|Table of Contents|

 Meilong Le and Hang Yu.The RHSA Strategy for the Allocation of Outbound Containers Based on the Hybrid Genetic Algorithm[J].Journal of Marine Science and Application,2013,(3):344-350.[doi:10.1007/s11804-013-1200-3]
Click and Copy

The RHSA Strategy for the Allocation of Outbound Containers Based on the Hybrid Genetic Algorithm


The RHSA Strategy for the Allocation of Outbound Containers Based on the Hybrid Genetic Algorithm
Meilong Le and Hang Yu
Meilong Le and Hang Yu
Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China
random hybrid stacking algorithm genetic algorithm container yard operation container stowage plan handling cost utilization ratio
Secure storage yard is one of the optimal core goals of container transportation; thus, making the necessary storage arrangements has become the most crucial part of the container terminal management systems (CTMS). This paper investigates a random hybrid stacking algorithm (RHSA) for outbound containers that randomly enter the yard. In the first stage of RHSA, the distribution among blocks was analyzed with respect to the utilization ratio. In the second stage, the optimization of bay configuration was carried out by using the hybrid genetic algorithm. Moreover, an experiment was performed to test the RHSA. The results show that the explored algorithm is useful to increase the efficiency.


Bazzazi M, Safaei N, Javadian N (2009). A genetic algorithm to solve the storage space allocation problem in a container terminal. Computers & Industrial Engineering, 56(1), 44-52.
Chen Lu, Lu Zhiqiang (2012). The storage location assignment problem for outbound containers in a maritime terminal. Int. J. Production Economics, 135(1), 73-80.
Dekker R, Voogd P, van Asperen E (2006). Advanced methods for container stacking. OR Spectrum, 28(4), 563-586.
Gen M, Lin L (2005). Priority-based genetic algorithm for shortest path routing problem in OSPF. Genetic and Evolutionary Computation Conference, Washington, D.C., USA.
Hao Jumin, Ji Zhuoshang, Lin Yan (2000). Study of optimization of a BAY of stacking. Journal of Dalian University of Technology, 40(1), 102-105.
Hou CX (2011). Research on the space allocation of container terminal export carton yard. Master thesis, Dalian Maritime University, Dalian.
Kang J, Ryu KR, Kim KH (2006). Deriving stacking strategies for export containers with uncertain weight information. Journal of Intelligent Manufacturing, 17(4), 399-410.
Kim KH, Kim KY (2007). Optimal price schedules for storage of inbound containers. Transportation Research Part B, 41(8), 892-905.
Kim KH, Park KT (2003). A note on a dynamic space-allocation method for outbound containers. European Journal of Operational Research, 148(1), 92-101.
Rodriguez-Molins M, Salido MA, Barber F (2012). Intelligent planning for allocating containers in maritime terminals. Expert Systems with Applications, 39(1), 978-989.
Salido MA, Rodriguez-Molins M, Barber F (2011). Integrated intelligent techniques for remarshaling and berthing in maritime terminals at marine terminals. Advanced Engineering Informatics, 25(3), 435-451.
Saurí S, Martín E (2011). Space allocating strategies for improving import yard performance. Transportation Research Part E, 47(6), 1038-1057.
Wang B (2007). Dynamic and Stochastic storage model in a container yard. Systems Engineering-Theory & Practice, 4, 147-153.
Wang MC (2007). Research on dynamic slot allocation strategy optimization in container terminal yards. Master thesis, Wuhan University of Technology, Wuhan.
Yi Zhengjun, Jiang Jing, Hu Yong (2011). An optimization control algorithm for containers relocation based on PCNN model. Acta Auto Maticasinica, 37(2), 241-244.
Zhang C, Liu J, Wan YW, Murty KG, Linn RJ (2003). Storage space allocation in container terminals. Transportation Research Part B, 37(10), 883-903.


Supported by the Research Grants from Shanghai Municipal Natural Science Foundation (No. 10190502500), Shanghai Maritime University Start-up Funds, Shanghai Science & Technology Commission Projects (No. 09DZ2250400), and Shanghai Education Commission Project (No. J50604)
Last Update: 2013-08-27