AI-based decision making in supply chains: prototyping a ML-driven APS (Advanced planning system) using Walmart open-source datasets
Coci, Marco (A.A. 2024/2025) AI-based decision making in supply chains: prototyping a ML-driven APS (Advanced planning system) using Walmart open-source datasets. Tesi di Laurea in International operations and global supply chain, Luiss Guido Carli, relatore Lorenza Morandini, pp. 73. [Master's Degree Thesis]
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Abstract/Index
Introduction: supply chain and its transformation in the AI era. Supply chain and its challenges. How demand forecasting is changing the supply chain. The role of machine learning. Advanced planning and scheduling (APS). Data, exploratory analysis and preprocessing. Dataset description: the Walmart M5 case. Exploratory data analysis (EDA). Preprocessing and analysis of intermittent demand. Forecasting modeling and implementation. Preliminary model selection and evaluation. Complete forecasting framework development. Forecasting demand for new products via similarity-based approaches. Operational integration and results. Translating forecasts into inventory decisions. Evaluation of operational KPIs and results.
References
Bibliografia: pp. 72-73.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | International operations and global supply chain |
| Thesis Supervisor: | Morandini, Lorenza |
| Thesis Co-Supervisor: | Spagnoletti, Paolo |
| Academic Year: | 2024/2025 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 24 Oct 2025 13:00 |
| Last Modified: | 24 Oct 2025 13:00 |
| URI: | https://tesi.luiss.it/id/eprint/43550 |
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