Abstract
The optimal usage of berths plays a key role in raising the efficiency of container terminals. The berth allocation problem in a container terminal is defined as the feasible allocation of berths to incoming ships such that the total time that elapses between the arrival of the ships to their exit from their berths is minimized. In the transportation literature, the latter problem is usually formulated as a mixed integer programming model. Optimization methods, like the branch and bound algorithm, are efficient ways to solve this model but become absolutely unusable when the size of the problem increases. An advanced search method such as GA may be suited to such a situation. In this paper, a genetic-based algorithm is proposed for the problem. Computational results for two test problems (a small and a large-sized problem) are also presented. The results from the small test are also compared with the results obtained from the branch and bound algorithm.
Similar content being viewed by others
References
Zhang C, Liu J, Wan Y-W, Murty KG, Linn RJ (2003) Storage space allocation in container terminals. Transp Res Part B 37:883–903
Imai A, Nishimura E, Papadimitriou S (2001) The dynamic berth allocation problem for a container port. Transp Res Part B 35:401–417
Nishimura E, Imai A, Papadimitriou S (2001) Berth allocation planning in the public berth system by genetic algorithms. Eur J Oper Res 131:282–292
Imai A, Nishimura E, Papadimitriou S (2003) Berth allocation with service priority. Transp Res Part B 37:437–457
Cordeau J-F, Laporte G, Legato P, Moccia L (2005) Models and tabu search heuristics for the berth-allocation problem. Transp Sci 39(4):526–538
Han M, Li P, Sun J (2006) The algorithm for berth scheduling problem by the hybrid optimization strategy GASA. In: Proceedings of the Ninth International Conference on Control, Automation, Robotics and Vision (ICARCV’06). IEEE Computer Society, Washington, DC, pp 1–4
Zhou P, Kang H, Lin L (2006) A dynamic berth allocation model based on stochastic consideration. In: Proceedings of the Sixth World Congress on Intelligent Control and Automation (WCICA 2006), vol 2. IEEE Computer Society, Washington, DC, pp 7297–7301
Lim A (1998) The berth planning problem. Oper Res Lett 22:105–110
Guan Y, Xiao W-Q, Cheung RK, Li C-L (2002) A multiprocessor task scheduling model for berth allocation: heuristic and worst-case analysis. Oper Res Lett 30:343–350
Park KT, Kim KH (2002) Berth scheduling for container terminals by using a sub-gradient optimization technique. J Oper Res Soc 53:1054–1062
Kim KH, Moon KC (2003) Berth scheduling by simulated annealing. Transp Res Part B 37:541–560
Imai A, Sun X, Nishimura E, Papadimitriou S (2005) Berth allocation in a container port: using a continuous location space approach. Transp Res Part B 39:199–221
Bierwirth C, Meisel F (2010) A survey of berth allocation and quay crane scheduling problems in container terminals. Eur J Oper Res 202:615–627
The MathWorks Inc. (2004) MATLAB, version 7.0 for Windows. The MathWorks Inc., Natick, MA
LINDO Systems Inc. (2003) LINGO, version 8.0 for Windows. LINDO Systems Inc., Chicago, IL
Ganji SS, Ganji DD, Karimpour S, Babazadeh H (2009) Applications of He’s homotopy perturbation method to obtain second-order approximations of the coupled two-degree-of-freedom systems. Int J Nonlinear Sci Numer Simul 10:303–312
Seyed Alizadeh SR, Domairry GG, Karimpour S (2008) An approximation of the analytical solution of the linear and nonlinear integro-differential equations by homotopy perturbation method. Acta Appl Math 104:355–366
Seyedalizadeh Ganji SR, Javanshir H, Vaseghi F (2009) Nonlinear mathematical programming for optimal management of container terminals. Int J Mod Phys B 23:5333–5342
Seyedalizadeh Ganji SR, Javanshir H (2010) Solving YCSNIP using an approximate solution. Int J Mod Phys B (in press)
Takano K, Arai M (2009) A genetic algorithm for the hub-and-spoke problem applied to containerized cargo transport. J Mar Sci Technol 14:256–274. doi:10.1007/s00773-008-0035-0
Kitamura M, Nobukawa H, Yang F (2000) Application of a genetic algorithm to the optimal structural design of a ship’s engine room taking dynamic constraints into consideration. J Mar Sci Technol 5:131–146. doi:10.1007/s007730070010
Chen J-H, Shih Y-S (2007) Basic design of a series propeller with vibration consideration by genetic algorithm. J Mar Sci Technol 12:119–129. doi:10.1007/s00773-007-0249-6
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Seyedalizadeh Ganji, S.R., Babazadeh, A. & Arabshahi, N. Analysis of the continuous berth allocation problem in container ports using a genetic algorithm. J Mar Sci Technol 15, 408–416 (2010). https://doi.org/10.1007/s00773-010-0095-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00773-010-0095-9