IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v83y2015icp111-125.html
   My bibliography  Save this article

Modeling downstream petroleum supply chain: The importance of multi-mode transportation to strategic planning

Author

Listed:
  • Kazemi, Yasaman
  • Szmerekovsky, Joseph

Abstract

This paper proposes a deterministic mixed integer linear programming (MILP) model for downstream petroleum supply chain (PSC) network to determine the optimal distribution center (DC) locations, capacities, transportation modes, and transfer volumes. The model minimizes multi-echelon multi-product cost along the refineries, distribution centers, transportation modes and demand nodes. The relationship between strategic planning and multimodal transportation is further elucidated. A case study was considered with real data from the U.S. petroleum industry and transportation networks within Geographic Information System (GIS). A scenario analysis is also conducted to demonstrate the impact of key parameters on PSC decisions and total cost.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:transe:v:83:y:2015:i:c:p:111-125
    DOI: 10.1016/j.tre.2015.09.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554515001696
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2015.09.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tingting Cui & Yanfeng Ouyang & Zuo-Jun Max Shen, 2010. "Reliable Facility Location Design Under the Risk of Disruptions," Operations Research, INFORMS, vol. 58(4-part-1), pages 998-1011, August.
    2. Chryssolouris, George & Papakostas, Nikolaos & Mourtzis, Dimitris, 2005. "Refinery short-term scheduling with tank farm, inventory and distillation management: An integrated simulation-based approach," European Journal of Operational Research, Elsevier, vol. 166(3), pages 812-827, November.
    3. 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.
    4. Olivares-Benitez, Elias & Ríos-Mercado, Roger Z. & González-Velarde, José Luis, 2013. "A metaheuristic algorithm to solve the selection of transportation channels in supply chain design," International Journal of Production Economics, Elsevier, vol. 145(1), pages 161-172.
    5. Tsao, Yu-Chung & Lu, Jye-Chyi, 2012. "A supply chain network design considering transportation cost discounts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 401-414.
    6. David Ronen, 1995. "Dispatching Petroleum Products," Operations Research, INFORMS, vol. 43(3), pages 379-387, June.
    7. Cui, Tingting & Ouyang, Yanfeng & Shen, Zuo-Jun Max J, 2010. "Reliable Facility Location Design under the Risk of Disruptions," University of California Transportation Center, Working Papers qt5sh2c7pw, University of California Transportation Center.
    8. Sarkar, Biswajit & Majumder, Arunava, 2013. "A study on three different dimensional facility location problems," Economic Modelling, Elsevier, vol. 30(C), pages 879-887.
    9. Li, Xiaopeng, 2013. "An integrated modeling framework for design of logistics networks with expedited shipment services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 46-63.
    10. Ross, Anthony D., 2000. "Performance-based strategic resource allocation in supply networks," International Journal of Production Economics, Elsevier, vol. 63(3), pages 255-266, January.
    11. SteadieSeifi, M. & Dellaert, N.P. & Nuijten, W. & Van Woensel, T. & Raoufi, R., 2014. "Multimodal freight transportation planning: A literature review," European Journal of Operational Research, Elsevier, vol. 233(1), pages 1-15.
    12. J. S. Aronofsky & A. C. Williams, 1962. "The Use of Linear Programming and Mathematical Models in Under-Ground Oil Production," Management Science, INFORMS, vol. 8(4), pages 394-407, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emenike, Scholastica N. & Falcone, Gioia, 2020. "A review on energy supply chain resilience through optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    2. Chen, Yan & Huang, Zhenhua & Ai, Hongshan & Guo, Xingkun & Luo, Fan, 2021. "The Impact of GIS/GPS Network Information Systems on the Logistics Distribution Cost of Tobacco Enterprises," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    3. Carmona-Benítez, Rafael Bernardo & Cruz, Héctor, 2023. "A multiproduct gasoline supply chain with product standardization and postponement strategy," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    4. Tu, Renfu & Jiao, Yingqi & Qiu, Rui & Liao, Qi & Xu, Ning & Du, Jian & Liang, Yongtu, 2023. "Energy saving and consumption reduction in the transportation of petroleum products: A pipeline pricing optimization perspective," Applied Energy, Elsevier, vol. 342(C).
    5. Özceylan, Eren & Çetinkaya, Cihan & Erbaş, Mehmet & Kabak, Mehmet, 2016. "Logistic performance evaluation of provinces in Turkey: A GIS-based multi-criteria decision analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 323-337.
    6. Bahman Naderi & Kannan Govindan & Hamed Soleimani, 2020. "A Benders decomposition approach for a real case supply chain network design with capacity acquisition and transporter planning: wheat distribution network," Annals of Operations Research, Springer, vol. 291(1), pages 685-705, August.
    7. Cortinhal, M. J. & Lopes, M. J. & Melo, M. T., 2018. "Impact of partial product outsourcing, transportation mode selection, and single-assignment requirements on the design of a multi-stage supply chain network," Technical Reports on Logistics of the Saarland Business School 15, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    8. Sylvia Mardiana, 2023. "Gasoline Policy Simulation to Increase Responsiveness Using System Dynamics: A Case Study of Indonesia’s Gasoline Downstream Supply Chain," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 109-118, November.
    9. Pudasaini, Pramesh, 2021. "Integrated planning of downstream petroleum supply chain: a multi-objective stochastic approach," Operations Research Perspectives, Elsevier, vol. 8(C).
    10. Gupta, Dipti & Dhar, Subash, 2022. "Exploring the freight transportation transitions for mitigation and development pathways of India," Transport Policy, Elsevier, vol. 129(C), pages 156-175.
    11. Wang, Shuang & Wallace, Stein W. & Lu, Jing & Gu, Yewen, 2020. "Handling financial risks in crude oil imports: Taking into account crude oil prices as well as country and transportation risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    12. Lu, Ying & Fang, Sidun & Niu, Tao & Liao, Ruijin, 2023. "Energy-transport scheduling for green vehicles in seaport areas: A review on operation models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    13. Farahani, Mohsen & Rahmani, Donya, 2017. "Production and distribution planning in petroleum supply chains regarding the impacts of gas injection and swap," Energy, Elsevier, vol. 141(C), pages 991-1003.
    14. de Assis, Leonardo Salsano & Camponogara, Eduardo, 2016. "A MILP model for planning the trips of dynamic positioned tankers with variable travel time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 372-388.
    15. Kumar, Sourabh & Barua, Mukesh Kumar, 2022. "A modeling framework and analysis of challenges faced by the Indian petroleum supply chain," Energy, Elsevier, vol. 239(PE).
    16. Klepikov, Vladimir Pavlovich & Klepikov, Vladimir Vladimirovich, 2020. "Quantitative approach to estimating crude oil supply in Southern Europe," Resources Policy, Elsevier, vol. 69(C).
    17. Chen, Jingxu & Wang, Shuaian & Liu, Zhiyuan & Guo, Yanyong, 2018. "Network-based optimization modeling of manhole setting for pipeline transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 38-55.
    18. Archetti, Claudia & Peirano, Lorenzo & Speranza, M. Grazia, 2022. "Optimization in multimodal freight transportation problems: A Survey," European Journal of Operational Research, Elsevier, vol. 299(1), pages 1-20.
    19. Aragão, Amanda & Giampietro, Mario, 2016. "An integrated multi-scale approach to assess the performance of energy systems illustrated with data from the Brazilian oil and natural gas sector," Energy, Elsevier, vol. 115(P2), pages 1412-1423.
    20. Chen, Haihong & Zuo, Lili & Wu, Changchun & Li, Qingping, 2019. "An MILP formulation for optimizing detailed schedules of a multiproduct pipeline network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 142-164.
    21. Baykasoğlu, Adil & Subulan, Kemal, 2016. "A multi-objective sustainable load planning model for intermodal transportation networks with a real-life application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 207-247.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yun, Lifen & Qin, Yong & Fan, Hongqiang & Ji, Changxu & Li, Xiaopeng & Jia, Limin, 2015. "A reliability model for facility location design under imperfect information," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 596-615.
    2. Ansari, Sina & Başdere, Mehmet & Li, Xiaopeng & Ouyang, Yanfeng & Smilowitz, Karen, 2018. "Advancements in continuous approximation models for logistics and transportation systems: 1996–2016," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 229-252.
    3. Dasci, Abdullah & Huang, Rongbing, 2017. "A continuous approximation method for dynamic pricing problem under costly price modifications," Omega, Elsevier, vol. 72(C), pages 38-49.
    4. Cui, Jianxun & Zhao, Meng & Li, Xiaopeng & Parsafard, Mohsen & An, Shi, 2016. "Reliable design of an integrated supply chain with expedited shipments under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 143-163.
    5. Fateme Fotuhi & Nathan Huynh, 2017. "Reliable Intermodal Freight Network Expansion with Demand Uncertainties and Network Disruptions," Networks and Spatial Economics, Springer, vol. 17(2), pages 405-433, June.
    6. Marufuzzaman, Mohammad & Eksioglu, Sandra D. & Li, Xiaopeng & Wang, Jin, 2014. "Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 122-145.
    7. Campbell, James F., 2013. "A continuous approximation model for time definite many-to-many transportation," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 100-112.
    8. Weijun Xie & Yanfeng Ouyang & Sze Chun Wong, 2016. "Reliable Location-Routing Design Under Probabilistic Facility Disruptions," Transportation Science, INFORMS, vol. 50(3), pages 1128-1138, August.
    9. An, Yu & Zhang, Yu & Zeng, Bo, 2015. "The reliable hub-and-spoke design problem: Models and algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 103-122.
    10. Chen, Ruoran & Deng, Tianhu & Huang, Simin & Qin, Ruwen, 2015. "Optimal crude oil procurement under fluctuating price in an oil refinery," European Journal of Operational Research, Elsevier, vol. 245(2), pages 438-445.
    11. Albareda-Sambola, Maria & Hinojosa, Yolanda & Puerto, Justo, 2015. "The reliable p-median problem with at-facility service," European Journal of Operational Research, Elsevier, vol. 245(3), pages 656-666.
    12. Li, Qingwei & Savachkin, Alex, 2013. "A heuristic approach to the design of fortified distribution networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 138-148.
    13. Azad, Nader & Hassini, Elkafi, 2019. "Recovery strategies from major supply disruptions in single and multiple sourcing networks," European Journal of Operational Research, Elsevier, vol. 275(2), pages 481-501.
    14. Yun Hui Lin & Yuan Wang & Loo Hay Lee & Ek Peng Chew, 2021. "Robust facility location with structural complexity and demand uncertainty," Flexible Services and Manufacturing Journal, Springer, vol. 33(2), pages 485-507, June.
    15. Donya Rahmani, 2019. "Designing a robust and dynamic network for the emergency blood supply chain with the risk of disruptions," Annals of Operations Research, Springer, vol. 283(1), pages 613-641, December.
    16. An, Shi & Cui, Na & Li, Xiaopeng & Ouyang, Yanfeng, 2013. "Location planning for transit-based evacuation under the risk of service disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 1-16.
    17. Yun, Lifen & Fan, Hongqiang & Li, Xiaopeng, 2019. "Reliable facility location design with round-trip transportation under imperfect information part II: A continuous model," Transportation Research Part B: Methodological, Elsevier, vol. 124(C), pages 44-59.
    18. Jeong, Yoonjea & Kim, Gwang, 2023. "Reliable design of container shipping network with foldable container facility disruption," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    19. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2021. "Robust facility location under demand uncertainty and facility disruptions," Omega, Elsevier, vol. 103(C).
    20. Zhang, Yanzi & Diabat, Ali & Zhang, Zhi-Hai, 2021. "Reliable closed-loop supply chain design problem under facility-type-dependent probabilistic disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 180-209.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:83:y:2015:i:c:p:111-125. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.