A hybrid computational approach for detailed scheduling of products in a pipeline with multiple pump stations

Multi-product pipeline is the most effective mode for refined products transportation and is of vital importance in the energy supply chain. The essential task in actual pipeline operation is scheduling delivery and injection of numerous kinds of products. Despite much research was done on products pipeline scheduling issue, little of them focused on multiple pump stations which are significant for long-distance pipelines. The paper establishes a mixed-integer nonlinear programming model (MINLP) for products pipeline with single source and multiple pump stations. The model has taken factors such as batch migration, local electricity price, demand time window, avoidance of idle segment, change of minimum flow rate and nonlinear hydraulic related objective function into consideration. The model contains two parts and is solved by a hybrid computational approach, the ant colony optimization algorithm (ACO) and the simplex method (SM). Finally, the formulation is successfully applied to a virtual and a real-world pipeline to verify the stability, convergence and practicability.