A decomposition method to analyze the performance of frame bridge based automated container terminal

This paper studies a new automated container terminal (ACT) system which utilizes multi-storey frame bridges and rail-mounted trolleys to transport containers between the quay and the yard. Different from widely used AGV-ACT systems, the ACT system studied in this paper uses three types of handling machines, which collaborate to transport containers. This study decomposes the container flow in the new ACT system into three queuing sub-networks. Then an iterative method is developed to analyze the operational efficiency of the ACT system. We analyze its transport efficiency by comparing with the widely used AGV-based systems. This study tries to help port operators better understand the relative merits of this new design and decide whether it is applicable in their terminals.

[1]  Iris F. A. Vis,et al.  Survey of research in the design and control of automated guided vehicle systems , 2006, Eur. J. Oper. Res..

[2]  Kap Hwan Kim,et al.  Comparison and evaluation of various cycle-time models for yard cranes in container terminals , 2010 .

[3]  D Towsley,et al.  Symmetry property of the throughput in closed tandem queueing networks with finite buffers , 1991, Oper. Res. Lett..

[4]  Iris F. A. Vis,et al.  Transshipment of containers at a container terminal: An overview , 2003, Eur. J. Oper. Res..

[5]  Loo Hay Lee,et al.  An Integrated Model for Berth Template and Yard Template Planning in Transshipment Hubs , 2011, Transp. Sci..

[6]  Hyung Rim Choi,et al.  Simulation Analysis on Effective Operation of Handling Equipments in Automated Container Terminal , 2006, Australian Conference on Artificial Intelligence.

[7]  Lu Zhen Yard template planning in transshipment hubs under uncertain berthing time and position , 2013, J. Oper. Res. Soc..

[8]  Margaret L. Brandeau,et al.  An Analytic Model for Design of a Multivehicle Automated Guided Vehicle System , 1993 .

[9]  Lu Zhen,et al.  A Comparative Study on Two Types of Automated Container Terminal Systems , 2012, IEEE Transactions on Automation Science and Engineering.

[10]  Youfang Huang,et al.  An investigation into knowledge-based yard crane scheduling for container terminals , 2011, Adv. Eng. Informatics.

[11]  Zuhua Jiang,et al.  Developing a dynamic rolling-horizon decision strategy for yard crane scheduling , 2011, Adv. Eng. Informatics.

[12]  Lu Zhen,et al.  A bi-objective model for robust berth allocation scheduling , 2012, Comput. Ind. Eng..

[13]  Stefan Voß,et al.  Container terminal operation and operations research — a classification and literature review , 2004 .

[14]  Loo Hay Lee,et al.  A decision model for berth allocation under uncertainty , 2011, Eur. J. Oper. Res..

[15]  Matthew E. H. Petering Effect of Block Width and Storage Yard Layout on Marine Container Terminal Performance , 2009 .

[16]  Petros A. Ioannou,et al.  Design, simulation, and evaluation of automated container terminals , 2002, IEEE Trans. Intell. Transp. Syst..

[17]  Gamini Dissanayake,et al.  A job grouping approach for planning container transfers at automated seaport container terminals , 2011, Adv. Eng. Informatics.

[18]  Kap Hwan Kim,et al.  An optimal layout of container yards , 2008, OR Spectr..

[19]  Michael G.H. Bell,et al.  An uncertainty-aware AGV assignment algorithm for automated container terminals , 2010 .

[20]  Kap Hwan Kim,et al.  Optimizing the Block Size in Container Yards , 2010 .

[21]  Yavuz A. Bozer,et al.  Tandem Configurations for Automated Guided Vehicle Systems and the Analysis of Single Vehicle Loops , 1991 .

[22]  Katta G. Murty,et al.  A decision support system for operations in a container terminal , 2005, Decis. Support Syst..

[23]  Satoshi Hoshino,et al.  Hybrid Design Methodology and Cost-Effectiveness Evaluation of AGV Transportation Systems , 2007, IEEE Transactions on Automation Science and Engineering.