Network optimisation for transporting liquefied natural gas from stations to end customers

This paper presents an approach to optimise the liquefied natural gas (LNG) transportation network. As the Chinese government put forward the coal to gas heating convention project in its Jing-Jin-Yi area, demands of LNG increased dramatically in 2017, rising an emergent need for optimisation of current LNG transportation network. A number of tanker trucks with limited capacity, parking at truck centres are available for LNG transportation. Each truck loads LNG at refuelling stations, transports LNG to customers, and returns to the truck centre after the delivery. According to the size of orders, the problem is divided into two sub-problems: a big order problem (BOP) to deal with integral trucks of LNG demands, and a small order problem to fulfil fractional demands. Trucks can be sent from multiple truck centres; and trucks need to move the LNG in gas stations – pickup locations – to a series of customers – delivery locations. We formulate the BOP with integer programming, and provide a decomposition approach. For small order problem, a network representation and a mathematical model are presented. A tailored object-coding genetic algorithm is developed to solve the small order problem. Four purposely designed experiments are conducted to test its performance.