title : “Arena Simulation Model for Inventory System in Supply Chain for a growing optical retail company”" shorttitle : “papaja Assigment”
author: “Marivalentina Lizardo”
affiliation: - id : “1” institution : “Harrisburg Univerisity”
authornote: | Since Supply Chain is always dealing with planning ahead in different time horizons, there are different levels of uncertain and that is why data analytics takes relevance; the opportunity to get historical data to predict future demands, work on simulations to see what it would be the response to different inventory policies or strategies, and analyze results, are some of the most used tools currently in the area
abstract: | For my analysis I will develop a multi-echelon inventory system using Arena Software, where I have, 130 retail stores, one warehouse, and two suppliers, and how transferring stock between stores if needed can decreased the inventory levels while accomplish the sales goals
keywords : “Supply Chain, Inventory, Arena, Optimization, multi-echelon” wordcount : “X”
bibliography : [“r-references.bib”]
floatsintext : no figurelist : no tablelist : no footnotelist : no linenumbers : yes mask : no draft : no
documentclass : “apa6” classoption : “man” output : papaja::apa6_pdf —
For my analysis I will develop a multi-echelon inventory system using Arena Software, where I have, 130 retail stores, one warehouse, and two suppliers, and how transferring stock between stores if needed can decreased the inventory levels while accomplish the sales goals
Since Supply Chain is always dealing with planning ahead in different time horizons, there are different levels of uncertain and that is why data analytics takes relevance; the opportunity to get historical data to predict future demand. According to [@WanJie_2009], work on simulations to could help to drive responses about how can impact the results.
I will analyze two different methods using Arena Software: 1) A model having 130 stores with no interaction, with 8 products, one distribution center and two suppliers. 2) A model having 130 stores with full interaction sharing inventory, with 8 products, one distribution center and two suppliers.
The 130 stores of the Retail Optical Company case study
I will analyze multiple parameters like demand, inventory levels, and reorder points to analyze the best approach to optimize results without impacting service levels
We used R [Version 3.6.1; @R-base] and the R-package papaja [Version 0.1.0.9842; @R-papaja] for all our analyses.
r_refs(file = "r-references.bib")
@article{bottani2014analysis, title={Analysis and optimisation of inventory management policies for perishable food products: a simulation study}, author={Bottani, Eleonora and Ferretti, Gino and Montanari, Roberto and Rinaldi, Marta}, journal={International Journal of Simulation and Process Modelling 11}, volume={9}, number={1-2}, pages={16–32}, year={2014}, publisher={Inderscience Publishers Ltd} }
@inproceedings{wan2009simulation, title={Simulation research on multi-echelon inventory system in supply chain based on arena}, author={Wan, Jie and Zhao, Cong}, booktitle={2009 First International Conference on Information Science and Engineering}, pages={397–400}, year={2009}, organization={IEEE} }