Global supply chains, as critical enablers of global economic integration, facilitate cross-border trade, expand market access, and support worldwide production and consumption. At the same time, they are increasingly exposed to risks such as trade policy shifts, tariff uncertainty, geopolitical conflict, natural disasters, supply disruptions, market volatility, and technological change. In response to evolving trade policies, sustainability pressures, tariff uncertainty, and resilience requirements, firms are restructuring their global production and sourcing strategies. This study presents a review of the literature on global supply chain management under tariff and market uncertainty. We analyze operations research approaches to network design, production planning, inventory management, and sourcing, with particular attention to how uncertainties are modeled and integrated into decision-making frameworks. The review further evaluates the role of emerging technologies, including artificial intelligence and machine learning, blockchain, and digital twins, in enhancing resilience and sustainability. In addition, we introduce an ongoing project on agricultural global supply chains under tariff uncertainty as an illustrative case, demonstrating the practical relevance of robust optimization methods. The findings highlight prevailing methodological trends, identify gaps in addressing multidimensional uncertainties, and outline directions for future research aimed at developing more adaptive and robust global supply chain systems.