我是R的初学者,我正在使用R studio的Cplex解决线性规划问题。我的模型中的一个约束是Xl(i,j,t) <= D(i,j,t)。我可以使用嵌套的for循环来实现这一点,该循环的维度很小(16X16X6)。但我想运行我的模型更大的模型,更像2500X2500X60。我需要节省内存,并且比嵌套的for循环运行得更快。我想过使用apply,但我不知道如何让它工作。任何帮助都将不胜感激!
location <-16
horizon <-6
Amat <- NULL
Xe_null <- array(0, dim = c(locations, locations, horizon))
Xl_null <- array(0, dim = c(locations, locations, horizon))
Xl <- array(0, dim = c(locations, locations, horizon))
Xl <- Xl_null
for (t in 1:horizon) {
for (j in 1:locations) {
for (i in 1:locations) {
Xl[i,j,t] <- 1
Amat <- rbind(Amat, c(as.vector(Xe_null), as.vector(Xl)))
Xl <- Xl_null
} } }
dim(Amat) # 1536 3072这是另一个限制。
R <- array(, dim=c(locations, horizon, horizon))
R_null <- array(, dim=c(locations, horizon, horizon))
R <- R_null
Xe <- Xe_null
Xl <- Xl_null
#
for (t in 1:(horizon-1)) {
for (tp in (t+1):horizon) {
for (j in 1:locations) {
for (i in 1:locations) {
if ((tp-t) ==Travel_time[i,j])
{
Xe[i,j,t]=1
Xl[i,j,t]=1
}
}
R[j,tp,t] = 1
R[j,tp,t+1] = -1
Amat <- rbind(Amat, c(as.vector(Xe), as.vector(Xl),as.vector(R)))
}
}
}我试着这样做:
Xl = function(ii,jj,tt){1}
t =c(1:horizon)
i =c(1:locations)
j =c(1:locations)
output_Xl = apply(expand.grid(i,j,t),1,function(x,y,h) Xl(x[1],x[2],x[3]))
Xl_new <- array(output_Xl, dim = c(locations, locations, horizon))
Amat <- rbind(Amat, c(as.vector(Xe_null), as.vector(Xl_new)))
dim(Amat) # 1 3072发布于 2017-12-08 01:37:18
您可以使用以下命令获得相同的输出
T <- horizon*locations*locations
Bmat <- cbind(matrix(0, nrow=T, ncol=T), diag(1, nrow=T, ncol=T))
identical(Amat, Bmat)
# TRUE发布于 2017-12-08 12:03:14
我认为你需要做的是制作一个矢量化的函数,给出相同的输出(参见?Vectorize)。下面的代码比你的快五百倍。
在您的实际问题中,可能需要使用<<-而不是<- (请参阅?"<<-")
my_func <- function(a, b, c){
Xl[a, b, c] <- 1
c(as.vector(Xe_null), as.vector(Xl))
}
vectorized_my_func <- Vectorize(my_func, c("a", "b", "c"))
arg_df <- expand.grid(1:locations, 1:locations, 1:horizon)
res <- vectorized_my_func(arg_df[,1], arg_df[,2], arg_df[,3])
identical(Amat, t(res)) # TRUE
# your code
## user system elapsed
## 77.538 18.293 97.056
# my code
## user system elapsed
### 0.137 0.051 0.189 https://stackoverflow.com/questions/47697281
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