卡车类型（其中的无限数）与订单

Question

以下DOCPLEX模型的目标是选择最低成本的卡车以履行所有订单。在以下代码中，我将卡车类型视为1卡车，但实际上，卡车类型可以拥有无​​限数量的卡车，在这种情况下，我应该如何修改约束和客观功能以适应这一点？

import pandas as pd
import docplex.mp
from docplex.mp.model import Model
df_order = pd.DataFrame([[1,5000],[2,1000],[3,2000]], columns =['OrderID','Weight']) 
orders = df_order['OrderID'].values.tolist()
df_order.set_index('OrderID', inplace=True)

df_truck_types = pd.DataFrame([[1,'TYPE1',20000,'SP TRANSPORTS',40000],[2,'TYPE2',20000,'SP TRANSPORTS',40000],[3,'TYPE3',10000,'SP TRANSPORTS',30000]], columns =['TruckTypeID','VehicleType','Capacity','Transporter','TruckCost']) 
truck_types = df_truck_types['TruckTypeID'].values.tolist()
df_truck_types.set_index('TruckTypeID', inplace=True)

def get_order(o):
    return df_order.loc[o]

def get_truck_type(f):
    return df_truck_types.loc[f]

# Decision Variable and Objective Function
mdl = Model(name='itc_load_planning')

Assignment = mdl.binary_var_matrix(orders, truck_types, name='Assignment')
#for objective 1
TruckCost=mdl.sum(Assignment[o,f] * get_truck_type(f).TruckCost for o in orders for f in truck_types)

mdl.minimize(TruckCost)

# C1
for o in orders:
    mdl.add_constraint(mdl.sum(Assignment[o,f] for f in truck_types)==1, "C1")
    
# solve model
print("===solution===")
si = mdl.solve()
mdl.print_solution()

Answer 1

这不是OPL模型，而是DocPlex Python模型。

要处理卡车而不是卡车类型，我会更改

Assignment = mdl.binary_var_matrix(orders, truck_types, name='Assignment')

为

Assignment = mdl.binary_var_matrix(orders, trucks, name='Assignment')

卡车的卡车，因此您必须对

OPL卡车的容量限制添加限制，您可以很快写这篇文章：

tuple order
{
  key int id;
  int weight;
}

{order} orders={<1,5000>,<2,1000>,<3,2000>};

tuple trucktype
{
  key int TruckTypeID;
  string VehicleType;
  int Capacity;
  string Transporter;
  int TruckCost;
};

{trucktype} trucktypes=
{
  <1,"TYPE1",20000,"SP TRANSPORTS",40000>,
  <2,"TYPE2",20000,"SP TRANSPORTS",40000>,
  <3,"TYPE3",10000,"SP TRANSPORTS",30000>
};

int nbTruckPerType=3;

tuple truck
{
  trucktype TruckType;
  int rank;
}

{truck} trucks={<i,j> | i in trucktypes,j in 1..nbTruckPerType};

dvar boolean assign[orders][trucks];
dvar boolean istruckused[trucks];


minimize sum(t in trucks) istruckused[t]*t.TruckType.TruckCost;
subject to
{
  forall(t in trucks) ctUseTruck:istruckused[t]==(1<=sum(o in orders) assign[o][t]);
  
  forall(o in orders) ctOrders:sum(t in trucks) assign[o][t]==1;
  
  forall(t in trucks) ctCapacity:sum(o in orders) assign[o][t]*o.weight<=t.TruckType.Capacity;
}