粒子羣算法（PSO）示例的C++實現

粒子羣算法的介紹和原理見最優化算法之粒子羣算法（PSO）

優化目標函數如下：

該目標函數可改爲其他函數，設定的粒子數N=3，迭代次數400次，慣性因子ω=0.9，學習因子c=2，參數可調。

使用C++優雅 實現該算法：

/**
An elegant implementation of pso(Particle Swarm Optimization) using C++11

Author@Larry King
*/

#include <vector>
#include <iostream>
#include <cmath>
#include <algorithm>
using namespace std;

// declaration
class pos;
class velocity;
float randomGenerator(float lowerBound, float upperBound);
int MAX_ITER = 400;
const int N = 3;
const float c = 2.0;
const float w = 0.9;
const float maxX1 = 10.0;
const float minX1 = -10.0;
const float maxX2 = 10.0;
const float minX2 = -10.0;
const float minV = -2; 
const float maxV = 4;
//float initV;
//pos initPos;

class pos {
public:
    friend ostream& operator<<(ostream &os, const pos &p) {
        os << "(" << p.x1 << ", " << p.x2 << ")";
        return os; 
    }   

    pos():x1(0.0), x2(0.0) {}
    pos(float x1, float x2):x1(x1), x2(x2) {}
    pos(const pos &p):x1(p.x1), x2(p.x2) {} // copy ctr
    pos& operator=(const pos &rhs) {
        if (this == &rhs) return *this;
        this->x1 = rhs.x1;
        this->x2 = rhs.x2;
        return *this;
    }

    void setX1(float x1) {this->x1 = x1;}
    void setX2(float x2) {this->x2 = x2;}
    float getX1() {return x1;}
    float getX2() {return x2;}
    float getX1() const {return x1;}
    float getX2() const {return x2;}
private:
    float x1;
    float x2;
};

class velocity {
public:
// to see the details of velocity class, download the source code from the link below
private:
    float v1;
    float v2;
};

float f(const pos &p)
{
    return p.getX1() * p.getX1() + p.getX2() * p.getX2();
}

void updateParas(velocity &vOrig, pos &pOrig, const pos &pBi, const pos &gBest)
{
    // to see the details of update function, download the source code from the link below

float randomGenerator(float lowerBound, float upperBound)
{
    static default_random_engine e(time(0));
    static uniform_real_distribution<float> u(lowerBound, upperBound);
//  cout << u(e) << endl;
    return u(e);
}

int main()
{
    vector<velocity> vs(N);
    vector<pos> ps(N);
    vector<pos> pBest(N);
    pos gBest;

    for (int i = 0; i != N; ++i) {
        vs[i].setV1(randomGenerator(minV, maxV));
        vs[i].setV2(randomGenerator(minV, maxV));
        ps[i].setX1(randomGenerator(minX1, maxX2));
        ps[i].setX2(randomGenerator(minX2, maxX2));
        pBest[i] = ps[i];
         // cout << "pBest: " << pBest[i] << endl;
    }
    gBest = pBest[0];
//  cout << "gBest: " << gBest << endl;
    for (int i = 1; i != N; ++i) {
        if (f(pBest[i]) < f(gBest))
            gBest = pBest[i];   // initialize the gBest as the minmum pBest
    }

    while (MAX_ITER-- != 0) {
        for (int i = 0; i != N; ++i) {
// to see the details of iterations, download the source code from the link below
		}
    }
    cout << "best global: " << gBest << endl;
    cout << "final answer: " << f(gBest) << endl;
}
                                                                                                                                              

運行結果如下：

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