Agent-Based Dynamic Simulation for Supply Chain Management of LNG Import Terminals

Global trade in LNG is ever-increasing, but so are the inherent vulnerabilities in LNG supply chains. Simulation is a powerful approach for analyzing and optimizing such complex systems. Agent-based models have garnered interest as a suitable paradigm for analyzing such systems, given their ability to explicitly consider the different actors in a supply chain and their differing objectives. Here, we propose an agent-based simulation model of LNG importers' supply chain. In this paper, we describe the model and its implementation as a dynamic simulator called LIquefied Natural Gas Agent-based Model (LINGAM). We demonstrate the application of LINGAM by utilizing it to evaluate a variety of real-world scenarios faced by an LNG receiving terminal in India. These studies involve normal operations, as well as disruptions related to demand, maritime transport, and production issues. The results indicate that disruptions can reduce the plant's profit by as much as 71%.