一C++PSO（PSO）算法

#include <cstring>
#include <iostream>
#include <cmath>
#include <algorithm>
#include <ctime>

#define rand_01 ((float)rand() / (float)RAND_MAX)

const int numofdims = 30;
const int numofparticles = 50;

using namespace std;

//typedef void (*FitnessFunc)(float X[numofparticles][numofdims], float fitnesses[numofparticles]);

void fitnessfunc(float X[numofparticles][numofdims], float fitnesses[numofparticles])
{
memset(fitnesses, 0, sizeof (float) * numofparticles);
for(int i = 0; i < numofparticles; i++)
{
for(int j = 0; j < numofdims; j++)
{
fitnesses[i] += X[i][j] * X[i][j]; //(pow(X[i][j], 2));
}
}
}

void rosenBroekFunc(float X[numofparticles][numofdims], float fitnesses[numofparticles])
{
float x1, x2, t1, t2;
memset(fitnesses, 0, sizeof (float) * numofparticles);
for(int i = 0; i < numofparticles; i++)
for(int j = 0; j < numofdims - 1; j++)
{
x1 = X[i][j];
x2 = X[i][j+1];
t1 = (x2 - x1 * x1);
t1 *= t1;
t1 *= 100;
t2 = x1 - 1;
t2 *= t2;
fitnesses[i] = t1 + t2;
}
}

float mean(float inputval[], int vallength)
{
float addvalue = 0;
for(int i = 0; i < vallength; i++)
{
addvalue += inputval[i];
}
return addvalue / vallength;
}

void PSO(int numofiterations, float c1, float c2,
float Xmin[numofdims], float Xmax[numofdims], float initialpop[numofparticles][numofdims],
float worsts[], float meanfits[], float bests[], float *gbestfit, float gbest[numofdims])
{
float V[numofparticles][numofdims] = {0};
float X[numofparticles][numofdims];
float Vmax[numofdims];
float Vmin[numofdims];
float pbests[numofparticles][numofdims];
float pbestfits[numofparticles];
float fitnesses[numofparticles];
float w;
float minfit;
int   minfitidx;

memcpy(X, initialpop, sizeof(float) * numofparticles * numofdims);
fitnessfunc(X, fitnesses);
//rosenBroekFunc(X, fitnesses);

//    fp(X, fitnesses);
minfit = *min_element(fitnesses, fitnesses + numofparticles);
minfitidx = min_element(fitnesses, fitnesses + numofparticles) - fitnesses;
*gbestfit = minfit;
memcpy(gbest, X[minfitidx], sizeof(float) * numofdims);

//设置速度极限
for(int i = 0; i < numofdims; i++)
{
Vmax[i] = 0.2 * (Xmax[i] - Xmin[i]);
Vmin[i] = -Vmax[i];
}

for(int t = 0; t < 1000; t++)
{
w = 0.9 - 0.7 * t / numofiterations;

//计算个体历史极小值
for(int i = 0; i < numofparticles; i++)
{
if(fitnesses[i] < pbestfits[i])
{
pbestfits[i] = fitnesses[i];  //pbestfits初始化尚未赋值
memcpy(pbests[i], X[i], sizeof(float) * numofdims);
}
}
for(int i = 0; i < numofparticles; i++)
{
for(int j = 0; j < numofdims; j++)
{
V[i][j] = min(max((w * V[i][j] + rand_01 * c1 * (pbests[i][j] - X[i][j])
+ rand_01 * c2 * (gbest[j] - X[i][j])), Vmin[j]), Vmax[j]);
X[i][j] = min(max((X[i][j] + V[i][j]), Xmin[j]), Xmax[j]);
}
}

fitnessfunc(X, fitnesses);
//rosenBroekFunc(X, fitnesses);
minfit = *min_element(fitnesses, fitnesses + numofparticles);
minfitidx = min_element(fitnesses, fitnesses + numofparticles) - fitnesses;
if(minfit < *gbestfit)
{
*gbestfit = minfit;
//cout << "It=" << t << "->" << minfit << endl;
memcpy(gbest, X[minfitidx], sizeof(float) * numofdims);
}

worsts[t] = *max_element(fitnesses, fitnesses + numofparticles);
bests[t] = *gbestfit;
meanfits[t] = mean(fitnesses, numofparticles);
}

}

int main()
{
time_t t;
srand((unsigned) time(&t));

float xmin[30], xmax[30];
float initpop[50][30];
float worsts[1000], bests[1000];
float meanfits[1000];
float gbestfit;
float gbest[30];
for(int i = 0; i < 30; i++)
{
xmax[i] = 100;
xmin[i] = -100;
}
for(int i = 0; i < 50; i++)
for(int j = 0; j < 30; j++)
{
initpop[i][j] = rand() % (100 + 100 + 1) - 100;
}

PSO(1000, 2, 2, xmin, xmax, initpop, worsts, meanfits, bests, &gbestfit, gbest);

cout<<"fitness: " << gbestfit << endl;
for(int i = 0; i < 30; i++)
cout << gbest[i] << ", ";
cout << endl;

return 0;
}