遗传算法解决TSP问题(C++)

遗传算法解决TSP问题（C++版）
遗传算法流程：
交叉，编译，计算适应度，保存最优个体。

其中交叉过程是选择最优的两个染色体进行交叉操作，本文采用的是轮盘赌算法。

#include<iostream>
#include<cstdlib>
#include<ctime>
using namespace std;
#define population 200//种群数量
#define pc 0.9//交叉的概率
#define pm 0.1//变异的概率
#define count 200//迭代的次数
#define num 10//城市的数量
int** city;//存放每个个体的访问顺序
int path[10][10] = {
//0, 1, 2, 3, 4, 5, 6, 7, 8, 9
{ 0, 23, 93, 18, 40, 34, 13, 75, 50, 35 },//0
{ 23, 0, 75, 4, 72, 74, 36, 57, 36, 22 },//1
{ 93, 75, 0, 64, 21, 73, 51, 25, 74, 89 },//2
{ 18, 4, 64, 0, 55, 52, 8, 10, 67, 1 }, //3
{ 40, 72, 21, 55, 0, 43, 64, 6, 99, 74 }, //4
{ 34, 74, 73, 52, 43, 0, 43, 66, 52, 39 },//5
{ 13, 36, 51, 8, 64, 43, 0, 16, 57, 94 },//6
{ 75, 57, 25, 10, 6, 66, 16, 0, 23, 11 }, //7
{ 50, 36, 74, 67, 99, 52, 57, 23, 0, 42 },//8
{ 35, 22, 89, 1, 74, 39, 94, 11, 42, 0 }//9
};
int* dis;//存放每个个体的访问顺序下的路径长度
double* fitness;//存放灭个个体的适应度
int min_dis = 1000000;
int min_index = -1;
int* min_path;
//初始化种群
void init()
{
int *a = new int[num];
for (int i = 0; i<num; i++)
{
a[i] = i;
}
city = new int*[population];
for (int i = 0; i<population; i++)
{
city[i] = new int[num];
}
for (int i = 0; i<population; i++)
{
for (int j = num - 1; j >= 0; j--)
{
int n = rand() % (j + 1);//产出的数是0-j,保证交换的后面的数不会再被交换
swap(a[j], a[n]);//保证a里面全是0-(num-1)的数，无重复的数，只是顺序颠倒
city[i][j] = a[j];
}
}
delete[]a;
dis = new int[population];
fitness = new double[population];
min_path = new int[num];
}
//计算适应度
void compute()
{
//cout << "do compute now. " << endl;
double total = 0;
for (int i = 0; i<population; i++)
{
//计算每种情况下，路径的长度
dis[i] = 0;
int a = city[i][0], b;
for (int j = 1; j<num; j++)
{
b = city[i][j];
dis[i] += path[a][b];
a = b;
}
dis[i] += path[b][city[i][0]];
fitness[i] = 1.0 / dis[i];//以距离的倒数作为适应度函数值
total += fitness[i];
}
}
//选择适应度高的物种，采用轮盘赌算法
int select()
{
double total = 0;
for (int i = 0; i<population; i++)
{
total += fitness[i];
}
double size = rand() / (double)RAND_MAX * total;//保证不产生0
//cout << "size " << size << endl;
double sum = 0;
int i = 0;
while (sum <= size&&i<population)
{
sum += fitness[++i];
}
return --i;//返回被选中的个体。