IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v54y2016i8p2241-2259.html
   My bibliography  Save this article

Modelling of coal trade process for the logistics enterprise and its optimisation with stochastic predictive control

Author

Listed:
  • Qifeng Cheng
  • Shiwei Ning
  • Xiaohua Xia
  • Fan Yang

Abstract

In the paper, a typical coal trade process is described and modelled, where one logistics enterprise with blending equipments lies in the core and two types of common contracts are elucidated to define constraints. A mixed-integer model is built and featured by addressing contract violation, blending operation, real-time price information and arbitrarily distributed stochastic demands. To deal with the stochastic demands, probabilistic constraints are formed. Accordingly, stochastic model predictive control strategy with both receding horizon and decreasing horizon formulations is developed to handle the probabilistic constraints and exploit the value of newest price information. By solving a series of mixed-integer linear programmes, optimal coal trade decisions for the logistics enterprise can be obtained, including procurement decision, selling decision and operational decision of the blending equipments. Thorough simulation experiments are carried out and compared with three different strategies, which interpret the effectiveness of the proposed strategy.

Suggested Citation

  • Qifeng Cheng & Shiwei Ning & Xiaohua Xia & Fan Yang, 2016. "Modelling of coal trade process for the logistics enterprise and its optimisation with stochastic predictive control," International Journal of Production Research, Taylor & Francis Journals, vol. 54(8), pages 2241-2259, April.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:8:p:2241-2259
    DOI: 10.1080/00207543.2015.1062568
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2015.1062568
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2015.1062568?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. Shih, Jhih-Shyang & Frey, H. Christopher, 1995. "Coal blending optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 83(3), pages 452-465, June.
    2. van Staden, Adam Jacobus & Zhang, Jiangfeng & Xia, Xiaohua, 2011. "A model predictive control strategy for load shifting in a water pumping scheme with maximum demand charges," Applied Energy, Elsevier, vol. 88(12), pages 4785-4794.
    3. Sherali, HD & Puri, R, 1993. "Models for a coal blending and distribution problem," Omega, Elsevier, vol. 21(2), pages 235-243, March.
    4. Peter Berling & Victor Martínez-de-Albéniz, 2011. "Optimal Inventory Policies when Purchase Price and Demand Are Stochastic," Operations Research, INFORMS, vol. 59(1), pages 109-124, February.
    5. Charles J. Corbett & Deming Zhou & Christopher S. Tang, 2004. "Designing Supply Contracts: Contract Type and Information Asymmetry," Management Science, INFORMS, vol. 50(4), pages 550-559, April.
    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. Zeng, Lanyan & Liu, Shi Qiang & Kozan, Erhan & Corry, Paul & Masoud, Mahmoud, 2021. "A comprehensive interdisciplinary review of mine supply chain management," Resources Policy, Elsevier, vol. 74(C).
    2. Li, Hangxin & Wang, Shengwei, 2022. "Comparative assessment of alternative MPC strategies using real meteorological data and their enhancement for optimal utilization of flexibility-resources in buildings," Energy, Elsevier, vol. 244(PA).

    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. Anna Danandeh & Bo Zeng & Brent Caldwell & Brian Buckley, 2016. "A Decision Support System for Fuel Supply Chain Design at Tampa Electric Company," Interfaces, INFORMS, vol. 46(6), pages 503-521, December.
    2. Liu, Chiun-Ming & Sherali, Hanif D., 2000. "A coal shipping and blending problem for an electric utility company," Omega, Elsevier, vol. 28(4), pages 433-444, August.
    3. Akgün, İbrahim & Özkil, Altan & Gören, Selçuk, 2020. "A multimodal, multicommodity, and multiperiod planning problem for coal distribution to poor families," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    4. Jiao Wang & Lima Zhao & Arnd Huchzermeier, 2021. "Operations‐Finance Interface in Risk Management: Research Evolution and Opportunities," Production and Operations Management, Production and Operations Management Society, vol. 30(2), pages 355-389, February.
    5. Scott, James & Ho, William & Dey, Prasanta K. & Talluri, Srinivas, 2015. "A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments," International Journal of Production Economics, Elsevier, vol. 166(C), pages 226-237.
    6. Xin Yun & Hao Liu & Yi Li & Kin Keung Lai, 2023. "Contract design under asymmetric demand information for sustainable supply chain practices," Annals of Operations Research, Springer, vol. 324(1), pages 1429-1459, May.
    7. Ni, Jian & Zhao, Jun & Chu, Lap Keung, 2021. "Supply contracting and process innovation in a dynamic supply chain with information asymmetry," European Journal of Operational Research, Elsevier, vol. 288(2), pages 552-562.
    8. Yan, Ruiliang & Ghose, Sanjoy, 2010. "Forecast information and traditional retailer performance in a dual-channel competitive market," Journal of Business Research, Elsevier, vol. 63(1), pages 77-83, January.
    9. Canyakmaz, Caner & Özekici, Süleyman & Karaesmen, Fikri, 2019. "An inventory model where customer demand is dependent on a stochastic price process," International Journal of Production Economics, Elsevier, vol. 212(C), pages 139-152.
    10. Lin Chen & Jin Peng & Zhibing Liu & Ruiqing Zhao, 2017. "Pricing and effort decisions for a supply chain with uncertain information," International Journal of Production Research, Taylor & Francis Journals, vol. 55(1), pages 264-284, January.
    11. Ümit Sakallı & Ömer Baykoç & Burak Birgören, 2011. "Stochastic optimization for blending problem in brass casting industry," Annals of Operations Research, Springer, vol. 186(1), pages 141-157, June.
    12. İsmail Bakal & Nesim Erkip & Refik Güllü, 2011. "Value of supplier’s capacity information in a two-echelon supply chain," Annals of Operations Research, Springer, vol. 191(1), pages 115-135, November.
    13. Filipe, Jorge & Bessa, Ricardo J. & Reis, Marisa & Alves, Rita & Póvoa, Pedro, 2019. "Data-driven predictive energy optimization in a wastewater pumping station," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    14. Clavijo López, Christian & Crama, Yves & Pironet, Thierry & Semet, Frédéric, 2024. "Multi-period distribution networks with purchase commitment contracts," European Journal of Operational Research, Elsevier, vol. 312(2), pages 556-572.
    15. Amiya K. Chakravarty & Jun Zhang, 2007. "Collaboration in contingent capacities with information asymmetry," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(4), pages 421-432, June.
    16. Yi Yang & Jianan Wang & Youhua Chen & Zhiyuan Chen & Yanchu Liu, 2020. "Optimal procurement strategies for contractual assembly systems with fluctuating procurement price," Annals of Operations Research, Springer, vol. 291(1), pages 1027-1059, August.
    17. Wanjiru, Evan M. & Sichilalu, Sam M. & Xia, Xiaohua, 2017. "Model predictive control of heat pump water heater-instantaneous shower powered with integrated renewable-grid energy systems," Applied Energy, Elsevier, vol. 204(C), pages 1333-1346.
    18. Youhua (Frank) Chen & Weili Xue & Jian Yang, 2013. "Technical Note---Optimal Inventory Policy in the Presence of a Long-Term Supplier and a Spot Market," Operations Research, INFORMS, vol. 61(1), pages 88-97, February.
    19. Chen, Yenming J. & Sheu, Jiuh-Biing, 2017. "Non-differentiated green product positioning: Roles of uncertainty and rationality," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 248-260.
    20. Matsui, Kenji, 2019. "A supply chain member should set its margin later if another member's cost is highly uncertain," European Journal of Operational Research, Elsevier, vol. 275(1), pages 127-138.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tprsxx:v:54:y:2016:i:8:p:2241-2259. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.