matlab：sa for vrptw

根据提供的引用内容，可以得知SA模拟退火＊＊＊＊＊＊```matlab
% 读取数据
data = load('vrptw_data.txt');
n = data(1,1); % 客户数量
m = data(1,2); % 车辆数量
Q = data(1,3); % 车辆容量
d = data(2:n+1,1:n); % 客户之间的距离
e = data(2:n+1,n+1:2*n); % 客户的早时间窗
l = data(2:n+1,2*n+1:end); % 客户的晚时间窗
s = 1; % 起点
t = n + 1; % 终点

% 参数设置
T0 = 100; % 初始温度
Tf = 1e-8; % 终止温度
alpha = 0.99; % 降温系数
L = 100; % 每个温度下的迭代次数

% 初始化
x = zeros(n, m); % 路径矩阵
for i = 1:m
x(1,i) = 1;
x(n,i) = 1;
end
for i = 2:n-1
x(i,mod(i-2,m)+1) = 1;
end
f = obj(x, d); % 目标函数值
T = T0; % 当前温度

% SA算法
while T > Tf
for i = 1:L
% 产生新解
x_new = neighbor(x);
f_new = obj(x_new, d);
delta_f = f_new - f;
% 判断是否接受新解
if delta_f < 0
x = x_new;
f = f_new;
else
p = exp(-delta_f/T);
if rand() < p
x = x_new;
f = f_new;
end
end
end
% 降温
T = alpha * T;
end

% 输出结果
disp(x);
disp(f);

% 目标函数
function f = obj(x, d)
n = size(x, 1);
m = size(x, 2);
f = 0;
for i = 1:m
for j = 1:n
for k = 1:n
f = f + d(j,k) * x(j,i) * x(k,i);
end
end
end
end

% 产生邻域解
function x_new = neighbor(x)
n = size(x, 1);
m = size(x, 2);
i = randi(n-2) + 1;
j = randi(m);
k = randi(m);
while k == j
k = randi(m);
end
x_new = x;
x_new(i,j) = 0;
x_new(i,k) = 1;
end