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Reviewing the applications of neural networks in supply chain: exploring research propositions for future directions

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Reviewing the Applications of Neural Networks in Supply -information-13-00261.pdf (3.613Mb)
Date
2022
Author
Meidutė-Kavaliauskienė, Ieva
Taşkın, Kamil
Ghorbani, Shahryar
Činčikaitė, Renata
Kačenauskaitė, Roberta
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Abstract
Supply chains have received significant attention in recent years. Neural networks (NN) are a technique available in artificial intelligence (AI) which has many supporters due to their diverse applications because they can be used to move towards complete harmony. NN, an emerging AI technique, have a strong appeal for a wide range of applications to overcome many issues associated with supply chains. This study aims to provide a comprehensive view of NN applications in supply chain management (SCM), working as a reference for future research directions for SCM researchers and application insight for SCM practitioners. This study generally introduces NNs and has explained the use of this method in five features identified by supply chain area, including optimization, forecasting, modelling and simulation, clustering, decision support, and the possibility of using NNs in supply chain management. The results showed that NN applications in SCM were still in a developmental stage since there were not enough high-yielding au-thors to form a strong group force in the research of NN applications in SCM.
Issue date (year)
2022
URI
https://etalpykla.vilniustech.lt/handle/123456789/112775
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  • Straipsniai Web of Science ir/ar Scopus referuojamuose leidiniuose / Articles in Web of Science and/or Scopus indexed sources [7946]

 

 

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