• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.216-217
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• 2011

The problem of automated stacking cranes (ASC) dispatching in container terminals is addressed in this paper. We propose a heuristic-based ASC dispatching approach which adopts multi-criteria decision strategy. By aggregating different criteria the proposed strategy can consider multiple aspects of the dispatching situation and make robust decision in various situations. A multi-objective evolutionary algorithm (MOEA) is adopted to tune the weights associated to each criteria to minimize both the quay crane delay and external truck delay. The proposed approach is validated by comparison with different dispatching heuristics and simulation results obtained confirms its effectiveness.

• Journal of Navigation and Port Research
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• v.36 no.5
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• pp.387-394
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• 2012

In an automated container terminal, automated stacking cranes(ASCs) take charge of handling of containers in a block of the stacking yard. This paper proposes a multi-criteria strategy to solve the problem of job dispatching of twin ASCs which are identical to each another in size and specification. To consider terminal situation from different angles, the proposed method evaluates candidate jobs through various factors and it dispatches the best score job to a crane by doing a weighted sum of the evaluated values. In this paper, we derive the criteria for job dispatching strategy, and we propose a genetic algorithm to optimize weights for aggregating evaluated results. Experimental results are shown that it is suitable for real time terminal with lower computational cost and the strategy using various criteria improves the efficiency of the container terminal.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.346-349
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• 2003

For a traveling crane, various control methods such as neural network predictive control and TDOFPID(Two Degree of Freedom Proportional Integral Derivative) are studied. So in this paper, we proposed improved navigation method to reduce transfer time and sway with anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the NNPPID(Neural Network Predictive PID) controller to control the precise move and speedy navigation. The proposed predictive control system is composed of the neural network predictor, TDOFPID controller, and neural network self-tuner. We analyzed ASC(Automated Stacking Crane) system and showed some computer simulations to prove excellence of the proposed controller than other conventional controllers.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.255-256
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• 2007

In case of inappropriate stacking position of the container taking in container yard, the working time for the container would be delayed in taking out because of the occurrence of the re-handle and the increase of the crane moving time. We have to take into account a variety of elements like the crane interference, the container group and stacking height in order to determine the optimal stacking position and decide the weight reflecting the importance of these criteria. We propose the dynamic weight adjustment algorithm for the stacking policy criteria employing the online search in this research.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.109-118
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• 2005

The purpose of this paper is to analyze transport ability of AGV(Automated Guided Vehicle) and SHC(SHuttle Carrier). The main difference between two types of transport vehicles is that AGV depends on container crane or transfer crane to do loading/unloading container, but SHC is very independent to it. Therefore, the transport ability of SHC is expected to be higher than AGV. So, in this paper, we established simulation model to evaluate two types of transport vehicles and analyzed the results. Simulation model was established to automated container terminal with perpendicular yard layout, and applied closed loop operation of transport vehicle between apron and stacking yard. In the result, SHC showed very superior than AGV aspect of container crane productivity and vehicle fleets.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.57-63
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• 2005

The purpose of this paper is to analyze transport ability of AGV(Automated Guided Vehicle) and SHC(SHuttle Carrier). The main difference between two types of transport vehicles is that AGV depends on container crane or transfer crane to do loading/unloading container, but SHC is very independent to it. Therefore, the transport ability of SHC is expected to be higher than AGV, So, in this paper, we established simulation model to evaluate two types of transport vehicles and analyzed the results. Simulation model was established to automated container terminal with perpendicular yard layout, and applied closed loop operation of transport vehicle between apron and stacking yard. In the result, SHC showed very superior than AGV aspect of container crane productivity and vehicle fleets,

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.335-336
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• 2007

This paper propose a heuristic method that divides the block into some work regions to operate stacking cranes efficiently in a automated container terminal where the blocks with non-crossing stacking cranes(SC) are laid out in perpendicular to the quay. Typically, fund over between SCS and trucks occur at each side if the blocks, and each if the landside and seaside SCS is responsible for the jobs that occur at its own side. When a container to be fetched is located far from fund over point, the SC should move a long distance and the interference between the two cranes am occur, which decreases the productivity of the SCS. Therefore, our method divides the block into two exclusive and one shared regions and let the containers located far from their fund over points to be transferred to the shared region by the other side crane before they are carried out. Although simple this method am reduce the crane movement and the interference between the two cranes. Simulation experiment shows that our proposed method significantly improves the productivity if the container terminal than previous heuristic that does not divide work regions.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.47-65
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• 2006

These days, the number of automated container terminals is increasing to encourage the productivity of the container terminal inside and outside of the country. So far, there have been a lot of researches on the operating one type of equipments in a container terminal. However, there is still room for further improvement as none of equipment works itself but cooperate each other to finish a job, which means synchronization among the equipments is necessary. Among lots of equipments in a terminal, this paper concerns with the operation of ATCs (Automated Transfer Crane) and YTs (Yard Truck). The purpose of this paper is to find the efficient heuristic methods for operating ATCs and YTs that can set up a schedule in a real time. Moreover, using simulation this paper shows the efficient stacking strategy to decide the location of containers to be put and the proper selection range of YTs.

• IE interfaces
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• v.19 no.3
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• pp.214-224
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• 2006

The container handling times of automated transfer cranes(ATCs) significantly affect the productivity of container terminals. In this paper, evaluation models for the container handling times of ATCs are suggested for import container blocks with different transfer point configurations. Firstly, evaluation models for various motion times of stacking and retrieving operations of ATC are suggested for two basic alternatives of import container blocks. In addition, in considering the space allocation, evaluation methods for the container handling times of ATC are suggested. Finally, the container handling times for each case are compared with each other in order to analyze how the block shape and the transfer point locations affect the container handling times of ATC.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.31-46
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• 2008

A stacking yard of a container terminal is a space for temporarily storing the containers that are carried in or imported until they are carried out or exported. If the containers are stacked in an inappropriate way, the efficiency of operation at the time of loading decreases significantly due to the rehandlings. The remarshaling is the task of rearranging containers during the idle time of transfer crane for the effective loading operations. This paper proposes a method of planning for remarshaling in a yard block of an automated container terminal. Our method conducts a search in two stages. In the first stage, the target stacking configuration is determined in such a way that the throughput of loading is maximized. In the second stage, the crane schedule is determined so that the remarshaling task can be completed as fast as possible in moving the containers from the source configuration to the target configuration. Simulation experiments have been conducted to compare the efficiency of loading operations before and after remarshaling. The results show that our remarshaling plan is really effective in increasing the efficiency of loading operation.