Reducing Ship Queuing Time in Port Operation: A Modelling and Simulation Approach

  • Authors

    • Fazeeda Binti Mohamad
    • Nurul Shahadah Binti Osman Mydin
    • Ahmad A.N.Aizat
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.20.18992
  • Queuing time, Simulation, ARENA software, Container loading and unloading, TEUs

  • Abstract

    This study focuses on reducing queuing time in port operation by using discrete event simulation approach. This study was conducted to analyze the port operation activity in order to improve their performance in terms of time operation. A model was developed and simulated by mimicking the real port operation system using a case study. Two scenarios were experimented to see the effects or improvements in the queuing time of container loading and unloading activities. The result demonstrates the positive improvement on the queuing time for container to be loading and unloading.

     

     

  • References

    1. [1] Alessandri, A., Sacone, S., & Siri, S. (2006). Modelling and Optimal Receding-horizon Control of Maritime Container Terminals. J Math Model Algor, 6(1), 109-133. doi:10.1007/s10852-006-9052-3

      [2] Bruzzone, A. G. (1998). Harbour and Maritime Simulation. SIMULATION, 71(2), 72-73. doi:10.1177/003754979807100201

      [3] Chang, Y., & Chen, C. (2006). Knowledge-based simulation of bunkering services in the port of Kaohsiung. Civil Engineering and Environmental Systems, 23(1), 21-34. doi:10.1080/10286600600585625

      [4] Chen, E. J., & Kelton, W. D. (2007). A Procedure for Generating Batch-Means Confidence Intervals for Simulation: Checking Independence and Normality. SIMULATION, 83(10), 683-694. doi:10.1177/0037549707086039

      [5] Cortés, P., Muñuzuri, J., Nicolás Ibáñez, J., & Guadix, J. (2004). Simulation of freight traffic in the Seville inland port. Simulation Modelling Practice and Theory, 15(3), 256-271. doi:10.1016/j.simpat.2006.11.004

      [6] Dahal, K., Galloway, S., Burt, G., Mcdonald, J., & Hopkins, I. (2003). A Port System Simulation Facility with An Optimization Capability. Int. J. Comp. Intel. Appl, 03(04), 395-410. doi:10.1142/s1469026803001099

      [7] De Swaan Arons, H., & Van Asperen, E. (n.d.). Computer assistance for model definition. 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165). doi:10.1109/wsc.2000.899745

      [8] Edmond, E. D., & Maggs, R. P. (1978). How Useful are Queue Models in Port Investment Decisions for Container Berths? J Oper Res Soc, 29(8), 741-750. doi:10.1057/jors.1978.162

      [9] Goobie, G., & Arbez, G. (2013). The Modelling and Simulation Process. Modelling and Simulation, 19-51. doi:10.1007/978-1-4471-2783-3_2

      [10] Hunecker, F. (2013). A generic process simulationâ€model for educational simulations and serious games. On the Horizon, 17(4), 313-322. doi:10.1108/10748120910998371

      [11] J.J. Shields. (1984). Container Stowage: A computer aided pre-planning system Marine Technology, 21(4).

      [12] K.H. Kim. (2004). Deriving decision rules to locate export containers in container yards,124(2000), 89-101.

      [13] Kia, M. P. (1992). Minimize Cost of Berthing (Port of Melbourne). National Conference Publication -Institution of Engineers, Australia, 92(8), 231-237.

      [14] Kim, K. H., & Park, Y. (2004). A crane scheduling method for port container terminals.European Journal of Operational Research, 156(3), 752-768. doi:10.1016/s0377-2217(03)00133-4

      [15] Krajewski, L. J., & Ritzman, L. P. (2002). Operations Management: Strategy and Analysis (2nd Edition). The Journal of the Operational Research Society, 43(4), 367. doi:10.2307/2583162

      [16] Law, A. M. (2008). How to build valid and credible simulation models. 2008 Winter Simulation Conference. doi:10.1109/wsc.2008.4736054

      [17] Legato, P., & Mazza, R. M. (2001). Berth planning and resources optimisation at a container terminal via discrete event simulation. European Journal of Operational Research,133(3), 537-547. doi:10.1016/s0377-2217(00)00200-9

      [18] Maria, A. (1997). Introduction to modeling and simulation. Proceedings of the 29th conference on Winter simulation - WSC '97. doi:10.1145/268437.268440

      [19] Maria, A. (1997). Introduction to modelling and simulation. Proceedings of the 29th conference on Winter simulation - WSC '97. doi:10.1145/268437.268440

      [20] Martagan, T. G., Eksioglu, B., Eksioglu, S. D., & Greenwood, A. G. (2009). A simulation model of port operations during crisis conditions. Proceedings of the 2009 Winter Simulation Conference (WSC). doi:10.1109/wsc.2009.5429245

      [21] Ranau, M. (2011). Planning Approach for Dimensioning of Automated Traffic Areas at Seaport Container Terminals. Operations Research/Computer Science Interfaces Series, 179-193. doi:10.1007/978-1-4419-8408-1_10

      [22] Rossetti D. (2010). Simulation Modelling and ARENA, 2-3.

      [23] Sacone, S., & Siri, S. (2009). An integrated simulation-optimization framework for the operational planning of seaport container terminals. Mathematical and Computer Modelling of Dynamical Systems, 15(3), 275-293. doi:10.1080/13873950902808636

      [24] Sasso, D., & Biles, W. E. (2008). An object-oriented programming approach for a GIS data-driven simulation model of traffic on an inland waterway. 2008 Winter Simulation Conference. doi:10.1109/wsc.2008.4736372

      [25] Shahpanah, A., S. Shariatmadari, Ali Chegeni, A. Gholamkhasi, and M. Shahpanah. 2014. "Improvement in Queuing Network Model to Reduce Waiting Time at Berthing Area of Port Container Terminal via Discrete Event Simulation", Applied Mechanics and Materials

      [26] Schriber, T. J., Brunner, D. T., & Smith, J. S. (2013). Inside discrete-event simulation software: How it works and why it matters. 2013 Winter Simulations Conference (WSC). doi:10.1109/wsc.2013.6721439

      [27] Somantri, A. S., & Thahir, R. (2007). Dynamic system analysis of rice availability in Merauke. Dynamic System Analysis of Rice Availability in Merauke, 3.

      [28] Steenken, D. (2004). Container terminal operation and operations research - a classification and literature review. OR Spectrum, 26(1), 3-49. doi:10.1007/s00291-003-0157-z

      [29] Steenken, D., Voß, S., & Stahlbock, R. (n.d.). Container terminal operation and operations research — a classification and literature review. Container Terminals and Automated Transport Systems, 3-49. doi:10.1007/3-540-26686-0_1

      [30] UMEDA, S., & JONES, A. (1999). A Simulation-Based BPR Support System for Supply Chain Management. The Quest for World-Class Excellence, 95-117. doi:10.1142/9781848160576_0006

      [31] Valentin, E., Steijaert, S., Bijlsma, R., & Silva, P. (n.d.). Approach for Modeling of Large Maritime Infrastructure Systems. Proceedings of the Winter Simulation Conference, 2005. doi:10.1109/wsc.2005.1574426

      [32] Van Rensburg, J., Yi He, & Kleywegt, A. (n.d.). A Computer Simulation Model of Container Movement by Sea. Proceedings of the Winter Simulation Conference, 2005. doi:10.1109/wsc.2005.1574424

      [33] Vis, I. F., & De Koster, R. (2003). Transshipment of containers at a container terminal: An overview. European Journal of Operational Research, 147(1), 1-16. doi:10.1016/s0377-2217(02)00293-x

      [34] Wilson, I. D., & Roach, P. A. (2000). Container Stowage Planning: A Methodology for Generating Computerised Solutions. The Journal of the Operational Research Society,51(11), 1248. doi:10.2307/254210

      [35] Worldshipping, (2012). (Accessed 17.03.13). (n.d.). . Retrieved from (Accessed 17.03.13)

      [36] Yang, C. H., Choi, Y. S., & Ha, T. Y. (2004). Simulation-based performance evaluation of transport vehicles at automated container terminals. OR Spectrum, 26(2), 149-170. doi:10.1007/s00291-003-0151-5

      [37] Zrnić, D. N., Dragović, B. M., & Radmilović, Z. R. (1999). Anchorage-Ship-Berth Link as Multiple Server Queuing System. J. Waterway, Port, Coastal, Ocean Eng, 125(5), 232-240. doi:10.1061/(asce)0733-950x(1999)125:5(232).

  • Downloads

  • How to Cite

    Binti Mohamad, F., Shahadah Binti Osman Mydin, N., & A.N.Aizat, A. (2018). Reducing Ship Queuing Time in Port Operation: A Modelling and Simulation Approach. International Journal of Engineering & Technology, 7(3.20), 114-118. https://doi.org/10.14419/ijet.v7i3.20.18992

    Received date: 2018-09-04

    Accepted date: 2018-09-04

    Published date: 2018-09-01