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Highlights • A mixed-time MILP model is proposed aiming at optimal scheduling of COPD. • Multiple transportation modes such as pipeline, road and railway are considered. • The detailed operation and transport scheduling of a crude oil port depot can be obtained. • A real case study in China is given to demonstrate this method’s practicality. Abstract Crude oil port depots are key hubs in oil trade and thus play a vital role in the crude oil supply chain. Based on the characteristics of the scheduling system in an oil port depot, the development of a precise schedule is essential for handling asynchronous upstream supply and downstream market demand, thereby reducing operation cost as well as the impact of market fluctuations. Most previous studies focused only on the depot system, and few have taken the export transport scheduling into consideration. In this study, the diversity of crude oil storage modes, complexity of operations, and variety of transportation modes are considered. To minimize the total operation cost, a mixed-time representation based on a mixed-integer linear programming model is established. Finally, three real cases in a crude oil port depot in China are studied, and the monthly schedules of the depot are developed. Compared with previous algorithms, this method yields more accurate results in a considerably shorter time with improved computational stability. [ABSTRACT FROM AUTHOR]

• A discrete-time MOMILP model for pump scheduling of products pipelines is built. • Various factors about pump operation are considered comprehensively in the model. • A two-stage strategy is adopted to deal with the proposed model. • Two cases from a products pipeline system in China illuminate model's practicability. As one of the major means to link refineries to local markets, pipelines are crucial for refined oil supply chains. Pump scheduling is vital to optimally operate the refined products pipelines. Existing studies mostly quantified the number of pump stop/restart in the form of cost, whereas the cost coefficient was often subjectively selected. The present study built a multi-objective mixed-integer linear programming (MOMILP) model for refined products pipelines to minimize the number of pump stop/restart and reduce the pump running cost simultaneously. In this study, the minimum continuous running time of pumps, changing electricity price (i.e., time-changing electricity price and local electricity) and the pressure limits of special points were considered meticulously, e.g. high-elevation points, low-elevation points and pump stations. In the first stage, the improved augmented ε-constraint method (AUGMECON) was adopted to deal with this model, and obtained a seris of pump operating schemes, acting as a Pareto set. Then the results of the AUGMECON were evaluated by an established evaluation model based on neural network. Finally, two cases from a refined products pipeline system in China were employed to verify the practicability and accuracy of the proposed model. The results of this study can effectively guide the pump scheduling of refined products pipelines. [ABSTRACT FROM AUTHOR]