Swarm Optimisation for Shipping Fleet Scheduling, Routing and Delivery in Sustainable Liquified Natural Gas (LNG) Supply Chain Models

Natural gas is a relatively clean fuel when compared to other hydrocarbon fuels, such as oil and coal. It can be liquified into what is known as liquefied natural gas (LNG) with the potential for cost-effective transportation thereby allowing it to be adopted as a major energy source in many parts of the world. Whilst there exists an increasing global demand for LNG of up to 20 % annually, supply chains lack objective approaches that enable decision-making for planning and delivery, and encourage the global mobilisation of LNG reserves in an economically and environmentally sustainable manner. The objective of this study is to develop a multi-objective mathematical model for shipping fleet scheduling, routing and delivery for sustainable LNG supply chains. The model incorporates flexibility in delivery times; inventory management and berth availability constraints; and fuel consumption and carbon emissions. The model formulation is based on a real-case LNG supply chain in the state of Qatar, which represents the business-as-usual scenario, with polynomial number of variables and constraints corresponding to 248 cargoes spread across 90 days. The problem formulation is subsequently solved using the Binary Particle Swarm Optimisation (BPSO) algorithm. The solutions for scheduling, routing and delivery over the representative planning horizon obtained thus far demonstrate that the average total costs and emissions associated with a single cargo is approximately 1.6 million USD and 38 million kg CO2/day respectively.