Scheduling of multi-product fungible liquid pipelines using genetic algorithms
Proceedings of the 1999 ACM symposium on Applied computing
Pipeline Transportation of Petroleum Products with No Due Dates
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
Eighteenth national conference on Artificial intelligence
The complexity of makespan minimization for pipeline transportation
Theoretical Computer Science
Integrated Methods for Optimization (International Series in Operations Research & Management Science)
CSE '08 Proceedings of the 2008 11th IEEE International Conference on Computational Science and Engineering
Activity based scheduling simulator for product transport using pipeline networks
Proceedings of the Winter Simulation Conference
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Brazilian petrobras is one of the world largest oil companies. Recurrently, it faces a very difficult planning and scheduling problem: how to operate a large pipeline network in order to adequately transport oil derivatives and biofuels from refineries to local markets. In spite of being more economical and environmentally safer, the use of a complex pipeline network poses serious operational difficulties related to resource allocation and temporal constraints. The current approaches known from the literature only consider a few types of constraints and restricted topologies, hence they are far from being applicable to real instances from petrobras. We propose a hybrid framework based on a two-phase problem decomposition strategy. A novel Constraint Programming (CP) model plays a key role in modelling operational constraints that are usually overlooked in literature, but that are essential in order to guarantee viable solutions. The full strategy was implemented and produced very adequate results when tested over large real instances.