corresponding Author: Aelentably@kau.edu.sa
Container terminal management is a very complex process involving many vital decisions to develop many appropriate solutions to increase plant productivity. There is a special allocation for the spaces of the places where containers are collected. Here is the problem of what the allocated area is. Then there is a decision that must be made. Then the decisions regarding the cranes and which suits the squares and what are the other ones that fit the berths. Emissions resulting from the operation of cranes and therefore a vital decision in this regard. The number of suitable cranes for loading and unloading with the container ships. Here is the location of another vital decision. What is the total area suitable for that station and the principles of dividing the area between the exported containers and the incoming containers? What are the containers that guarantee the hazardous materials, the container gates and the internal roads of the station? In order to maximize the economic return and productivity higher than the break- even point. Simulators are an important tool to rationalize decisions and achieve target productivity. This is the objective of the present paper to provide the contribution of simulation techniques to serve the container terminal in order to enhance the collaboration with terminal components and help reducing costs.
Keywords: transportation, berth management, scheduling, simulation, optimization
- Baird, A. J. 2002. The economics of container transhipment in Northern Europe. International Journal of Maritime Economics, 4, 249-280. Barros, C. P. 2003 .
]2[Bichou, K. & Gray, R. 2005. A critical review of conventional terminology for classifying seaports. Transportation Research Part A: Policy and Practice, 39, 75-92.
- Carbone, V. & De Martino, M. 2003. The changing role of ports in supply-chain management: an empirical study. Maritime Policy & Management, 30, 305-320 .
- Chao, S. L. & Lin, Y. J. 2011. Evaluating advanced quay cranes in container terminals. Transportation Research Part E: Logistics and Transportation Review, 47, 432-445. ]5[Dekker, S. 2005. Port investment: towards an integrated planning of port capacity. PhD Thesis, Netherlands TRAIL Research School. Grossmann, I. 2008 .
- Henesey, L., Davidsson, P. & Persson, J. A. 2009. Evaluation of automated guided vehicle systems for container terminals using multi agent-based simulation
- NUNO, D., JAIME, S. & O, S. (eds.) Multi-Agent-Based Simulation IX. Springer-Verlag. Henesey, L. E. 2006 .
- Islam, S. & Olsen, T. L. Factors affecting seaport capacity. 19th International Congress on Modelling and Simulation, 2011 Perth, Western Australia. 412-418.
- Kim, K. 1998. A transportation planning model for state highway management: A decision support system methodology to achieve sustainable development. Doctor of Philosophy, Virginia Polytechnic Institute and Sate University.
- Maani, K. E. & Cavana, R. Y. 2000. Systems thinking and modelling: understanding change and complexity, Auckland, Pearson Education .
- Marlow, P. B. & Paixão Casaca, A. C. 2003. Measuring lean ports performance. International Journal of Transport Management, 1, 189-202.
- Martin, J. & Thomas, B. J. 2001. The container terminal community. Maritime Policy & Management, 28, 279-292 .
- Ocean Shipping Consultants Limited. 2009. North European container markets to 2020. Available: http://biodata.asp4all.nl/andreas/2010/09012f97806ff81b/09012f97806ff81b.pdf [Accessed 10 August, 2011.]
- Pallis, A. A. & De Langen, P. W. 2010. Seaports and the structural implications of the economic crisis. Research in Transportation Economics, 27, 10-18 .