旅行商问题代码matlab
时间: 2023-07-29 13:09:38 浏览: 35
以下是一个简单的旅行商问题的 MATLAB 代码示例:
```
% 创建城市坐标
x = [0 1 2 3 4];
y = [0 1 2 3 4];
% 计算城市之间的距离矩阵
n = length(x);
dist = zeros(n,n);
for i = 1:n
for j = 1:n
dist(i,j) = sqrt((x(i)-x(j))^2 + (y(i)-y(j))^2);
end
end
% 设置初始解并计算总距离
curr_solution = [1:n 1];
curr_dist = 0;
for i = 1:n
curr_dist = curr_dist + dist(curr_solution(i),curr_solution(i+1));
end
% 开始模拟退火过程
temp = 1;
temp_min = 0.001;
alpha = 0.99;
while temp > temp_min
% 生成新解
new_solution = curr_solution;
i = randi(n-1);
j = randi(n-1);
if i == j
continue
end
if i > j
temp = i;
i = j;
j = temp;
end
new_solution(i:j) = fliplr(curr_solution(i:j));
% 计算新解的总距离
new_dist = 0;
for i = 1:n
new_dist = new_dist + dist(new_solution(i),new_solution(i+1));
end
% 判断是否接受新解
delta = new_dist - curr_dist;
if delta < 0
curr_solution = new_solution;
curr_dist = new_dist;
else
p = exp(-delta/temp);
if rand < p
curr_solution = new_solution;
curr_dist = new_dist;
end
end
% 降温
temp = temp*alpha;
end
% 输出最优解和总距离
best_solution = curr_solution(1:end-1);
best_dist = curr_dist;
disp(['最优解:', num2str(best_solution)]);
disp(['总距离:', num2str(best_dist)]);
```
该代码使用模拟退火算法来解决旅行商问题。它首先创建城市坐标,并计算城市之间的距离矩阵。然后,它设置初始解并计算总距离。接下来,它开始模拟退火过程,在每个温度下生成新解并计算新解的总距离。它根据一定的概率接受新解或保留当前解,并逐渐降温,直到温度足够低。最后,它输出最优解和总距离。