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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM49978
Volume:
9 |
6 |
Jun 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Off late, the demand for pharmaceutical products and drugs has ramped up significantly due to the ongoing COVID-19 scenario. Several instances have been reported where large scarcity of drugs have led to fatalities in patients. Hence, the necessity for a holistic approach for demand forecasting for the pharmaceutical supply chain has become imperative. Recently, soft computing techniques are being used widely for demand forecasting due to relatively higher accuracy compared to conventional statistical techniques. This work presents a comprehensive review on machine learning based models for demand forecasting in pharmaceutical supply chains. The performance parameters have also been discussed.
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Publication Date
6/10/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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