Decision making in inventory control by using artificial neural networks

Oscar León-Granizo,Miguel Botto Tobar,Lorenzo Cevallos-Torres,Angela Díaz Cadena

doi:10.37868/sei.v4i1.id150

Abstract

The purpose of this work is to increase the sales of a store devoted to the purchase and sale of soft drinks, even though the store's inventory is overstocked. This occurs as a result of the business's lack of an effective management system that controls product ordering. Additionally, there is no analysis of future sales owing to the variations that may occur because of unforeseen occurrences. The main criterion was that the proprietors of the business submit monthly records from 2017 to July 2019. To accomplish this objective completely, we used the Monte Carlo simulation method to obtain data from August to December 2019; and neural networks to obtain data for all monthly periods in the years 2020, 2021, and 2022, which enabled us to generate records of demand and stock for each of the products. Finally, it was shown that the application of neural networks enables the solution of vehicle control issues, resulting in a maximization of more than 22% of sales, thus achieving the goal and giving an optimum solution to the company.

Highlights

Forecasting demand and supply for products in the sales shop are the main factors to consider while optimizing inventory management
It should be mentioned that the months from August to December 2019 were produced via the use of Monte Carlo simulation techniques. 4.2
Monte Carlo simulation The Monte Carlo simulation method was used to simulate the values of both sales and purchases for the months of August through December of this year

Summary

Introduction

Forecasting demand and supply for products in the sales shop are the main factors to consider while optimizing inventory management. That is, it must determine the timing and quantity of stock to produce. It must determine the timing and quantity of stock to produce It should demonstrate which items generate the greatest revenue and which generate losses for the company. This data is critical for making business choices that optimize sales via effective inventory management, increasing the store's market competitiveness. Inadequate inventory management results in several issues, including higher expenses, product loss, diminished market competitiveness, and customer loss

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Conclusion