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A mathematical model for planning transportation of multiple petroleum products in a multi-pipeline system.

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dc.contributor.authorCruz García, Jesús Manuel de la
dc.contributor.authorHerrán, A.
dc.contributor.authorAndrés Toro, Bonifacio de
dc.date.accessioned2023-06-20T03:34:50Z
dc.date.available2023-06-20T03:34:50Z
dc.date.issued2010-03-05
dc.description© 2009 Elsevier Ltd. The authors would like to thank the Spanish Science and Technology Ministry for their support of project DPI2002-02924 and the Madrid
dc.description.abstractA multiproduct Pipeline provides an economic way to transport large Volumes of refined petroleum products over long distances. In such a pipeline, different products are pumped back-to-back without any separation device between them. Sometimes, multiproduct pipelines can be connected together, resulting in a more complex system commonly named multi-pipeline system. This paper proposes a new discrete mathematical approach to solve short-term operational planning Of multi-pipeline systems for refined products. This model is based on a discrete approach that divides both the planning horizon into time intervals of equal duration and the individual polyducts into packages of equal volume each containing a single product. Numerical examples are solved in order to show the performance of the proposed model. All the instances are implemented with the OPL modeling language running CPLEX as solver.
dc.description.departmentSección Deptal. de Arquitectura de Computadores y Automática (Físicas)
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipSpanish Science and Technology Ministry
dc.description.sponsorshipMadrid Autonomous Community
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/22560
dc.identifier.doi10.1016/j.compchemeng.2009.11.014
dc.identifier.issn0098-1354
dc.identifier.officialurlhttp://dx.doi.org/10.1016/j.compchemeng.2009.11.014
dc.identifier.relatedurlhttp://www.sciencedirect.com/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/43944
dc.issue.number3
dc.journal.titleComputers & Chemical Engineering
dc.language.isoeng
dc.page.final413
dc.page.initial401
dc.publisherPergamon-Elsevier Science LTD
dc.relation.projectIDDPI2002-02924
dc.relation.projectIDS-0505/DPI/0391
dc.rights.accessRightsopen access
dc.subject.cdu004
dc.subject.keywordMultiproduct Pipeline
dc.subject.keywordMulti-Pipeline System
dc.subject.keywordTransportation
dc.subject.keywordPlanning and Scheduling
dc.subject.keywordDiscrete Approach
dc.subject.keywordMixed-Integer Linear Program
dc.subject.ucmInformática (Informática)
dc.subject.unesco1203.17 Informática
dc.titleA mathematical model for planning transportation of multiple petroleum products in a multi-pipeline system.
dc.typejournal article
dc.volume.number34
dcterms.referencesCafaro, D. C., & Cerdá, J. (2004). Optimal scheduling of multiproduct pipeline systems using a nondiscrete MILP formulation. Computers and Chemical Engineering, 28, 2053–2068. Cafaro, D. C., & Cerdá, J. (2008). Dynamic scheduling of multiproduct pipelines with multiple delivery due dates. Computers and Chemical Engineering, 32, 728–753. Cruz, J. M., Andrés, B., Herrán, A., Besada, E., & Fernández, P. (2003). Multiobjective optimization of the transport in oil pipelines networks. In Proceedings of the 9th IEEE International Conference on Emerging Technologies and Factory Automation, vol. 1 (pp. 566–573). Cruz, J. M., Herrán, A., Risco, J. L., & Andrés, B. (2005). Hybrid heuristic and mathematical programming in oil pipelines networks: Use of immigrants. Journal of Zhejiang University Science, 6A(1), 9–19. ILOG Inc. (2006). ILOG OPL Studio 4.2 users manual. 1080 Linda Vista Ave., Mountain View, CA 94043. http://www.ilog.com. Mirhassani, S. A., & Ghorbanalizadeh, M. (2008). The multiproduct pipeline scheduling system. Computers and Mathematics with Applications, 56(4), 891–897. Rejowski, R., Jr., & Pinto, J. M. (2003). Scheduling of a multiproduct pipeline system. Computers and Chemical Engineering, 27, 1229–1246. Rejowski, R., Jr., & Pinto, J. M. (2004). Efficient MILP formulations and valid cuts for multiproduct pipeline scheduling. Computers and Chemical Engineering, 28, 1511–1528. Rejowski, R., Jr., & Pinto, J. M. (2008). A novel continuous time representation for the scheduling of pipeline systems with pumping yield rate constraints. Computers and Chemical Engineering, 32, 1042–1066. Sasikumar, M., Prakash, P. R., Patil, S. M., & Ramani, S. (1997). PIPES: A heuristic search model for pipeline schedule generation. Knowledge-Based Systems, 10, 169–175. Techo, R., & Holbrook, D. L. (1974). Computer scheduling the worlds biggest product pipeline. Pipeline and Gas Journal, 4, 27.
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