matlab写VRP问题的带啊吗

是的，MATLAB可以用来解决VRP问题。下面是一个简单的VRP问题的MATLAB代码示例：

% 首先定义一个VRP问题的数据
num_customers = 10; % 客户数量
num_vehicles = 3; % 车辆数量
capacity = 20; % 车辆容量
locations = rand(num_customers+1,2); % 客户和仓库的位置
demands = randi([1 10],num_customers,1); % 客户的需求量
demands = [0; demands]; % 仓库的需求量为0

% 定义VRP问题的优化模型
model = struct();
model.A = []; % 约束矩阵
model.rhs = []; % 右手边向量
model.lb = zeros(num_customers+num_vehicles,1); % 变量下限
model.ub = [capacity*ones(num_vehicles,1); inf(num_customers,1)]; % 变量上限
model.obj = [zeros(num_vehicles,1); ones(num_customers,1)]; % 目标函数系数
model.sense = repmat('<',num_customers+num_vehicles,1); % 约束类型
model.vtype = [repmat('I',num_vehicles,1); repmat('B',num_customers,1)]; % 变量类型

% 添加容量约束
for i = 1:num_vehicles
    idx = num_vehicles + i;
    model.A(end+1,:) = [zeros(1,i-1) 1 zeros(1,num_vehicles-i+1) demands'];
    model.rhs(end+1,1) = capacity;
end

% 添加客户访问约束
for i = 1:num_customers
    idx = num_vehicles + i;
    model.A(end+1,:) = [zeros(1,idx-1) 1 zeros(1,num_customers+num_vehicles-idx+1)];
    model.rhs(end+1,1) = 1;
end

% 添加车辆流出约束
for i = 1:num_vehicles
    idx = i;
    model.A(end+1,:) = [zeros(1,idx-1) locations(idx,:)];
    model.A(end+1,:) = [zeros(1,idx-1) -locations(idx,:)];
    model.rhs(end+1,1) = 0;
    model.rhs(end+1,1) = 0;
end

% 添加车辆流入约束
for i = 1:num_vehicles
    idx = i;
    model.A(end+1,:) = [zeros(1,idx-1) 1 zeros(1,num_customers) -num_customers];
    model.rhs(end+1,1) = 0;
end

% 求解VRP问题
params.outputflag = 0;
result = gurobi(model,params);
routes = cell(num_vehicles,1);
for i = 1:num_vehicles
    idx = i;
    route = [idx; find(result.x(num_vehicles+1:end) == 1)+num_vehicles];
    routes{i} = route;
end

% 输出结果
for i = 1:num_vehicles
    fprintf('Vehicle %d: %s\n',i,num2str(routes{i}'));
end

这段代码使用了Gurobi求解器来求解VRP问题。如果您没有Gurobi许可证，可以使用MATLAB内置的linprog函数来求解LP问题，但效率可能会比较低。