Laboratoire de Génie Informatique et d’Automatique de l’Artois

This thesis project, titled "Optimization of Supply Chain and Demand Forecasting Using Artificial Intelligence (AI)", focuses on enhancing the performance of supply chains by integrating innovative AI-based approaches. In the face of challenges such as unpredictable demand fluctuations, inventory management, delivery delays, and the pressure to reduce costs while increasing efficiency, this research aims to design advanced predictive models. These models, leveraging machine learning and deep learning techniques, will improve demand forecasting accuracy, reduce inventory errors, and lower operational costs. Through a rigorous methodology, the project includes an in-depth literature review, data analysis and preparation, evaluation of hybrid models (recurrent neural networks, convolutional networks, and others), and benchmarking to identify the most effective approaches. By providing concrete and adaptable solutions, this thesis seeks to transform current logistics practices by proposing proactive and sustainable management of information, physical, and financial flows. It highlights the potential impact of AI in modernizing supply chains, improving responsiveness to unforeseen events, and contributing to environmental sustainability by minimizing waste and carbon footprints.