Abstract
<jats:p>A hybrid approach to optimizing supply chain management using computer simulation and artificial intelligence The monograph explores the integration of optimization methods, computer simulation, and artificial intelligence in supply chain management, aligning with the Supply Chain Management 5.0 paradigm. In the face of growing environmental complexity and uncertainty, advanced analytical technologies have become essential for building flexible, resilient, and efficient supply chains. The study identifies a research gap concerning the full integration of AI tools &ndash; particularly large language models &ndash; with simulation-based modeling in optimization processes, despite their widely recognized theoretical potential. The monograph adopts a theoretical-empirical approach. The theoretical part systematizes the scientific literature on optimization methods, computer simulation, and artificial intelligence, and includes a bibliometric analysis revealing the limited presence of hybrid approaches in existing research. The empirical part comprises a survey of Polish managers and case studies demonstrating practical applications of AI&ndash;simulation integration in areas such as inventory management, production scheduling, and procurement logistics. The results indicate a low level of adoption of advanced tools among Polish enterprises, mainly due to knowledge gaps and competency barriers. The proposed hybrid approach shows that combining computer simulation with large language models can significantly simplify modeling and optimization, making these techniques more accessible to practitioners. The monograph highlights the potential of such solutions to reduce the gap between theory and practice.</jats:p>