Abstract Scheduling product batches in pipelines is a very complex task with many constraints to be considered. Several papers have been published on the subject during the last decade. Most of them are based on large-size MILP discrete time scheduling models whose computational efficiency greatly diminishes for rather long time horizons. By introducing an MILP continuous representation in both time and volume. Cafaro and Cerda (2004) recently developed a more rigorous problem description providing better schedules at much lower computational cost. However, all model-based scheduling techniques were applied to examples featuring short time horizons and a unique duedate for all deliveries at the horizon end. Pipeline operators generally use a recurring monthly schedule involving several periods, with product demands to be satisfied, at the end of each period. Because of the pipeline time delay, most of the market demands over short horizons are fulfilled through inventories already available at depot tanks or in pipeline transit. Therefore, the scheduled pumping runs have nothing to do with future product demands at distribution terminals and are aimed at simply moving product slugs along the duct. To overcome such drawbacks of current approaches, this work presents an efficient MILP continuous framework for the dynamic scheduling of pipelines over a multiperiod rolling horizon. At the completion of the current period, another one is added at the end of the rolling horizon and the re-scheduling process is triggered again over the new horizon. Pumping runs may extend for two or more periods. The approach successfully solved a real-world pipeline scheduling problem involving the transportation of four products to five destinations over a rolling horizon always comprising four one-week periods.
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