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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM49978

Supply Chain Forecasting Employing Artificial Intelligence and Machine Learning Approaches: A Survey

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-

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Paper ID:

IJSREM49978

Volume:

9 |

6 |

Jun 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

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.

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Authors

DR

Divya Rathwe

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Abstract

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.

KEYWORDS

Demand Forecasting Pharmaceutical Supply Chain Soft Computing Machine Learning Mean Absolute Percentage Error (MAPE)

Cite This Article

Divya Rathwe, "Supply Chain Forecasting Employing Artificial Intelligence and Machine Learning Approaches: A Survey," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 6, Jun 2025.

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6/10/2025

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