Decision making in inventory control by using artificial neural networks
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, the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Research and Development Academy
2022-02-01
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| Series: | Sustainable Engineering and Innovation |
| Online Access: | https://sei.ardascience.com/index.php/journal/article/view/150 |
| _version_ | 1811272709966921728 |
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| author | Lorenzo Cevallos-Torres Miguel Botto Tobar Angela Díaz Cadena Oscar León-Granizo |
| author_facet | Lorenzo Cevallos-Torres Miguel Botto Tobar Angela Díaz Cadena Oscar León-Granizo |
| author_sort | Lorenzo Cevallos-Torres |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T22:45:11Z |
| format | Article |
| id | doaj.art-ca9a3795e0884ec48778aa88ea2349ea |
| institution | Directory Open Access Journal |
| issn | 2712-0562 |
| language | English |
| last_indexed | 2024-04-12T22:45:11Z |
| publishDate | 2022-02-01 |
| publisher | Research and Development Academy |
| record_format | Article |
| series | Sustainable Engineering and Innovation |
| spelling | doaj.art-ca9a3795e0884ec48778aa88ea2349ea2022-12-22T03:13:35ZengResearch and Development AcademySustainable Engineering and Innovation2712-05622022-02-0141667510.37868/sei.v4i1.id150116Decision making in inventory control by using artificial neural networksLorenzo Cevallos-Torres0Miguel Botto Tobar1Angela Díaz Cadena2Oscar León-Granizo3University of Guayaquil, EcuadorEindhoven University of Technology, The NetherlandsUniversity of Valencia, SpainUniversity of Guayaquil, EcuadorThe 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.https://sei.ardascience.com/index.php/journal/article/view/150 |
| spellingShingle | Lorenzo Cevallos-Torres Miguel Botto Tobar Angela Díaz Cadena Oscar León-Granizo Decision making in inventory control by using artificial neural networks Sustainable Engineering and Innovation |
| title | Decision making in inventory control by using artificial neural networks |
| title_full | Decision making in inventory control by using artificial neural networks |
| title_fullStr | Decision making in inventory control by using artificial neural networks |
| title_full_unstemmed | Decision making in inventory control by using artificial neural networks |
| title_short | Decision making in inventory control by using artificial neural networks |
| title_sort | decision making in inventory control by using artificial neural networks |
| url | https://sei.ardascience.com/index.php/journal/article/view/150 |
| work_keys_str_mv | AT lorenzocevallostorres decisionmakingininventorycontrolbyusingartificialneuralnetworks AT miguelbottotobar decisionmakingininventorycontrolbyusingartificialneuralnetworks AT angeladiazcadena decisionmakingininventorycontrolbyusingartificialneuralnetworks AT oscarleongranizo decisionmakingininventorycontrolbyusingartificialneuralnetworks |