Stochastic Simulation Agent for Unknown Inventory Demands in Healthcare Supply Management

Rafael Marin Machado de Souza, Rafael Marin Machado de Souza, Rafael Marin Machado de Souza, Leandro Nunes de Castro, Leandro Nunes de Castro, Leandro Nunes de Castro, Marcio Biczyk, Marcos dos Santos, Marcos dos Santos, Eder Cassettari

2024

Abstract

The acquisition of innovative items or those without historical demand data considerably increases the complexity of the routine of buyers, who among the daily challenges are keeping stocks up to date, with quantities that provide maximum profitability or maximum use of the purchased items. Seeking to provide a tool to assist in these goals, this study implements a Python-based software agent employing the Monte Carlo method for stochastic simulation and proposes a solution for uncertain inventory demands, providing a decision-mak-ing tool in the absence of historical data, thereby optimizing inventory levels and maximizing profitability. Experiments conducted across both local and cloud server configurations, with a comparative analysis of CPU and GPU performance, demonstrates the agent’s capacity to generate random scenarios with a statistical tolerance margin of 1% from 10,000 simulations. Scalability tests underscore the agent’s adaptability to diverse scenarios, effectively harnessing GPU capabilities for processing extensive data.

Paper Citation

in Harvard Style

Marin Machado de Souza R., Nunes de Castro L., Biczyk M., dos Santos M. and Cassettari E. (2024). Stochastic Simulation Agent for Unknown Inventory Demands in Healthcare Supply Management. In Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-707-8, SciTePress, pages 211-217. DOI: 10.5220/0012674700003756

in Bibtex Style

@conference{data24,
author={Rafael Marin Machado de Souza and Leandro Nunes de Castro and Marcio Biczyk and Marcos dos Santos and Eder Cassettari},
title={Stochastic Simulation Agent for Unknown Inventory Demands in Healthcare Supply Management},
booktitle={Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2024},
pages={211-217},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012674700003756},
isbn={978-989-758-707-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Stochastic Simulation Agent for Unknown Inventory Demands in Healthcare Supply Management
SN - 978-989-758-707-8
AU - Marin Machado de Souza R.
AU - Nunes de Castro L.
AU - Biczyk M.
AU - dos Santos M.
AU - Cassettari E.
PY - 2024
SP - 211
EP - 217
DO - 10.5220/0012674700003756
PB - SciTePress