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Multi-agent optimization of the intermodal terminal main parameters by using AnyLogic simulation platform: Case study on the Ningbo-Zhoushan Port

Author

Listed:
  • Muravev, Dmitri
  • Hu, Hao
  • Rakhmangulov, Aleksandr
  • Mishkurov, Pavel

Abstract

Due to numerous uncertainties such as bad weather conditions, frequent changes in the schedules of vessels, breakdowns of equipment, port managers are aiming at providing adaptive and flexible strategic planning of their facilities, especially intermodal terminals. In this research, we investigate a two-stage optimization of intermodal terminals main parameters via using AnyLogic simulation platform. We have developed a set of hybrid simulation models to optimize the main parameters of intermodal terminals which are also called dry ports. To make an express evaluation of the preliminary implementation of dry ports, we have developed an agent-based system dynamics simulation model to achieve the stable state of the main parameters of intermodal terminals. To clarify the obtained averaged benefits of the main dry ports parameters while the port managers make key decisions on the investments into implementation of intermodal terminals, we have developed an agent-based discrete-event simulation model of a seaport – a dry port system. We show that the combination of the agent-based modeling with other simulation approaches simplifies the process of designing simulation models and increases their visibility. The developed set of models allows us to compute the balanced values of the parameters, while an effective operation of a seaport – intermodal terminal system is achieved. On the basis of the provided case study on one of the busiest ports in China, we prove the adequacy and validity of the developed simulation models. Due to the lack of systematic approach to optimization of the main parameters of intermodal terminals in logistic industry, our findings set herein could improve the decision-making process related to the selection of strategic facility planning in the field of intermodal terminals.

Suggested Citation

  • Muravev, Dmitri & Hu, Hao & Rakhmangulov, Aleksandr & Mishkurov, Pavel, 2021. "Multi-agent optimization of the intermodal terminal main parameters by using AnyLogic simulation platform: Case study on the Ningbo-Zhoushan Port," International Journal of Information Management, Elsevier, vol. 57(C).
  • Handle: RePEc:eee:ininma:v:57:y:2021:i:c:s026840121931789x
    DOI: 10.1016/j.ijinfomgt.2020.102133
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    Citations

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    Cited by:

    1. El Yaagoubi, Amina & Ferjani, Aicha & Essaghir, Yasmina & Sheikhahmadi, Farrokh & Abourraja, Mohamed Nezar & Boukachour, Jaouad & Baron, Marie-Laure & Duvallet, Claude & Khodadad-Saryazdi, Ali, 2022. "A logistic model for a french intermodal rail/road freight transportation system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    2. Khalil Tliba & Thierno M. L. Diallo & Olivia Penas & Romdhane Ben Khalifa & Noureddine Ben Yahia & Jean-Yves Choley, 2023. "Digital twin-driven dynamic scheduling of a hybrid flow shop," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2281-2306, June.
    3. Demartini, Melissa & Bertani, Filippo & Tonelli, Flavio & Raberto, Marco & Cincotti, Silvano, 2021. "An investigation into modelling approaches for industrial symbiosis: a literature review," MPRA Paper 107448, University Library of Munich, Germany.
    4. Li, Xiangda & Peng, Yun & Tian, Qi & Feng, Tao & Wang, Wenyuan & Cao, Zhen & Song, Xiangqun, 2023. "A decomposition-based optimization method for integrated vehicle charging and operation scheduling in automated container terminals under fast charging technology," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    5. Golghamat Raad, Nima & Rajendran, Suchithra, 2024. "A hybrid scenario-based fuzzy stochastic model for closed-loop dry port network design with multiple robustness measures," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).

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