PORT CAPACITY FORECASTING AND THE IMPACT OF THE DREDGING WORKS ON PORT SEA OPERATIONS USING DISCRETE EVENT SIMULATION

Atef Salem Souf-Aljen, Adi Maimun, Rahimuddin Rahimuddin, Noor Zairie

Abstract


Continuous capacity expansion is vital for ports to handle future growth due to the  increase in volume of maritime transport and size of the vessels. Some improvements and developments are required for the port to enhance its capacity throughput. In order to accommodate huge vessels without any restrictions, there is a need to deepen the channels. Furthermore, there is also need to widen the channel to prevent congestions. However, dredging work for deepening the harbour waters will reduce the utilization of the berths and navigational areas. This will significantly affect the port capacity and hence its income. In this paper a simulation program based on queuing theory and discrete event simulation is developed and used for forecasting port throughput and simulating dredging conditions. Data from a container port and an Automatic Identification System (AIS) were utilised to develop the simulation program in MATLAB-Simulink. Using this tool, port capacity was simulated and the effect of dredging on port capacity was studied. An appropriate period of time needed for dredging is determined by taking into considerations the blocking of some berths and limiting the number of vessels passing the channels during the dredging operations. The results from the simulations could then be used for planning the dredging works

Keywords


Marine safety, dredging and reclamation works, AIS, queuing theory, discrete-event simulation, port capacity

Full Text:

PDF

References


Adi Maimun, Istaz F. Nursyirman, Ang Yit Sian, Rahimuddin and Sulaiman Oladokun. 2013. Using AIS Data for Navigational Risk Assessment in Restricted Waters. IGL Global. Hershey, USA 2013.

MB Zaman, E Kobayashi, N Wakabayashi, S Khanfir, T Pitana, A Mainmun. 2014. Fuzzy FMEA Model For Risk Evaluation Of Ship Collisions in the Malacca Strait: based on AIS data. Journal of Simulation. 8(1): 91-104.

Branislav Dragovi , Nam-Kyu Park , Nenad D . Zrni, and Romeo Me strove. 2012. Mathematical Models of Multi Server Queuing System for Dynamic Performance Evaluation in Port. Mathematical Problems in Engineering, Vol. 2012, Article ID 710834, 19 pages doi:10.1155/2012/710834 Hindawi Publishing Corporation.

Nam-Kyu Park and Branislav Dragović. 2009. A Study of Container Terminal Planning. FME Transactions. 37(4): 203-209.

D. N. Zrnic, B. M. Dragovic, and Z. R. Radmilovic.1999. Anchorage-ship-berth link as multiple server queuing system. Journal of Waterway, Port, Coastal and Ocean Engineering. 125(5): 232–240.

Dahal, K.P., Galloway, S., Burty, G.M., McDonald, J.R. and Hopkins, I. 2003. A Port System Simulation Facility With An Optimization Capability. International Journal of Computational Intelligence and Applications. 3(4): 395-410.

Canonaco, P., Legato, P., Mazza, R.M. and Musmanno, R. 2008. A Queuing Network Model For The Management Of Berth Crane Operations. Computers & Operations Research. 35(8): 2432-2446.

Petering, M.E.H. and Murty, K.G. 2009. Effect Of Block Length And Yard Crane Deployment Systems On Overall Performance At A Seaport Container Transshipment Terminal. Computers & Operations Research. 36(5): 1711-1725.

Petering, M.E.H. 2009. Effect Of Block Width And Storage Yard Layout On Marine Container Terminal Performance. Transportation Research Part E: Logistics and Transportation Review. 45(4): 591-610.

Petering, M., Wu, Y., Li, W., Goh, M. and De Souza, R. 2009. Development And Simulation Analysis Of Real-Time Yard Crane Control Systems For Seaport Container Transshipment Terminals. OR Spectrum. 31(4): 801-835.

Cartenì, Armando, and Stefano De Luca. 2012. Tactical And Strategic Planning For A Container Terminal: Modelling Issues Within A Discrete Event Simulation Approach. Simulation Modelling Practice and Theory. 21(1): 123-145.

Almaz, OzhanAlper, and TayfurAltiok. 2012. Simulation Modelling Of The Vessel Traffic In Delaware River: Impact Of Deepening On Port Performance. Simulation Modelling Practice and Theory. 22: 146-165.

Dragovic, B., Zrnic, Dj. N., Twrdy, E., Rooy, DK. 2010. Ship Traffic Modelling And Performance Evaluation In Container Port. Analele UniversităŃii, Eftimie Murgu. XVII(2): 127-138.

Dragović B., Park N. K., Radmilović Z. 2006. Ship-Berth Link Performance Evaluation: Simulation And Analytical Approache. Maritime Policy &Management, 2006, 33(3): 281-299.

S. Kos, M. Hess, S. Hess.2006. A Simulation Method in Modelling Exploitation Factors of Seaport Queuing Systems .Pomorstvo, God. 20, Br. 1: 67-85.

Tu-Cheng Kuo, Wen-Chih Huang, Sheng-Chieh Wu, and Pei-Lun Cheng .2006. A Case Study of Inter-Arrival Time Distributions of Container Ships. Journal of Marine Science and Technology. 14(3): 155-164




DOI: http://dx.doi.org/10.11113/jt.v78.9692

Refbacks

  • There are currently no refbacks.


Copyright © 2012 Penerbit UTM Press, Universiti Teknologi Malaysia.
Disclaimer : This website has been updated to the best of our knowledge to be accurate. However, Universiti Teknologi Malaysia shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.
Best viewed: Mozilla Firefox 4.0 & Google Chrome at 1024 × 768 resolution.