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Integrated planning of downstream petroleum supply chain: a multi-objective stochastic approach

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  • Pudasaini, Pramesh

Abstract

In studying petroleum supply chain networks, past studies have largely segregated three critical decision-making aspects: integrated planning, uncertainties, and multi-objective setting. This study focuses on consolidating these aspects and proposes a stochastic, multi-objective, mixed-integer linear programming model for strategic and tactical planning of downstream petroleum supply chain (DPSC) networks. Demand, considered the uncertain parameter, is modeled using a two-stage stochastic approach based on scenarios. The model—designed for multiple supply centers, distribution centers, products, and transportation modes—also considers transshipment between the centers. The objective functions consider simultaneous minimization of transportation cost and product loss cost that is incurred during transportation between the centers. The application of the proposed model is demonstrated with a case study of a real-world DPSC network undergoing construction of new pipelines and expansion of storage facilities. The augmented ε-constraint method is used to solve the model. Interesting trade-offs in the case study are analyzed, aiding the decision-makers in exploiting the model as a decision-support tool to better understand the complexity, flexibility, and risk of integrated decision-making under uncertainty.

Suggested Citation

  • Pudasaini, Pramesh, 2021. "Integrated planning of downstream petroleum supply chain: a multi-objective stochastic approach," Operations Research Perspectives, Elsevier, vol. 8(C).
  • Handle: RePEc:eee:oprepe:v:8:y:2021:i:c:s2214716021000129
    DOI: 10.1016/j.orp.2021.100189
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    References listed on IDEAS

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    1. Georgiadis, Michael C. & Tsiakis, Panagiotis & Longinidis, Pantelis & Sofioglou, Maria K., 2011. "Optimal design of supply chain networks under uncertain transient demand variations," Omega, Elsevier, vol. 39(3), pages 254-272, June.
    2. Escudero, Laureano F. & Quintana, Francisco J. & Salmeron, Javier, 1999. "CORO, a modeling and an algorithmic framework for oil supply, transformation and distribution optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 114(3), pages 638-656, May.
    3. Moradi Nasab, N. & Amin-Naseri, M.R., 2016. "Designing an integrated model for a multi-period, multi-echelon and multi-product petroleum supply chain," Energy, Elsevier, vol. 114(C), pages 708-733.
    4. S.A. Torabi & J. Namdar & S.M. Hatefi & F. Jolai, 2016. "An enhanced possibilistic programming approach for reliable closed-loop supply chain network design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(5), pages 1358-1387, March.
    5. Kazemi, Yasaman & Szmerekovsky, Joseph, 2015. "Modeling downstream petroleum supply chain: The importance of multi-mode transportation to strategic planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 111-125.
    6. Mavrotas, George & Florios, Kostas, 2013. "An improved version of the augmented epsilon-constraint method (AUGMECON2) for finding the exact Pareto set in Multi-Objective Integer Programming problems," MPRA Paper 105034, University Library of Munich, Germany.
    7. M A H Dempster & N Hicks Pedrón & E A Medova & J E Scott & A Sembos, 2000. "Planning logistics operations in the oil industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(11), pages 1271-1288, November.
    8. Al-Othman, Wafa B.E. & Lababidi, Haitham M.S. & Alatiqi, Imad M. & Al-Shayji, Khawla, 2008. "Supply chain optimization of petroleum organization under uncertainty in market demands and prices," European Journal of Operational Research, Elsevier, vol. 189(3), pages 822-840, September.
    9. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
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