R中的机车车辆分布

Question

我有一个数据框，其中包含按月的手头库存、到货数量和预期消费量。

我需要计算每个月需要购买的数量，以使我的库存每月保持在一定安全库存之上。

例如：我有 3 件库存，4 件第一个月到货，预计消费量为 0。因此我这个月不需要购买任何件，剩下 3+4-0=7。

这意味着下个月我将从 7 开始，假设消费量为 7 并且到达 1 单位。因此，我的安全库存量为 4 时，我将不足 3 件，因此我需要在当月计划购买 3 件。

第 3 个月，我从 4 件安全库存开始，1 件到货，消耗 5 件，所以我是 0，所以我需要编程购买 4 件来补充我的安全库存。

作为一个例子，我需要复制以下“购买”是我需要计算的地方

df <- data.frame(type = c("a","a","a","a","a"),
date = as.Date(c("2020-01-01", "2020-02-01", "2020-03-01", "2020-04-01", "2020-05-01")),
stock= c(3,0,0,0,0),
arriving = c(4,1,1,3,2),
consumption = c(0,7,5,5,3),
safety_stock = c(4,4,4,4,4),
to_purchase= c(0,3,4,2,1))

Answer 1

假设这些库存是不易腐烂的，那么每个月的初始stock 应该等于您上个月剩余的数量。

您每个月的 to_purchase 方程应该是
to_purchase = safety_stock - (stock - consumption + arriving)，
基本上是需求减去可用供应。

library(tidyverse)

df <- data.frame(
  type = c("a","a","a","a","a"),
  date = as.Date(c("2020-01-01", "2020-02-01", "2020-03-01", "2020-04-01", "2020-05-01")),
  stock = c(3,7,4,4,4),
  arriving = c(4,1,1,3,2),
  consumption = c(0,7,5,5,3),
  safety_stock = c(4,4,4,4,4)
) %>% 
  mutate(
    to_purchase = safety_stock - (stock - consumption + arriving), # purchase equation
    to_purchase = ifelse(to_purchase < 0, 0, to_purchase) # if negative, change value to zero
  )

但是，这样做的一个问题是，如果您要计算需要购买的数量 (to_purchase)，您可能还需要计算上个月剩余的数量 (@987654326 @)。因此，您的代码还应包括每个月初始 stock 的计算。

df <- data.frame(
  type = c("a","a","a","a","a"),
  date = as.Date(c("2020-01-01", "2020-02-01", "2020-03-01", "2020-04-01", "2020-05-01")),
  stock = c(3,NA,NA,NA,NA),
  arriving = c(4,1,1,3,2),
  consumption = c(0,7,5,5,3),
  safety_stock = c(4,4,4,4,4),
  to_purchase = NA
) 

for(i in 2:nrow(df)){
  # determine if you need to purchase anything from the previous month
  h = i-1
  df$to_purchase[h] = df$safety_stock[h] - (df$stock[h] - df$consumption[h] + df$arriving[h])
  df$to_purchase[h] = ifelse(df$to_purchase[h] < 0, 0, df$to_purchase[h])
  # determine initial stock of the current month
  df$stock[i] = df$stock[h] + df$arriving[h] - df$consumption[h] + df$to_purchase[h]
  # determine if you need to purchase anything for the current month
  df$to_purchase[i] = df$safety_stock[i] - (df$stock[i] - df$consumption[i] + df$arriving[i])
  df$to_purchase[i] = ifelse(df$to_purchase[i] < 0, 0, df$to_purchase[i])
}

df
#>   type       date stock arriving consumption safety_stock to_purchase
#> 1    a 2020-01-01     3        4           0            4           0
#> 2    a 2020-02-01     7        1           7            4           3
#> 3    a 2020-03-01     4        1           5            4           4
#> 4    a 2020-04-01     4        3           5            4           2
#> 5    a 2020-05-01     4        2           3            4           1