Autonomous Agents and Multi-Agent Systems

, Volume 18, Issue 2, pp 220–238 | Cite as

Agent based simulation architecture for evaluating operational policies in transshipping containers

  • Lawrence Henesey
  • Paul DavidssonEmail author
  • Jan A. Persson


An agent based simulator for evaluating operational policies in the transshipment of containers in a container terminal is described. The simulation tool, called SimPort, is a decentralized approach to simulating managers and entities in a container terminal. Real data from two container terminals are used as input for evaluating eight transshipment policies. The policies concern the sequencing of ships, berth allocation, and stacking rule. They are evaluated with respect to a number of aspects, such as, turn-around time for ships and traveled distance of straddle carriers. The simulation results indicate that a good choice in yard stacking and berthing position policies can lead to faster ship turn-around times. For instance, in the terminal studied the Overall-Time-Shortening policy offers fast turn-around times when combined with a Shortest-Job-First sequencing of arriving ships.


Agent-based simulation Container terminal management Policy evaluation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Davidson, N. (2005). A global capacity assessment and needs analysis. In Proceedings of the 39th Terminal Operating Conference, Antwerp, Belgium.Google Scholar
  2. 2.
    Frankel E.G. (1987). Port Planning and Development. Wiley, New York Google Scholar
  3. 3.
    De Monie, G. (2006). Inter-port cooperation and competition: Developing transshipment operations in the Mediterranean Environmental Scanning in Ports. In Proceedings of the Fourth MedTrade 2006, St. Julians, Malta.Google Scholar
  4. 4.
    Vis I.F.A. and de Koster R. (2003). Transshipment of containers at a container terminal: An overview. European Journal of Operational Research, 147: 1–16 zbMATHCrossRefGoogle Scholar
  5. 5.
    Meersmans, P. J. M., & Dekker, R. (2001). Operations research supports container handling. Technical Report, The Netherlands Econometric Institute Report EI 2001–22. Econometric Institute, Erasmus University, Rotterdam, November 2.Google Scholar
  6. 6.
    Steenken D., Vos S. and Stahlback R. (2004). Container terminal operations and operations research—a classification and literature review. OR Spectrum, 26: 3–49 zbMATHCrossRefGoogle Scholar
  7. 7.
    Henesey, L. (2004). Enhancing container terminals: A multi-agent systems approach. Licentiate Thesis. Department of Systems and Software Engineering, Blekinge Institute of Technology, Sweden, pp. 1–132.Google Scholar
  8. 8.
    Ocean Shipping Consultants. (2006). European and Mediterranean Containerport Markets to 2015. Surrey, UK: Ocean Shipping Consultants, Ltd.Google Scholar
  9. 9.
    Baird A. (2006). Optimising the container transshipment hub location in northern Europe. Journal of Transport Geography, 14(3): 195–214 CrossRefGoogle Scholar
  10. 10.
    Wilson I.D. and Roach P.A. (2000). Container stowage planning: A methodology for generating computerised solutions. Journal of the Operational Research Society, 51(11): 1248–1255 zbMATHCrossRefGoogle Scholar
  11. 11.
    Henesey L., Davidsson P. and Persson J.A. (2006). Evaluating container terminal transshipment operational policies: An agent based simulation approach. WSEAS Transaction on Computers, 5(9): 2090–2098 Google Scholar
  12. 12.
    Wooldridge M. (2002). An Introduction to Multi Agent Systems. Wiley, West Sussex Google Scholar
  13. 13.
    Parunak, H. V. D., Savit, R., & Riolo, R. L. (1998). Agent-based modeling vs. equation-based modeling: A case study and users’ guide. In Multi-agent Systems and Agent-based Simulation, LNAI, J. S. Sichman, R. Conte, & N. Gilbert, (vol. 1534, pp. 10–26). Springer-Verlag.Google Scholar
  14. 14.
    Law A.M. and Kelton W.D. (2000). Simulation Modeling and Analysis (3rd ed). McGraw-Hill International, Boston Google Scholar
  15. 15.
    Davidsson P., Henesey L., Ramstedt L., Törnquist J. and Wernstedt F. (2005). An analysis of agent-based approaches to transport logistics. Transportation Research: Part C: Emerging Technologies, 13(4): 255–271 CrossRefGoogle Scholar
  16. 16.
    Henesey, L. (2006). Multi-agent systems for container terminal management. Ph.D. Thesis, School of Engineering, Blekinge Institute of Technology, Karlshamn, Sweden Dissertation Series no. 2006:08, pp. 185–202.Google Scholar
  17. 17.
    Liu C.-I., Hossein J. and Ioannou P.A. (2002). Design, simulation, and evaluation of automated container terminals. IEEE Transaction on Intelligent Transportation Systems, 3: 12–26 CrossRefGoogle Scholar
  18. 18.
    Buchheit, M., Kuhn, N., Müller, J. P., & Pischel, M. (1992). MARS: Modeling a multiagent scenario for shipping companies. In Proceedings of the European Simulation Symposium (ESS-92), Dresden, Germany.Google Scholar
  19. 19.
    Degano, C., & Pellegrino, A. (2002). Multi-agent coordination and collaboration for control and optimization strategies in an intermodal container terminal. In Proceedings of the IEEE International Engineering Management Conference (IEMC-2002), Cambridge, UK.Google Scholar
  20. 20.
    Rebollo, M., Julian, V., Carrascosa, C., & Botti, V. (2000). A multi-agent system for the automation of a port container terminal. In Proceedings of Autonomous Agents 2000 Workshop on Agents in Industry, Barcelona, Spain.Google Scholar
  21. 21.
    Rebollo, M., Julian, V., Carrascosa, C., & Botti, V. (2001). A MAS approach for port container terminal management. In Proceedings of the 3rd Iberoamerican Workshop on DAI-MAS, Atibaia, Sao Paulo, Brazil.Google Scholar
  22. 22.
    Carrascosa, C., Rebollo, M., Julian, V., & Botti, V. (2001). A MAS approach for port container terminal management: The transtainer agent. In Proceedings of the International Conference on Information Systems, Analysis and Synthesis, Orlando, US.Google Scholar
  23. 23.
    Thurston, T., & Hu, H. (2002). Distributed agent architecture for port automation. In Proceedings of the 26th International Computer Software and Applications Conference (COMPSAC 2002), Oxford, UK.Google Scholar
  24. 24.
    Yun W.Y. and Choi Y.S. (1999). A simulation model for container-terminal operation analysis using an object-oriented approach. International Journal of Production Economics, 59: 221–230 CrossRefGoogle Scholar
  25. 25.
    Lee, T.-W., Park, N.-K., & Lee, D.-W. (2002). Design of simulation system for port resources availability in logistics supply chain. In Proceedings of the International Association of Maritime Economists Annual Conference, (IAME 2002), Panama City, Panama.Google Scholar
  26. 26.
    Lokuge, P., Alahakoon, D., & Dissanayake, P. (2004). Collaborative neuro-BDI agents in container terminals. In 18th International Conference on Advanced Information Networking and Applications Vol. 2, pp. 155–158.Google Scholar
  27. 27.
    Lokuge, P., & Alahakoon, D. (2004). Hybrid BDI agents with improved learning capabilities for adaptive planning in a container terminal application. International Conference on Intelligent Agent Technology, IEEE/WIC/ACM, 120–126.Google Scholar
  28. 28.
    Lokuge P. and Alahakoon D. (2004). Enhancing efficiency of container terminal operations using homogenous intelligent agents. International Association of Maritime Economists Annual Conference, Turkey Google Scholar
  29. 29.
    Gambardella L.M., Rizzoli A.E. and Zaffalon M. (1998). Simulation and planning of an intermodal container terminal. Simulation, 71: 107–116 CrossRefGoogle Scholar
  30. 30.
    Blackstone J.H., Jr., Phillips D.T. and Hogg G.L. (1982). A state-of-the-art survey of dispatching rules for manufacturing job shop operations. International Journal of Production Research, 20(1): 27–45 CrossRefGoogle Scholar
  31. 31.
    Green G.I. and Appel L.B. (1981). Journal of Operations Management, 1(4): 197–204 CrossRefGoogle Scholar
  32. 32.
    Henesey, L., Notteboom, T., & Davidsson, P. (2003). Agent-based simulation of stakeholders relations: An approach to sustainable port and terminal management. In Proceedings of the International Association of Maritime Economists Annual Conference, (IAME 2003), Busan, Korea.Google Scholar
  33. 33.
    Iglesias, C. A., Garijo, M., Centeno-Gonzalez, J., & Velasco, J. R. (1998). Analysis and design of multiagent systems using MAS-CommonKADS. In Intelligent Agents IV, LNCS (Vol. 1365, pp. 313–326). Springer-Verlag.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Lawrence Henesey
    • 1
  • Paul Davidsson
    • 2
    Email author
  • Jan A. Persson
    • 1
  1. 1.Department of Systems and Software EngineeringBlekinge Institute of TechnologyKarlshamnSweden
  2. 2.Department of Systems and Software EngineeringBlekinge Institute of TechnologyRonnebySweden

Personalised recommendations