写一段代码实现gurobi CVRP
时间: 2024-02-15 17:37:49 浏览: 28
以下是一个使用Gurobi和Python解决CVRP问题的示例代码。该代码使用Gurobi的Python API实现,需要安装Gurobi并获取Gurobi的许可证才能运行。
```python
import gurobipy as gp
from gurobipy import GRB
# 数据集
num_vehicles = 3
depot = 0
customers = [1, 2, 3, 4, 5]
demands = {1: 50, 2: 36, 3: 60, 4: 36, 5: 30}
capacities = {1: 100, 2: 100, 3: 100}
distances = {(i, j): # 前面两个数字是起点和终点
(((i - j) ** 2 + (i - j) ** 2) ** 0.5) # 这里是距离函数,可以根据实际情况修改
for i in [0] + customers
for j in [0] + customers}
# 创建模型
model = gp.Model('CVRP')
# 定义变量
vars = {}
for i in [0] + customers:
for j in [0] + customers:
if i != j:
vars[i, j] = model.addVar(obj=distances[i, j], vtype=GRB.BINARY, name='x_%d_%d' % (i, j))
model.update()
# 添加约束
for i in customers:
model.addConstr(gp.quicksum(vars[i, j] for j in [0] + customers if j != i) == 1)
for i in customers:
model.addConstr(gp.quicksum(vars[j, i] for j in [0] + customers if j != i) == 1)
for k in capacities:
model.addConstr(gp.quicksum(demands[i] * vars[i, j] for i in [0] + customers for j in [0] + customers if i != j
if i in k and j not in k) <= capacities[k])
# 添加目标函数
model.modelSense = GRB.MINIMIZE
# 求解
model.optimize()
# 输出结果
if model.status == GRB.Status.OPTIMAL:
print('Total distance: %g' % model.objVal)
solution = model.getAttr('x', vars)
routes = {}
for i in customers:
for j in customers:
if solution[i, j] > 0:
if i not in routes:
routes[i] = []
routes[i].append(j)
for k, v in routes.items():
print('Route:', [0] + v + [0])
else:
print('No solution found')
```
这段代码实现了一个CVRP问题的求解,其中`num_vehicles`表示车辆数量,`depot`表示车辆的起点,`customers`表示客户节点的编号,`demands`表示每个客户节点的需求,`capacities`表示每个车辆的容量,`distances`表示每个节点之间的距离。
代码首先创建了一个Gurobi模型,然后定义了变量和约束条件,并添加了目标函数。最后,模型被求解并输出结果。