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Rule based optimization for a bulk handling port operations

Author

Listed:
  • Saurabh Pratap

    (Indian Institute of Technology)

  • Yash Daultani

    (Indian Institute of Management)

  • M. K. Tiwari

    (Indian Institute of Technology)

  • Biswajit Mahanty

    (Indian Institute of Technology)

Abstract

In this paper a study on the operations of a bulk material port is carried out to develop a decision support model, which deals with the dynamics of port and aids in better decision making at different scenarios. Here, we describe various decisions taken by port authorities pertaining to the import of coal at the terminal. We optimize these decisions with the aim of minimizing the unloading time of ships at the port, congestion in the stockyard, and loading time of the rakes. A practice-oriented decision support model is proposed to assist port planners in making these decisions. Various operational rules are embedded within the model, for carrying out the modelling of various port operations. The utility of the developed model is demonstrated using a case study which helps in achieving efficient utilization of berths, stockyard and rake loading stations.

Suggested Citation

  • Saurabh Pratap & Yash Daultani & M. K. Tiwari & Biswajit Mahanty, 2018. "Rule based optimization for a bulk handling port operations," Journal of Intelligent Manufacturing, Springer, vol. 29(2), pages 287-311, February.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:2:d:10.1007_s10845-015-1108-7
    DOI: 10.1007/s10845-015-1108-7
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    References listed on IDEAS

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    1. Lu Zhen & Ek Peng Chew & Loo Hay Lee, 2011. "An Integrated Model for Berth Template and Yard Template Planning in Transshipment Hubs," Transportation Science, INFORMS, vol. 45(4), pages 483-504, November.
    2. Singh, Gaurav & Sier, David & Ernst, Andreas T. & Gavriliouk, Olena & Oyston, Rob & Giles, Tracey & Welgama, Palitha, 2012. "A mixed integer programming model for long term capacity expansion planning: A case study from The Hunter Valley Coal Chain," European Journal of Operational Research, Elsevier, vol. 220(1), pages 210-224.
    3. Zhen, Lu, 2014. "Container yard template planning under uncertain maritime market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 199-217.
    4. Akio Imai & Jin-Tao Zhang & Etsuko Nishimura & Stratos Papadimitriou, 2007. "The Berth Allocation Problem with Service Time and Delay Time Objectives," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 9(4), pages 269-290, December.
    5. Lee, Yusin & Chen, Chuen-Yih, 2009. "An optimization heuristic for the berth scheduling problem," European Journal of Operational Research, Elsevier, vol. 196(2), pages 500-508, July.
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    Cited by:

    1. Cao, Zhen & Wang, Wenyuan & Jiang, Ying & Xu, Xinglu & Xu, Yunzhuo & Guo, Zijian, 2022. "Joint berth allocation and ship loader scheduling under the rotary loading mode in coal export terminals," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 229-260.
    2. Jia Hao & Mengying Zhou & Guoxin Wang & Liangyue Jia & Yan Yan, 2020. "Design optimization by integrating limited simulation data and shape engineering knowledge with Bayesian optimization (BO-DK4DO)," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 2049-2067, December.
    3. Dhirendra Prajapati & Yash Daultani & Naoufel Cheikhrouhou & Saurabh Pratap, 2020. "Identification and ranking of key factors impacting efficiency of Indian shipping logistics sector," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 765-786, September.

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