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The reloading of a ship in a maritime container terminal as a queuing problem of interacting processes

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this work, we propose a multi-server queuing system for modeling the processes that occur in a maritime container terminal. In our study, the main operations that take place at the quay and in the yard are first disaggregated into several elementary activities. Then we propose the step-by-step calculation of the times of each operation that influences both the unloading and the loading of a container. Next, we analyze the vessel cycle time while separately investigating the STS (ship to shore) crane cycle time, the RTG (rubber tyred gantry) cycle time, as well as the IMV (internal movement vehicle) transfer time. Finally, we apply two process-driven simulation experiments to the system analysis. The paper demonstrates the proposed model’s effectiveness with data from the BCT Gdynia container terminal. We show that, among others, even with properly planned work of STS cranes and RTGs, there is still a high probability that the quay will become a bottleneck of the described processes.
Rocznik
Strony
17--33
Opis fizyczny
Bibliogr. 32 poz., rys.
Twórcy
  • Department of Operational Research, University of Lodz, Lodz, Poland
  • Department of Operational Research, University of Lodz, Lodz, Poland
Bibliografia
  • [1] Bartosiewicz, A. Terminal operating systems as a tool to support entrepreneurship and competitiveness of sea ports. Przedsi˛ebiorczos´c i Zarz ˛adzanie 15 ´ , 10 (2014), 175–187.
  • [2] Bartosiewicz, A. Planning of cargo routes from the quay to the storage yard at the sea container terminal in Gdansk. Studia Ekonomiczne. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicach 235 (2015), 18–33 (in Polish).
  • [3] Bartosiewicz, A. Maritime transport of containers. The role and importance of intermodal transshipment terminals. Wydawnictwo Uniwersytetu Łódzkiego, 2020 (in Polish).
  • [4] Bartosiewicz, A., and Kucharski, A. The determination of times of transshipment processes at maritime container terminals. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation 16, 3 (2022), 507–513.
  • [5] Beskovnik, E., and Twrdy, B. Productivity simulation model for optimization of maritime container terminals. Transport Problems 4, 3 (2009), 113–122.
  • [6] Canonaco, P., Legato, P., Mazza, R. M., and Musmanno, R. A queuing network model for the management of berth crane operations. Computers and Operations Research 35, 8 (2008), 2432–2446.
  • [7] Oyatoye E. O., Adebiyi, S. O., Chinweze A. J., and Bolanle, A. B. Application of queueing theory to port congestion problem in Nigeria. European Journal of Business and Management 3, 8 (2011), 24–36.
  • [8] Collier, Z. A., Hendrickson, D., Polmateer, T. L., and Lambert, J. H. Scenario analysis and PERT/CPM applied to strategic investment at an automated container port. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 4, 3 (2018), 04018026.
  • [9] Deja, M., Dobrzyński, M., Siemia¸tkowski, M. S., and Wiśniewska, A. Simulation studies into quayside transport and storage yard operations in container terminals. Polish Maritime Research 24, S1 (2017), 46–52.
  • [10] Dirman, E. N., Pallu, S., and Ramli, I. Queuing simulation and container crane utilization at the Makassar Container Terminal. International Journal of Innovative Technology and Exploring Engineering 8, 4S (2019), 302–305.
  • [11] El-Naggar, M. E. Application of queuing theory to the container terminal at Alexandria seaport. Journal of Soil Science and Environmental Management 1, 4 (2010), 77–85.
  • [12] Elentably, A. Simulation of a container terminal and its reflect on port economy. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation 10, 2 (2016), 331–337.
  • [13] Gui, J. S., and Yang, C. X. The queuing model and simulation of container terminal based on liner transport. Applied Mechanics and Materials 253-255 (2012), 1167–1170.
  • [14] Gumuskaya, V., van Jaarsveld, W., Dijkman, R., Grefen, P., and Veenstra, A. A framework for modeling and analysing coordination challenges in hinterland transport systems. Maritime Economics and Logistics 22, 1 (2020), 124–145.
  • [15] He, Y. Y., and Hu, Y. H. Synchronized loading and unloading containers method based on simultaneous hatches operations Applied Mechanics and Materials 201-202 (2012), 939–942.
  • [16] Hora, S. C. Spreadsheet modeling of the G/G/c queuing system without macros or add-ins. INFORMS Transactions on Education 3, 3 (2003), 86–89.
  • [17] Ingolfsson, A., and Grossman, Jr., T. A. Graphical spreadsheet simulation of queues. INFORMS Transactions on Education 2, 2 (2002), 27–39.
  • [18] Ji, M., Zhu, H., Wang, Q., Zhao, R., and Yang, Y. Integrated strategy for berth allocation and crane assignment on a continuous berth using Monte Carlo simulation. Simulation 91, 1 (2015), 26–42.
  • [19] Lee, S.-Y., and Cho, G.-S. A simulation study for the operations analysis of dynamic planning in container terminals considering RTLS. In Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007), (Kumamoto, Japan, 2007), IEEE, pp. 457–460.
  • [20] Legato, P., and Mazza, R. M. Berth planning and resources optimisation at a container terminal via discrete event simulation. European Journal of Operational Research 133, 3 (2001), 537–547.
  • [21] Legato, P., and Mazza, R. M. Queueing analysis for operations modeling in port logistics. Maritime Business Review 5, 1 (2019), 67–83.
  • [22] Leong, T.-Y. Simpler spreadsheet simulation of multi-server queues. INFORMS Transactions on Education 7, 2 (2007), 172–177.
  • [23] Mašće, I., , Singolo, R., and Jurišić, I. Network planning method in optimizing vessel utilization – laytime calculation. Naše More 65, 3 (2018), 146–150.
  • [24] Meng, Q., Weng, J., and Suyi, L. Impact analysis of mega vessels on container terminal operations. Transportation Research Procedia 25 (2017), 187–204.
  • [25] Meštrović, R., Dragović, B., Zrnić, N., and Dragojević, D. A relationship between different costs of container yard modelling in port using queuing approach. FME Transactions 46, 3 (2018), 367–373.
  • [26] Mishra, N., Roy, D., and van Ommeren, J.-K. A stochastic model for interterminal container transportation. Transportation Science 51, 1 (2017), 67–87.
  • [27] Park, S.-W., Lee, M.-K., and Park, Y.-S. Analysis and improvement of communications in port areas using the queuing theory. The Journal of Navigation 73, 4 (2020), 912–931.
  • [28] Petering, M. E. H., and Murty, K. G. Effect of block length and yard crane deployment systems on overall performance at a seaport container transshipment terminal. Computers and Operations Research 36, 5 (2009), 1711–1725.
  • [29] Ruscă, F., Popa, M., Roşca, E., Roşca, M., and Ruscă, A. Simulation model for maritime container terminal. Transport Problems 13, 4 (2019), 47–54.
  • [30] Sgouris, S. P., and Angelides, D. C. Simulation-based analysis of handling inbound containers in a terminal. In Proceedings of the Winter Simulation Conference, (San Diego, CA, USA, 2002), E. Yücesan, C.-H. Chen, J. L. Snowdon, and J. M.Charnes, Eds., IEEE, pp. 1716–1724.
  • [31] Shahpanah, A., Shariatmadari, S., Chegeni, A., Gholamkhasi, A., and Shahpanah, M. Improvement in queuing network model to reduce waiting time at berthing area of port container terminal via discrete event simulation. Applied Mechanics and Materials 621 (2014), 253–258.
  • [32] Szpytko, J., and Salgado Duarte Y. A digital twins concept model for integrated maintenance: a case study for crane operation. Journal of Intelligent Manufacturing 32, 7 (2021), 1863–1881.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2ea83bd9-8bf3-49ee-875f-9cfcd97769e9
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