README.md
In sidoruvigo/EOQd: EOQ Model With and Without Discounts
EOQdis
Description [package]
This package implements functions suitable to solve problems of deterministic inventory with and without quantity discounts.
Usage
Install the development version from GitHub
install.packages("devtools") # If needed
devtools::install_github("sidoruvigo/EOQdis")
Load the library with: library("EOQdis")
The package includes the following functions:
+ EOQ()
+ EOQd()
+ EOQpd()
+ plot.EOQ()
EOQ(l, k, I, C)
Description [function EOQ]
This function implements the basic deterministic EOQ (Economic Order Quantity) model.
Assumptions for the EOQ model
- Order arrives instantly.
- No stockout.
- Constant rate of demand.
Parameters
- l: Demand (per unit of time).
- k: Preparation cost (per order).
- I: Storage cost (per article).
- C: Cost of goods (per item).
Return
A list containing:
- Q: Optimal order quantity.
- Z: Total cost.
- T: Cycle length.
- N: Number of orders.
Usage
library(EOQdis)
l <- 520 # Demand
k <- 10 # Preparation cost
I <- 0.2 # Storage cost per article
C <- 5 # Cost of goods per item
res1 <- EOQ(l = l, k = k, I = I, C = C)
res1
EOQd(l, k, I, q, dis, c)
Description [function EOQd]
This function provides an EOQ with discounts where the units purchased have the same reduction in price.
Parameters
- l: Demand (per unit of time).
- k: Preparation cost (per order).
- I: Storage cost (per article).
- q: Product quantities where the price changes (Vector of quantities within the discounts given in 'dis' are applied).
- dis: Vector of discounts.
- c: Orginal price of the product. (Price of the product without any discount)
Return
A list containing:
- Q: Optimal order quantity.
- Z: Total cost.
- T: Cycle length.
- N: Number of orders.
Usage
dis <- c(0, 0.05, 0.1) # Disccounts: 5% and 10%
l <- 520 # Demand (per unit of time).
k <- 10 # Preparation cost (per order).
I <- 0.2 # Storage cost (per article).
q <- c(0, 110, 150) # 5% when the quantity is greater than 110 and less than 150. For more than 150 units the discoun is 10%
c <- 5 # Original price of the product
res2 <- EOQd(dis = dis, l = l, k = k, I = I, q = q, c = c)
res2
Real example
A company needs 500 chairs every month to sell in their online store that costs 15€ each. The supplier negotiates with the company that if they buy more than 50 chairs they offer them a 25% disccount and if they buy more than 100 they offer them a 50% disccount. Making an order costs 10€ and the storage cost is estimated to be 2€ per chair.
dis <- c(0, 0.25, 0.5)
q <- c(0, 50, 100)
l <- 500
k <- 10
I <- 2
c <- 15
opt <- EOQd(dis = dis, l = l, k = k, I = I, q = q, c = c)
opt
EOQpd(l, k, I, q, c)
Description [function EOQpd]
This function provides an EOQ with discounts where the discount occurs for units purchased when a certain amount is reached.When the amount of order increases, the cost price decreases in the additional units ordered, not in all units.
Parameters
- l: Demand (per unit of time).
- k: Preparation cost (per order).
- I: Storage cost (per article).
- q: Quantites where the discounts are applied.
- c: Vector of cost of goods.
Return
A list containing:
+ Q: Optimal order quantity.
+ Z: Total cost.
+ T: Cycle length.
+ N: Number of orders.
Usage
l <- 50000
k <- 10
I <- 0.25
c <- c(0.6, 0.55)
q <- c(0, 1000)
res3 <- EOQpd(l = 50000, k = 10, I = 0.25, c = c, q = q)
res3
Real example
An university needs to buy 5000 markers every year, with a cost per order of 15€ and there is an estimated storage cost of 0.2€. The provider has the following policy: if the customer buys less than 500 markers, the cost per item is 0.75€, if the customer buys more than 500 units, the cost per item is 0.5€. We need to determine the optimal policy
l <- 5000
k <- 15
I <- 0.2
c <- c(0.75, 0.5)
q <- c(0, 500)
res3 <- EOQpd(l = l, k = k, I = I, c = c, q = q)
res3
plot.EOQ(z)
Description [function plot.EOQ]
S3 method to plot a EOQ object by using the generic plot function.
Parameters
- x: Object of class EOQ.
Return
A plot with classical EOQ representation.
Usage
plot(res1)
plot(res2)
plot(res3)
Author(s)
- Soage González, José Carlos.
Maintainer: José Carlos Soage González (jsoage@uvigo.es)
sidoruvigo/EOQd documentation built on May 16, 2019, 11:13 p.m.
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EOQdis
Description [package]
This package implements functions suitable to solve problems of deterministic inventory with and without quantity discounts.
Usage
Install the development version from GitHub
install.packages("devtools") # If needed
devtools::install_github("sidoruvigo/EOQdis")
Load the library with: library("EOQdis")
The package includes the following functions: + EOQ() + EOQd() + EOQpd() + plot.EOQ()
EOQ(l, k, I, C)
Description [function EOQ]
This function implements the basic deterministic EOQ (Economic Order Quantity) model.
Assumptions for the EOQ model
- Order arrives instantly.
- No stockout.
- Constant rate of demand.
Parameters
- l: Demand (per unit of time).
- k: Preparation cost (per order).
- I: Storage cost (per article).
- C: Cost of goods (per item).
Return
A list containing:
- Q: Optimal order quantity.
- Z: Total cost.
- T: Cycle length.
- N: Number of orders.
Usage
library(EOQdis)
l <- 520 # Demand
k <- 10 # Preparation cost
I <- 0.2 # Storage cost per article
C <- 5 # Cost of goods per item
res1 <- EOQ(l = l, k = k, I = I, C = C)
res1
EOQd(l, k, I, q, dis, c)
Description [function EOQd]
This function provides an EOQ with discounts where the units purchased have the same reduction in price.
Parameters
- l: Demand (per unit of time).
- k: Preparation cost (per order).
- I: Storage cost (per article).
- q: Product quantities where the price changes (Vector of quantities within the discounts given in 'dis' are applied).
- dis: Vector of discounts.
- c: Orginal price of the product. (Price of the product without any discount)
Return
A list containing:
- Q: Optimal order quantity.
- Z: Total cost.
- T: Cycle length.
- N: Number of orders.
Usage
dis <- c(0, 0.05, 0.1) # Disccounts: 5% and 10%
l <- 520 # Demand (per unit of time).
k <- 10 # Preparation cost (per order).
I <- 0.2 # Storage cost (per article).
q <- c(0, 110, 150) # 5% when the quantity is greater than 110 and less than 150. For more than 150 units the discoun is 10%
c <- 5 # Original price of the product
res2 <- EOQd(dis = dis, l = l, k = k, I = I, q = q, c = c)
res2
Real example
A company needs 500 chairs every month to sell in their online store that costs 15€ each. The supplier negotiates with the company that if they buy more than 50 chairs they offer them a 25% disccount and if they buy more than 100 they offer them a 50% disccount. Making an order costs 10€ and the storage cost is estimated to be 2€ per chair.
dis <- c(0, 0.25, 0.5)
q <- c(0, 50, 100)
l <- 500
k <- 10
I <- 2
c <- 15
opt <- EOQd(dis = dis, l = l, k = k, I = I, q = q, c = c)
opt
EOQpd(l, k, I, q, c)
Description [function EOQpd]
This function provides an EOQ with discounts where the discount occurs for units purchased when a certain amount is reached.When the amount of order increases, the cost price decreases in the additional units ordered, not in all units.
Parameters
- l: Demand (per unit of time).
- k: Preparation cost (per order).
- I: Storage cost (per article).
- q: Quantites where the discounts are applied.
- c: Vector of cost of goods.
Return
A list containing: + Q: Optimal order quantity. + Z: Total cost. + T: Cycle length. + N: Number of orders.
Usage
l <- 50000
k <- 10
I <- 0.25
c <- c(0.6, 0.55)
q <- c(0, 1000)
res3 <- EOQpd(l = 50000, k = 10, I = 0.25, c = c, q = q)
res3
Real example
An university needs to buy 5000 markers every year, with a cost per order of 15€ and there is an estimated storage cost of 0.2€. The provider has the following policy: if the customer buys less than 500 markers, the cost per item is 0.75€, if the customer buys more than 500 units, the cost per item is 0.5€. We need to determine the optimal policy
l <- 5000
k <- 15
I <- 0.2
c <- c(0.75, 0.5)
q <- c(0, 500)
res3 <- EOQpd(l = l, k = k, I = I, c = c, q = q)
res3
plot.EOQ(z)
Description [function plot.EOQ]
S3 method to plot a EOQ object by using the generic plot function.
Parameters
- x: Object of class EOQ.
Return
A plot with classical EOQ representation.
Usage
plot(res1)
plot(res2)
plot(res3)
Author(s)
- Soage González, José Carlos.
Maintainer: José Carlos Soage González (jsoage@uvigo.es)
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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