Practical solutions for reducing container ships’ waiting times at ports using simulation model

Abstract

The main challenge for container ports is the planning required for berthing container ships while docked in port. Growth of containerization is creating problems for ports and container terminals as they reach their capacity limits of various resources which increasingly leads to traffic and port congestion. Good planning and management of container terminal operations reduces waiting time for liner ships. Reducing the waiting time improves the terminal’s productivity and decreases the port difficulties. Two important keys to reducing waiting time with berth allocation are determining suitable access channel depths and increasing the number of berths which in this paper are studied and analyzed as practical solutions. Simulation based analysis is the only way to understand how various resources interact with each other and how they are affected in the berthing time of ships. We used the Enterprise Dynamics software to produce simulation models due to the complexity and nature of the problems. We further present case study for berth allocation simulation of the biggest container terminal in Iran and the optimum access channel depth and the number of berths are obtained from simulation results. The results show a significant reduction in the waiting time for container ships and can be useful for major functions in operations and development of container ship terminals.

Keywords

container ships / waiting time / access channel depth / quay length / simulation model / enterprise dynamics / berth allocation

References

[1] Ali I, Abouelseoud Y, HamdyElwany M. Container terminal berth allocation and quay crane assignment using IP and simulated annealing. Proceedings of the 41st International Conference on Computers & Industrial Engineering, USA, Los Angeles, 2011, 31-37

[2] Banks J, Carson JS. Discrete event system simulation, 2010, 5th ed, Upper Saddle River, NJ: Pearson Education, Inc., 14-21

[3] Bierwirth C, Meisel F. A survey of berth allocation and quay crane scheduling problems in container terminals. European Journal of Operational Research, 2010, 202(3): 615-627

[4] Bruzzone AG, Giribone P, Revetria R. Operative requirements and advances forth new generation simulators in multimodal container terminals. Proceedings of the 31^st Conference on Winter Simulation, 1999, New York: ACM Press, 1243-1252

[5] Cakaj S. Modeling, simulation and optimization: focus on applications, 2010, Publisher: In Tech, India

[6] Dahal K, Galloway S, Hopkins I. Modeling, simulation and optimization of port system management. International Journal of Agile Systems and Management, 2007, 2(1): 92-108

[7] Demirbilek Z, Sargent F. Deep-draft coastal navigation entrance channel practice, 1999

[8] Economic Development Research Group Panama canal expansion study phase 1 Report: Developments in trade and national and global economies, 2012, Washington, DC: The United States Department of Transportation, Maritime Administration

[9] Halverson R. Simulation with enterprise dynamics. Midwestern State University, Wichita Falls, TX. Journal of Computing Sciences in Colleges Archive, 2009, 21(4): 246-252

[10] He L, Liu H, Lv H, Zhao J. Optimization study of berth allocation based on genetic algorithm. ICLEM 2012: Logistics for Sustained Economic Development-Technology and Management for Efficiency, 2012, 67-73

[11] Hartmann S. A general framework for scheduling equipment and manpower on container terminals. OR Spectrum, 2004, 26: 51-74

[12] Kim KH, Moon K. Berth scheduling by simulated annealing. Transportation Research Part B, 2002, 37: 541-560

[13] Legato P, Mazza R. Berth planning and resources optimization at a container terminal via discrete event simulation. University della Calabria, 2000, 537-547

[14] Meng N, Chen Y, He L. Dynamic decision-making for port berth allocation. Second International Conference of Intelligent Computation Technology and Automation, 2009, 4: 188-191

[15] Merkuryev Y, Tolujew J, Blümel E, Novitsky L, Ginters E, Viktorova E, Merkuryeva G, Pronins J. A modeling and simulation methodology for managing the Riga harbor container terminal. Simulation, 1998, 71(2): 84-95

[16] Nam KC, Kwak KS, Yu MS. Simulation study of container terminal performance. Journal of Waterway. Port, Coastal and Ocean Engineering, 2002, 128(3): 126-132

[17] Perros H. Computer Simulation Techniques-The Definitive Introduction, 2009, Raleigh: Computer Science Department, NC State University

[18] Saanen YA. Examining the potential for adapting simulation software to enable short-term tactical decision making for operational optimization, 2000

[19] Yun WY, Choi YS. Simulator for port container terminal using an object oriented approach, 2003