灰狼优化算法C语言代码

灰狼优化算法的C语言代码如下所示[^1]：

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

#define N 30 // 灰狼个体数
#define D 10 // 问题维度
#define MAX_ITER 100 // 最大迭代次数

// 定义灰狼结构体
typedef struct {
    double position[D]; // 灰狼位置
    double fitness; // 适应度值
} Wolf;

// 计算适应度函数
double fitnessFunction(double position[]) {
    // TODO: 根据具体问题定义适应度函数
    // 返回适应度值
}

// 初始化灰狼个体
void initialize(Wolf wolves[]) {
    for (int i = 0; i < N; i++) {
        for (int j = 0; j < D; j++) {
            // TODO: 根据具体问题初始化灰狼位置
        }
        wolves[i].fitness = fitnessFunction(wolves[i].position);
    }
}

// 更新灰狼位置
void updatePosition(Wolf wolves[], double a, double A, double C, double l, double u) {
    for (int i = 0; i < N; i++) {
        for (int j = 0; j < D; j++) {
            double r1 = (double)rand() / RAND_MAX;
            double r2 = (double)rand() / RAND_MAX;
            double A1 = 2 * a * r1 - a;
            double C1 = 2 * r2;
            double D_alpha = fabs(C * wolves[i].position[j] - wolves[0].position[j]);
            double X1 = wolves[0].position[j] - A1 * D_alpha;

            r1 = (double)rand() / RAND_MAX;
            r2 = (double)rand() / RAND_MAX;
            double A2 = 2 * a * r1 - a;
            double C2 = 2 * r2;
            double D_beta = fabs(C * wolves[i].position[j] - wolves[0].position[j]);
            double X2 = wolves[0].position[j] - A2 * D_beta;

            r1 = (double)rand() / RAND_MAX;
            r2 = (double)rand() / RAND_MAX;
            double A3 = 2 * a * r1 - a;
            double C3 = 2 * r2;
            double D_delta = fabs(C * wolves[i].position[j] - wolves[0].position[j]);
            double X3 = wolves[0].position[j] - A3 * D_delta;

            wolves[i].position[j] = (X1 + X2 + X3) / 3;
            if (wolves[i].position[j] < l) {
                wolves[i].position[j] = l;
            }
            if (wolves[i].position[j] > u) {
                wolves[i].position[j] = u;
            }
        }
        wolves[i].fitness = fitnessFunction(wolves[i].position);
    }
}

// 寻找最优解
void findOptimalSolution() {
    Wolf wolves[N];
    double a = 2; // 衰减系数
    double A = 2; // 陷阱参数
    double C = 1; // 收缩系数
    double l = -10; // 位置下界
    double u = 10; // 位置上界

    initialize(wolves);

    for (int iter = 0; iter < MAX_ITER; iter++) {
        updatePosition(wolves, a, A, C, l, u);
        // TODO: 根据具体问题更新陷阱参数A和衰减系数a
    }

    // 寻找最优解
    double bestFitness = wolves[0].fitness;
    int bestIndex = 0;
    for (int i = 1; i < N; i++) {
        if (wolves[i].fitness < bestFitness) {
            bestFitness = wolves[i].fitness;
            bestIndex = i;
        }
    }

    // 输出最优解
    printf("Optimal solution: ");
    for (int j = 0; j < D; j++) {
        printf("%lf ", wolves[bestIndex].position[j]);
    }
    printf("\n");
}

int main() {
    findOptimalSolution();
    return 0;
}