A combination of geopolitical developments and advances in artificial intelligence is revolutionizing the field of logistics. Globalization has led to increased exposure to supply uncertainty, highlighting the need for reliable and resilient supply chains. Simultaneously, advances in artificial intelligence have established the potential of applying machine learning to logistical problems. Recent research is increasingly successful at finding methods to address supply chain uncertainty and apply artificial intelligence. Nonetheless, research gaps often exist between proposed stylized models and a complex reality. The goal of the dissertation is to overcome a selection of these gaps using AI-based models, thereby industrializing these models for use in practice.