Despite of the high demand for liquefied natural gas (LNG) in demanding countries, an ideal means for establishing the LNG supply system has not yet been found in many regions. In this paper, a three-stage stochastic programming method has been proposed for LNG supply system infrastructure development and inventory routing in demanding countries. The minimum daily cost is set as the objective function; and the cost consists of the delivery cost, liquefaction cost, purchase cost, and construction cost. Under the constraints of delivery mode, volume, vehicle, time, and infrastructure construction, a multi-scenario MILP model was established and solved by a hybrid computational method (ACO-MILP), and the optimal infrastructure development and inventory routing were presented as the result. Finally, the method was successfully applied to the LNG supply system along the Yangtze River in China. Furthermore, compared with the other methods, the superiority of the method was verified. (C) 2017 Elsevier Ltd. All rights reserved.