IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v20y2020i4d10.1007_s12351-018-0400-7.html
   My bibliography  Save this article

An MILP approach for scheduling of tree-like pipelines with dual purpose terminals

Author

Listed:
  • Mehrnoosh Taherkhani

    (Islamic Azad University)

Abstract

Pipelines represent the most reliable and economical mode of fluid transportation in the petroleum supply chain. They are often multi-product systems and are extensively used to carry different types of petroleum derivatives from refineries to distribution depots. This paper addresses the optimal scheduling of a treelike pipeline that connects several refineries to multiple depots and that meets the customer demands over a multi-period planning horizon. A continuous time scheduling formulation based on a mixed integer linear programing framework is presented which allows intermediate nodes to act as dual purpose stations. The problem goal is to satisfy local market requirements on time while keeping the inventory levels at depot tanks within feasible ranges. Solutions to three case studies show remarkable reductions in the CPU time with regards to previous contributions.

Suggested Citation

  • Mehrnoosh Taherkhani, 2020. "An MILP approach for scheduling of tree-like pipelines with dual purpose terminals," Operational Research, Springer, vol. 20(4), pages 2133-2161, December.
    • Handle: RePEc:spr:operea:v:20:y:2020:i:4:d:10.1007_s12351-018-0400-7
    DOI: 10.1007/s12351-018-0400-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-018-0400-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12351-018-0400-7?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. Relvas, Susana & Boschetto Magatão, Suelen N. & Barbosa-Póvoa, Ana Paula F.D. & Neves, Flávio, 2013. "Integrated scheduling and inventory management of an oil products distribution system," Omega, Elsevier, vol. 41(6), pages 955-968.
    2. Ali Zaghian & Hossein Mostafaei, 2016. "An MILP model for scheduling the operation of a refined petroleum products distribution system," Operational Research, Springer, vol. 16(3), pages 513-542, October.
    3. Zhang, Haoran & Liang, Yongtu & Liao, Qi & Wu, Mengyu & Yan, Xiaohan, 2017. "A hybrid computational approach for detailed scheduling of products in a pipeline with multiple pump stations," Energy, Elsevier, vol. 119(C), pages 612-628.
    4. Danielle Zyngier & Jeffrey D. Kelly, 2009. "Multi-Product Inventory Logistics Modeling in the Process Industries," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Kevin C. Furman & Panos M. Pardalos (ed.), Optimization and Logistics Challenges in the Enterprise, pages 61-95, Springer.
    Full references (including those not matched with items on IDEAS)

    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. M. Taherkhani & M. Seifbarghy & R. Tavakkoli-Moghaddam & P. Fattahi, 2020. "Mixed-integer linear programming model for tree-like pipeline scheduling problem with intermediate due dates on demands," Operational Research, Springer, vol. 20(1), pages 399-425, March.
    2. Mostafaei, Hossein & Castro, Pedro M. & Relvas, Susana & Harjunkoski, Iiro, 2021. "A holistic MILP model for scheduling and inventory management of a multiproduct oil distribution system," Omega, Elsevier, vol. 98(C).
    3. Kirschstein, Thomas, 2018. "Planning of multi-product pipelines by economic lot scheduling models," European Journal of Operational Research, Elsevier, vol. 264(1), pages 327-339.
    4. Long, Yin & Yoshida, Yoshikuni & Fang, Kai & Zhang, Haoran & Dhondt, Maya, 2019. "City-level household carbon footprint from purchaser point of view by a modified input-output model," Applied Energy, Elsevier, vol. 236(C), pages 379-387.
    5. Wu, Yan & Xia, Tianqi & Wang, Yufei & Zhang, Haoran & Feng, Xiao & Song, Xuan & Shibasaki, Ryosuke, 2022. "A synchronization methodology for 3D offshore wind farm layout optimization with multi-type wind turbines and obstacle-avoiding cable network," Renewable Energy, Elsevier, vol. 185(C), pages 302-320.
    6. Jonek-Kowalska Izabela, 2014. "Financial aspects of changes in the level of finished goods inventory in a mining enterprise," Gospodarka Surowcami Mineralnymi / Mineral Resources Management, Sciendo, vol. 30(4), pages 1-20, December.
    7. Shanbi Peng & Zhe Zhang & Yongqiang Ji & Laimin Shi, 2022. "Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search Algorithm," Energies, MDPI, vol. 15(20), pages 1-19, October.
    8. Zheng, Jianqin & Wang, Chang & Liang, Yongtu & Liao, Qi & Li, Zhuochao & Wang, Bohong, 2022. "Deeppipe: A deep-learning method for anomaly detection of multi-product pipelines," Energy, Elsevier, vol. 259(C).
    9. Wolfgang Albrecht & Martin Steinrücke, 2020. "Continuous-time scheduling of production, distribution and sales in photovoltaic supply chains with declining prices," Flexible Services and Manufacturing Journal, Springer, vol. 32(3), pages 629-667, September.
    10. Neda Beheshti Asl & S. A. MirHassani & S. Relvas & F. Hooshmand, 2022. "A novel two-phase decomposition-based algorithm to solve MINLP pipeline scheduling problem," Operational Research, Springer, vol. 22(5), pages 4829-4863, November.
    11. Sağlam, Ümit & Banerjee, Avijit, 2018. "Integrated multiproduct batch production and truck shipment scheduling under different shipping policies," Omega, Elsevier, vol. 74(C), pages 70-81.
    12. Longinidis, Pantelis & Georgiadis, Michael C., 2014. "Integration of sale and leaseback in the optimal design of supply chain networks," Omega, Elsevier, vol. 47(C), pages 73-89.
    13. Zhang, Haoran & Liang, Yongtu & Liao, Qi & Wu, Mengyu & Yan, Xiaohan, 2017. "A hybrid computational approach for detailed scheduling of products in a pipeline with multiple pump stations," Energy, Elsevier, vol. 119(C), pages 612-628.
    14. Velez, Sara & Dong, Yachao & Maravelias, Christos T., 2017. "Changeover formulations for discrete-time mixed-integer programming scheduling models," European Journal of Operational Research, Elsevier, vol. 260(3), pages 949-963.
    15. Li, Zhengbing & Feng, Huixia & Liang, Yongtu & Xu, Ning & Nie, Siming & Zhang, Haoran, 2019. "A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo," International Journal of Critical Infrastructure Protection, Elsevier, vol. 27(C).
    16. Li, Yanfeng & Szeto, W.Y. & Long, Jiancheng & Shui, C.S., 2016. "A multiple type bike repositioning problem," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 263-278.
    17. Fan, Mu-wei & Ao, Chu-chu & Wang, Xiao-rong, 2019. "Comprehensive method of natural gas pipeline efficiency evaluation based on energy and big data analysis," Energy, Elsevier, vol. 188(C).
    18. Long, Yin & Yoshida, Yoshikuni & Meng, Jing & Guan, Dabo & Yao, Liming & Zhang, Haoran, 2019. "Unequal age-based household emission and its monthly variation embodied in energy consumption – A cases study of Tokyo, Japan," Applied Energy, Elsevier, vol. 247(C), pages 350-362.
    19. 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.
    20. Matsumoto, Ken׳ichi & Andriosopoulos, Kostas, 2016. "Energy security in East Asia under climate mitigation scenarios in the 21st century," Omega, Elsevier, vol. 59(PA), pages 60-71.

    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:spr:operea:v:20:y:2020:i:4:d:10.1007_s12351-018-0400-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.