Purchasing and transport scheduling based on scenario tree in coal maritime supply chain with stochastic demand

A multi-period mixed integer programming model is presented in this paper to reduce the overall cost of coal purchasing and transport in large-scale power generation group with the consideration of the stochastic coal demand. Mixed integer linear programming is used in problem formulation considering inherent connection between purchasing and inventory routing, and scenario tree method is applied to represent the uncertainty of demand. The objective is to minimize the purchase and transport costs, inventory costs and expected penalty costs across the entire scheduling cycle. Due to the stochastic feature of the coal demand and the unbearable stock-out, supplement coal purchasing is regarded as a mean to avoid shortage of coal. The berth constrain is taken into account to prevent time clashes. Numerical tests are performed for a power generation group and the result shows that the overall system costs can be saved by 17 million Y when taking the stochastic demand into consideration, and supplement quantity can be further reduced when transport plan is implemented with time flexibility.