Intelligent Supply Chain Optimization in Emerging Markets Using Ensemble Machine Learning

In today’s highly competitive and volatile environment, supply chains in emerging economies face ongoing challenges related to inventory management, demand forecasting, and distribution efficiency. This research proposes a predictive approach based on machine learning, specifically using ensemble st...

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Autores principales:	Christian Ovalle, Joel Martin Visurraga Agüero, Frans Ramiro Cárdenas Palomino, Waldyr Fredy Cerrón-Valverde, Daniel Ramón Chirinos Armas, Lenin Froy Arce-Huamán, Omar Santillan Aching
Formato:	Preprint
Lenguaje:	inglés
Publicado:	2025
Materias:	supply chain optimization stacking ensemble demand forecasting inventory management logistics decision-making emerging markets random forest CatBoost XGBoost gradient boosting k-nearest neighbors Forecasting Techniques and Applications Supply Chain and Inventory Management Impact of AI and Big Data on Business and Society
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Intelligent Supply Chain Optimization in Emerging Markets Using Ensemble Machine Learning

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