The impact of geopolitical conflict and supply chain (SC) uncertainties in the global gas trading context is a burgeoning area of research. The strategic imperative of optimizing resource and technology utilization through cost optimization models within SC dynamics is realized. This study examines the effectiveness of linear programming techniques in mitigating the transportation challenges in the landscape of global gas trade, particularly amidst geopolitical disruptions in the SC. Computational tests underscore the substantial efficiency gains provided by this method, highlighting its capacity to generate significantly more efficient solutions to transportation problems. The findings indicate that the model shows promise for practical implementation, showcasing a notable reduction in transportation costs across the three primary markets for liquefied natural gas (LNG). Significantly, this reduction surpasses a quarter of the original expenses, indicating the potential for substantial cost savings in turbulent geopolitical environments and uncertain SCs. This study emphasizes the pivotal role of cost optimization models in navigating uncertainty and enhancing efficiency within the intricate and volatile landscape of global gas trading supply chains.