exp(0.5 * (cos(2 * M_PI * x) + cos(2 * M_PI * y))) + exp(1);
}

void init(double (*pop)[2]) {
    for (int i = 0; i < NP; ++i) {
        pop[i][0] = randDouble(-5, 5);
        pop[i][1] = randDouble(-5, 5);
    }
}

void mutate(double (*pop)[2], int r, double (*trial)[2]) {
    int a, b, c;
    do {
        a = rand() % NP;
    } while (a == r);
    do {
        b = rand() % NP;
    } while (b == r || b == a);
    do {
        c = rand() % NP;
    } while (c == r || c == a || c == b);

    for (int j = 0; j < 2; ++j) {
        trial[r][j] = pop[a][j] + F * (pop[b][j] - pop[c][j]);
    }
}

void crossover(double (*pop)[2], int r, double (*trial)[2]) {
    int j_rand = rand() % 2;
    for (int j = 0; j < 2; ++j) {
        if (randDouble(0, 1) < CR || j == j_rand) {
            trial[r][j] = pop[r][j];
        }
    }
}

void select(double (*pop)[2], double (*trial)[2]) {
    for (int i = 0; i < NP; ++i) {
        double f = z(trial[i][0], trial[i][1]);
        double f_old = z(pop[i][0], pop[i][1]);
        if (f < f_old) {
            pop[i][0] = trial[i][0];
            pop[i][1] = trial[i][1];
        }
    }
}

int main() {
    srand(time(NULL));

    double pop[NP][2];
    double trial[NP][2];

    init(pop);

    for (int gen = 0; gen < MAX_GENERATION; ++gen) {
        for (int i = 0; i < NP; ++i) {
            mutate(pop, i, trial);
            crossover(pop, i, trial);
        }
        select(pop, trial);

        double f_best = z(pop[0][0], pop[0][1]);
        for (int i = 1; i < NP; ++i) {
            double f = z(pop[i][0], pop[i][1]);
            if (f < f_best) {
                f_best = f;
            }
        }

        printf("generation: %d, best: %.6f\n", gen, f_best);

        if (f_best < EPSILON) {
            printf("converged!\n");
            break;
        }
    }

    printf("x: %.6f, y: %.6f, z: %.6f\n", pop[0][0], pop[0][1], z(pop[0][0], pop[0][1]));
}

在该代码中，init函数用于初始化种群，mutate函数用于进行变异操作，crossover函数用于进行交叉操作，select函数用于选择操作。在主函数中，我们反复进行变异、交叉和选择操作，直到满足收敛精度或达到最大迭代次数为止。最终，输出最优解以及对应的函数值。