Introduction

Inventory control is of great importance in companies as the total investment in inventories is enormous. Methods for inventory control can give a significant advantage over the competition Axsäter (2015). By using different tools, inventory costs can be minimized, without ignoring the needs of consumers and finding a balance with the other costs of acquisition, production and marketing.

It is important to consider that the benefits of inventory control are not only seen in the financial area, but also in customer satisfaction, which implies the delivery of orders placed by customers and product availability.

On the other hand, maintaining inventories is important for different reasons such as achieving greater economy for each production run, where it is necessary to produce sufficient quantities of products to compensate the investment made for each production run. Uncertainties, in many cases, it is not known with certainty the demand that will be in the future, that is why it is important to have enough units stored to meet the amount of products that will be demanded. In terms of control costs, it may be less expensive to maintain large quantities of certain inexpensive units than to pay for employees to keep detailed records of the products Nahmias and Olsen (2015).

There are packages that handle inventory control models in different programming languages. As for the R programming environment, two packages were found: SCperf (Marchena (2018)) and Inventorymodel (Nieves (2017)). The first one (SCperf) deals with inventory models with deterministic and stochastic demand. Among these are: EOQ, EPL, Newsvendor, and the Wagner Whitin algorithm. The Inventorymodel package handles inventory models with mainly deterministic demand, where the EOQ and EPL models are found. However, these two packages in the R programming environment use these models in the classical way. Based on the content found above, the objective is to develop modified inventory control models where more complex problems can be covered. This book explains the theory and how to use the functions in the package __ InvControl __, created based on the R Packages book (Wickman (2019b)) and Package Options Manual (“Chunk Options and Package Options” (2020)).

References

Axsäter, Sven. 2015. Inventory Control. 3rd ed. Lund, Sweden: Springer.
“Chunk Options and Package Options.” 2020. Knitr: Elegant, Flexible, and Fast Dynamic Report Generation with R. https://yihui.org/knitr/options/#plots.
Marchena, Marlene. 2018. SCperf: Functions for Planning and Managing Inventories in a Supply Chain. https://CRAN.R-project.org/package=SCperf.
Nahmias, Steven, and Tava Lennon Olsen. 2015. Production an Operation Analysis. 7th ed. Long Grove, Il, United States: Waveland Press, Inc.
Nieves, Alejandro Saavedra. 2017. Inventorymodel: Inventory Models. https://CRAN.R-project.org/package=Inventorymodel.
———. 2019b. R Packages - Whole Game. https://r-pkgs.org/whole-game.html.