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 diminishesforratherlongtimehorizons.Recently,anMILPcontinuousproblemrepresentationinbothtimeandvolumeprovidingbetterschedulesat muchlowercomputationalcosthasbeenpublished.However,allmodel-basedschedulingtechniqueswereappliedtoexamplesassumingastaticmarketenvironment,ashortsingle-periodtimehorizonandauniquedue-dateforalldeliveriesatthehorizonend.Incontrast,pipelineoperatorsgenerally use a monthly planning horizon divided into a number of equal-length periods and a cyclic scheduling strategy to fulfill terminal demands at period ends. Moreover, the rerouting of shipments and time-dependent product requirements at distribution terminals force the scheduler to continuously update pipeline operations. To ...
Diego C. Cafaro, Jaime Cerdá