check_for_unknown_vars_implmodel，the_ast中的错误：表达式包含一个不属于模型的变量

问题描述

问题是要找到最小距离量值，但是代码仍然显示以下错误

check_for_unkNown_vars_impl（model，the_ast）中的错误：表达式包含的变量不属于模型。

我真的找不到问题所在。代码如下所示：

#load the data of distance from factory to distribution center
distance_factorydc <- read_excel("Autoparts24.xlsx",sheet="Factories_to_DCs")
distance_factorydc<-distance_factorydc[,-1]

#load the data of distance from distribution center to customers
distance_dccustomer<- read_excel("Autoparts24.xlsx",sheet="DCs_to_Customers") 
distance_dccustomer<-distance_dccustomer[-c(5:6),-1]

#the demand of the customer
customerdemand<- read_excel("Autoparts24.xlsx",sheet="DCs_to_Customers")
customerdemand<-customerdemand[6,-1]


# the ILP model is created
model <- MIPModel() %>%
# set F as a continuous variables 
# Fij is the amount that shipped from factory i to distribution center j
 add_variable(F[i,j],i = 1:3,j = 1:4,type = "continuous",lb = 0) %>%
# set C as a continuous variables 
# Cjk is the amount that shipped from distribution center j to customer k
add_variable(C[j,k],j =1:4,k = 1:30,lb = 0) %>%

# minimize the total cost
set_objective(sum_expr(distance_factorydc[i,j]* F[i,j = 1:4) +
              sum_expr(distance_dccustomer[j,k]* C[j,k = 1:30),"min")%>% 

# the total amount that shipped from distribution center to customers 
# should >= the total demand of the customer 
add_constraint(sum_expr(F[j,j=1:4)  >= sum_expr(customerdemand[k],k=1:30)) %>% 


# the total amount that shipped from factory to distribution center    should be the same as
# the amount that shipped from distribution center to customers
add_constraint(sum_expr(F[i,i = 1:3)  >= sum_expr(C[j,j=1:4) 
               

解决方法

我不确定要导入的数据的格式，但是distance_factorydc,distance_dccustomer,and customerdemand 变量似乎是模型中的问题。确保模型中的索引引用正确的行和列。您也可以将它们转换为矢量，然后在模型中公式化。

,

add_constraint(sum_expr(F[j,k],j=1:4) >= sum_expr(customerdemand[k],k=1:30))

对我来说可疑：

• F[j,k]应该类似于F[i,j]
• k中的F[j,k]不受控制，因为它位于sum_expr(customerdemand[k],k=1:30)内

此代码需要多加注意。