matlab模拟退火算法求解车辆路径问题代码
时间: 2023-09-06 15:11:14 浏览: 46
以下是一个简单的MATLAB代码示例,用于使用模拟退火算法解决车辆路径问题(TSP):
```matlab
% 随机生成城市位置
num_cities = 20;
cities = rand(num_cities, 2);
% 计算城市之间的距离矩阵
distances = pdist2(cities, cities);
% 初始化模拟退火参数
temperature = 100;
cooling_rate = 0.99;
num_iterations = 1000;
% 初始解为随机排列
current_solution = randperm(num_cities);
% 计算初始解的总距离
current_distance = 0;
for i = 1:num_cities-1
current_distance = current_distance + distances(current_solution(i), current_solution(i+1));
end
current_distance = current_distance + distances(current_solution(num_cities), current_solution(1));
% 开始模拟退火搜索
while temperature > 1
for i = 1:num_iterations
% 随机交换两个城市的位置
new_solution = current_solution;
swap_idx = randperm(num_cities, 2);
new_solution(swap_idx(1)) = current_solution(swap_idx(2));
new_solution(swap_idx(2)) = current_solution(swap_idx(1));
% 计算新解的总距离
new_distance = 0;
for j = 1:num_cities-1
new_distance = new_distance + distances(new_solution(j), new_solution(j+1));
end
new_distance = new_distance + distances(new_solution(num_cities), new_solution(1));
% 判断是否接受新解
delta_distance = new_distance - current_distance;
if delta_distance < 0 || rand() < exp(-delta_distance / temperature)
current_solution = new_solution;
current_distance = new_distance;
end
end
% 降低温度
temperature = temperature * cooling_rate;
end
% 输出最终解和总距离
disp(['Final solution: ' num2str(current_solution)]);
disp(['Total distance: ' num2str(current_distance)]);
```
该代码使用随机生成的城市位置,计算城市之间的距离矩阵,并使用模拟退火算法搜索最优解。在每个温度下,它在当前解的基础上随机交换两个城市的位置,并根据一定的概率接受新解。最终,它输出最优解和总距离。