sim_base_normal {inventorize} | R Documentation |
sim_Base_normal
Description
Simulating a Base Stock policy.
Usage
sim_base_normal(
demand,
mean,
sd,
leadtime,
service_level,
Base = FALSE,
ordering_delay = FALSE,
shortage_cost = FALSE,
inventory_cost = FALSE,
ordering_cost = FALSE
)
Arguments
demand |
A vector of demand in N time periods. |
mean |
average demand in N time periods. |
sd |
standard deviation in N time periods. |
leadtime |
lead time from order to arrival |
service_level |
cycle service level requested |
Base |
Set to False for automatic calculation,else manual input of base. |
ordering_delay |
logical,Default is FALSE,if TRUE, orders are delayed one period. |
shortage_cost |
shortage cost per unit of sales lost |
inventory_cost |
inventory cost per unit. |
ordering_cost |
ordering cost for every time an order is made. |
Details
The Function takes a demand vector, mean of demand ,sd,lead time and requested service level to simulate and inventory system, orders are lost if inventory level is less than requested demand, also ordering is made at day t+1, metrics like item fill rate and cycle service level are calculated based on a normal distribution. the base is calculated automatically based on the mean demand and standard deviaiton. every period the order is exactly as the sales.
Value
a list of two date frames, the simulation and the metrics.
Author(s)
"haytham omar email: <haytham@rescaleanalytics.com>"
Examples
sim_base_normal(demand=rpois(80,6),mean=6,sd=0.2,leadtime=5,service_level=0.95,Base = 50,
shortage_cost= 1,inventory_cost=1,ordering_cost=1,ordering_delay=FALSE)