An optimization approach to increasing sustainability and enhancing resilience against environmental constraints in LNG supply chains: A Qatar case study

Natural gas is an essential fuel in the transition towards a sustainable energy future as it is a cleaner source of fuel compared to other hydrocarbon sources. To enable natural gas delivery from the producer to consumers, natural gas is liquified to enhance transportation efficiency and reliability. This study contributes towards advancing decision support systems within the LNG supply chain to enhance sustainability and resilience. Five scenarios are investigated in terms of vessel types (Conventional, Q-Flex, Q-Max, and mixed fleet), delivery operation modes (single discharge and multi-discharge), and different bunker fuels (HFO, LNG, and dual-fuel). The Mixed Integer Programming model is used to schedule, assign and deliver a fixed number of LNG cargoes within one month considering total transportation costs and emissions. The developed model, which is implemented using the Binary Particle Swarm Optimization algorithm subjected to economic and environmental objectives within an overarching strategic aim for sustainability and resilience. The results demonstrate that using LNG as a bunker fuel supports the reduction in the total emissions within LNG transportation leading to enhancing the resilience of LNG delivery operations against growing environmental constraints. Outputs of the study indicate that the multi-discharge LNG-fuelled operation mode can achieve a cost reduction of 23.4% and a total emission reduction of 19.7% relative to a single discharge operation mode, where boil-off gas has a minor impact compared to the emissions released from fuel consumption.