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Improving the efficiency of food supplies for a trading company based on an artificial neural network

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 14 No. 4 (2024)

DOI
10.11591/ijece.v14i4.pp4407-4417
ISSN
2722-2578, 2088-8708
Published
2024-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This article presents the proper organization of the supply chain to meet consumer demand, which is crucial for modern commercial enterprises involved in the sale of various products. Studies indicate that a company's success is linked to the satisfaction of its customers. To optimize the supply chain, this study will consider the use of artificial neural network models. The results of this model will seek a balance between demand and supply, helping determine the necessary quantity of goods to satisfy demand and prevent overproduction. By using this model, the company can fully meet the needs of its customers. Additionally, the company saves its resources and labor costs and reallocates them to other tasks. The model demonstrates the optimization of production and supply business processes, as well as an increase in efficiency.

Collaboration network of the authors

15 authors · 47 co-authorship links · 14 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • L. N. Gumilyov Eurasian National University
  • Astana IT University
  • National Academy of Education named after Y. Altynsarin
  • Caspian University
  • Yessenov University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Zhanat KenzhebayevaCaspian University2
Ulzhan MakhazhanovaAffiliation unknown2
Ainur MukhiyadinL. N. Gumilyov Eurasian National University2
Manargul MukashevaNational Academy of Education named after Y. Altynsarin2
Gulmira AzievaL. N. Gumilyov Eurasian National University2
Aigul AdamovaAstana IT University1
Tamara Kokenovna ZhukabayevaAstana IT University1
Laula ZhumabayevaYessenov University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Improving the efficiency of food supplies for a trading company based on an artificial neural network</dc:title><dc:creator>Bisenovna, Kassekeyeva Aislu</dc:creator><dc:creator>Arman Ashatuly, Sadvakassov</dc:creator><dc:creator>Zhanar Beibutovna, Lamasheva</dc:creator><dc:creator>Yesilbayuly, Kerimkhulle Seyit</dc:creator><dc:creator>Zagievna, Abdrakhmanova Alfiya</dc:creator><dc:creator>Galymbekovna, Makpal Zhartybayeva</dc:creator><dc:creator>Oralkhanuly, Oralkhanov Berdibek</dc:creator><dc:description>&lt;jats:p&gt;This article presents the proper organization of the supply chain to meet consumer demand, which is crucial for modern commercial enterprises involved in the sale of various products. Studies indicate that a company's success is linked to the satisfaction of its customers. To optimize the supply chain, this study will consider the use of artificial neural network models. The results of this model will seek a balance between demand and supply, helping determine the necessary quantity of goods to satisfy demand and prevent overproduction. By using this model, the company can fully meet the needs of its customers. Additionally, the company saves its resources and labor costs and reallocates them to other tasks. The model demonstrates the optimization of production and supply business processes, as well as an increase in efficiency.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2024-08-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v14i4.pp4407-4417</dc:identifier><dc:identifier>10.11591/ijece.v14i4.pp4407-4417</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 14 No 4 (2024); 4407</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/34930/17557</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>