Machine Learning for Sustainable Supply Chain Management and Waste Reduction

Abstract

The increasing global demand for sustainable supply chains necessitates the use of intelligent technologies to optimize logistics, minimize waste, and reduce carbon footprints. This paper explores the role of machine learning in supply chain management, focusing on demand forecasting, route optimization, and waste minimization. Techniques such as reinforcement learning, predictive analytics, and generative AI models are examined to improve inventory management and reduce inefficiencies. Case studies highlight AI-driven solutions implemented by major corporations to enhance sustainability in logistics and production, demonstrating significant reductions in resource wastage and greenhouse gas emissions.