Free Access
RAIRO-Oper. Res.
Volume 54, Number 4, July-August 2020
Page(s) 1087 - 1102
Published online 20 May 2020
  • A.P. Barbosa-Póvoa, Process supply chains management – Where are we? Where to go next? Front. Energy Res. 2 (2014) 23. [Google Scholar]
  • C.E. Bodington and T.E. Baker, A history of mathematical programming in the petroleum industry. INFORMS J. Appl. Anal. 20 (1990) 117–127. [CrossRef] [Google Scholar]
  • V.G. Cafaro, P.C. Pautasso, J. Cerdá and D.C. Cafaro, Efficient planning of crude oil supplies through long-distance pipelines. Comput. Chem. Eng. 122 (2019) 203–217. [Google Scholar]
  • J. Cerdá, P.C. Pautasso and D.C. Cafaro, Optimization approaches for efficient crude blending in large oil refineries. Ind. Eng. Chem. Res. 57 (2018) 8484–8501. [Google Scholar]
  • L.S. de Assis, E. Camponogara, B.C. Menezes and I.E. Grossmann, An MINLP formulation for integrating the operational management of crude oil supply. Comput. Chem. Eng. 123 (2019) 110–125. [Google Scholar]
  • G.S.S. Diz, F. Oliveira and S. Hamacher, Improving maritime inventory routing: application to a Brazilian petroleum case. Marit. Policy Manage. 44 (2017) 42–61. [CrossRef] [Google Scholar]
  • J. Dyntar and J. Skvor, Oil refinery supply chain modelling using pipe transportation simulator. IJCSI Int. J. Comput. Sci. Issues 9 (2012) 278. [Google Scholar]
  • IOC web-site, Crude Oil Pipelines. Available at: (2020). [Google Scholar]
  • V.P. Klepikov and V.V. Klepikov, Crude oil logistics, production and refining in North Europe. Int. J. Energy Econ. Policy 8 (2018) 18–28. [Google Scholar]
  • F. Oliveira, P.M. Nunes, R. Blajberg and S. Hamacher, A framework for crude oil scheduling in an integrated terminal-refinery system under supply uncertainty. Eur. J. Oper. Res. 252 (2016) 635–645. [Google Scholar]
  • D.K. Papageorgiou, G.L. Nemhauser, J. Sokol, M.-S. Cheon and A.B. Keha, MIRPLib – a library of maritime inventory routing problem instances: survey, core model, and benchmark results. Eur. J. Oper. Res. 235 (2014) 350–366. [Google Scholar]
  • S. Randall, Energy, Risk & Competitive Advantage: The Information Imperative. Pennwell Corporation (2008). [Google Scholar]
  • R. Rocha, I.E. Grossmann and M.V. Poggi de Arago, Petroleum allocation at PETROBRAS: mathematical model and a solution algorithm. Comput. Chem. Eng. 33 (2009) 2123–2133. [Google Scholar]
  • D. Ronen, Dispatching petroleum products. Oper. Res. 43 (1995) 379–387. [Google Scholar]
  • C.E.H. Ross and L.E. Sloan, Terra Incognita: A Navigation Aid for Energy Leaders. Pennwell Corporation (2007). [Google Scholar]
  • S.J.K. Sahith, K.V. Rao and P.S. Rao, Design and surge study of Salaya Mathura pipeline for higher throughput of crude oil transportation. Mater. Today: Proc. 5 (2018) 5459–5466. [CrossRef] [Google Scholar]
  • H.M. Salkin and K. Mathur, Foundations of Integer Programming. Elsevier Science Publishing Co., Inc. (1989). [Google Scholar]
  • H.D. Sherali, S. Al-Yakoob and M.M. Hassan, Fleet management models and algorithms for an oil-tanker routing and scheduling problem. IIE Trans. (Inst. Ind. Eng.) 31 (1999) 395–406. [Google Scholar]
  • A.W. Siddiqui and M. Verma, A bi-objective approach to routing and scheduling maritime transportation of crude oil. Transp. Res. Part D: Transp. Environ. 37 (2015) 65–78. [CrossRef] [Google Scholar]
  • M. Simmons, Twilight in the Desert: The Coming Saudi Oil Shock and the world economy. John Wiley & Sons (2005). [Google Scholar]
  • J.-H. Song and K.C. Furman, A maritime inventory routing problem: practical approach. Comput. Oper. Res. 40 (2013) 657–665. [Google Scholar]
  • D.G. Victor, D.R. Hults and M. Thurber, editors,Oil and Governance: State-owned Enterprises and the World Energy Supply. Cambridge University Press (2012). [Google Scholar]
  • C. Vilhelmsen, J. Larsen and R.M. Lusby, Tramp Ship Routing and Scheduling – Models, Methods and Opportunities. DTU Management Engineering (2015). [Google Scholar]
  • D. Yergin, The Quest: Energy, Security, and the Remaking of the Modern World, Penguin Books, Pearson (2012). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.