Impact of megaships on the performance of port container terminals

  • Enrico MussoEmail author
  • Anna Sciomachen
Original Article


Following the advent of megaships, the performance requirements of container terminals have increased significantly, highlighting necessary changes in their layout, infrastructure, and equipment. We focus on the impact of megaships on a terminal within the port network of the Italian Region of Liguria, in terms of its ability to manage the flow of imports from arrival to inland destinations. We use discrete event simulation techniques to analyze the operations of a terminal and evaluate the relevant performance indices in different scenarios, which vary as a function of the “call size” of the larger containerships. The possibility of guaranteeing a more balanced modal split (favoring rail transport) for the inland distribution of containers is also evaluated. Dwell times at the yard and turnaround times at the berth are considered, with the objective of achieving a modal split of inland transport consisting of no less than 40% rail. Our results show that this objective can be achieved if a higher dwell time for outgoing containers is allowed.


Logistics Maritime container terminal Discrete event simulation Performance indices Megaships 



This work has been partially supported by the PRIN 2015 Project: “Smart PORt Terminals – SPORT: Gate Operations and inland forwarding,” funded by the Italian Ministry of Education, University and Research. We are most grateful to the MEL reviewers for their exceptionally detailed and in-depth work, and for their useful comments which allowed significant improvement in the quality of this paper.


  1. Ballis, A., and J. Golias. 2004. Towards the improvement of a combined transport chain performance. European Journal of Operational Research 152 (2): 420–436.CrossRefGoogle Scholar
  2. Bielli, M., A. Boulmakoul, and M. Rida. 2006. Object oriented model for container terminal distributed simulation. European Journal of Operational Research 144 (1): 83–107.Google Scholar
  3. Carlo, H., I. Vis, and K. Roddbergen. 2013. Seaside operations in container terminals: Literature overview, trends, and research directions. Journal of Production Research 49: 6199–6226.Google Scholar
  4. Carlo, H., I. Vis, and K. Roddbergen. 2014. Storage yard operations in container terminals: Literature overview, trends, and research directions. European Journal of Operational Research 235: 412–430.CrossRefGoogle Scholar
  5. Cartení, A., and S. De Luca. 2012. Tactical and strategic planning for a container terminal: Modelling issues within discrete event simulation approach. Simulation Modelling Practice and Theory 21: 123–145.CrossRefGoogle Scholar
  6. Chen, G., and Z.Z. Yang. 2010. Optimizing time windows for managing arrivals of export containers at Chinese container terminals. Maritime Economics & Logistics 12: 111–126.CrossRefGoogle Scholar
  7. Dulebenets, M.A., M.M. Golias, S. Mishra, and W.C. Heaslet. 2015. Evaluation of the floaterm concept at marine container terminals via simulation. Simulation Modelling Practice and Theory 54: 19–35.CrossRefGoogle Scholar
  8. Gambardella, L.M., A.E. Rizzoli, and M. Zaffalon. 1998. Simulation and planning of an intermodal container terminal. Simulation 71 (2): 107–116.CrossRefGoogle Scholar
  9. Haralambides, H.E. 2017. Globalization, public sector reform, and the role of ports in international supply chains. Maritime Economics & Logistics 19 (1): 1–51.CrossRefGoogle Scholar
  10. Haralambides, H.E. 2019. Gigantism in container shipping, ports and global logistics: a time-lapse into the future. Maritime Economics & Logistics 21 (1): 1–60.CrossRefGoogle Scholar
  11. Accessed Jan 2018.
  12. Kaveshgar, N., and N. Huynh. 2015. Integrated quay crane and yard truck scheduling for unloading inbound containers. International Journal of Production Economics 159 (2015): 168–177.CrossRefGoogle Scholar
  13. Lanner Group Ltd. 2017. Witness. Discrete event simulation with VR available on desktop and cloud. Henley-in-Arden: Lanner Group Ltd.Google Scholar
  14. Law, A.M. 2007. Simulation modelling and analysis. New York: McGraw-Hill.Google Scholar
  15. Legato, P., and R.M. Mazza. 2001. Berth planning and resources optimisation at a container terminal via discrete event simulation. European Journal of Operational Research 133: 537–547.CrossRefGoogle Scholar
  16. Maibach M., C. Schreyer, D. Sutter, H.P. van Essen, B.H. Boon, R. Smokers, A. Schroten, C. Doll, B. Pawlowska, and M. Bak. 2008 Handbook on estimation of external costs in the transport sector, Internalisation Measures and Policies for All External Cost of Transport. IMPACT Project, Version 1.1, European Commission DG TREN, CE Delft, The Netherlands.Google Scholar
  17. OECD/ITF 2015. The Impact of Mega-Ships, Case-Specific Policy Analysis.Google Scholar
  18. Parola, F., and A. Sciomachen. 2005. Intermodal container flows in a port system network: Analysis of possible growths via simulation models. International Journal of Production Economics 97 (1): 75–88.CrossRefGoogle Scholar
  19. Parola, F., and A. Sciomachen. 2009. Modal split evaluation of a maritime container terminal. Maritime Economics & Logistics 11: 77–97.CrossRefGoogle Scholar
  20. Qiang, M., W. Jinxiam, and L. Suyi. 2017. Impact analysis of mega vessels on container terminal operations. Transportation Research Procedia 25: 187–204.CrossRefGoogle Scholar
  21. Rizzoli, A., N. Fornara, and L.M. Gambardella. 2002. A simulation tool for combined rail/road transport in intermodal terminals. Mathematics and Computers in Simulation 59 (1–3): 57–71.CrossRefGoogle Scholar
  22. Sharif, O., N. Huynh, and J.M. Vidal. 2011. Application of El Farol model for managing marine terminal gate congestion. Research in Transportation Economics 32: 81–89.CrossRefGoogle Scholar
  23. Stahlbock, R., and S. Voß. 2008. Operations research at container terminals: a literature update. OR Spectrum 30 (1): 1–52.CrossRefGoogle Scholar
  24. Steenken, D., S. Voß, and R. Stahlbock. 2004. Container terminal operation and operations research—a classification and literature review. OR Spectrum 26: 3–49.CrossRefGoogle Scholar
  25. Sys, C., G. Blauwens, E. Omey, E. Van De Voorde, and F. Witlox. 2008. In search of the link between ship size and operations. Transportation Planning and Technology 31 (4): 435–463.CrossRefGoogle Scholar
  26. Tran, N.K., and H.D. Haasis. 2015. An empirical study of fleet expansion and growth of ship size in container liner shipping. International Journal of Production Economics 159: 241–253.CrossRefGoogle Scholar
  27. Veloqui, M., I. Turias, and M.M. Cerbán. 2014. Simulating the landside congestion in a container terminal. The experience of the port of Naples (Italy). Procedia-Social and Behavioural Sciences 160: 615–624.CrossRefGoogle Scholar
  28. Waller A. 2012. Witness Simulation Software. Proceedings of the 2012 Winter Simulation Conference C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A.M. Uhrmacher, eds.Google Scholar

Copyright information

© Springer Nature Limited 2019

Authors and Affiliations

  1. 1.Department of Economics and Business Studies & CIELI (Italian Centre of Excellence for Integrated Logistics and Transport)University of GenoaGenoaItaly

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