• 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.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.219-226
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• 2020

The container terminal operators established a re-marshalling plan to reduce the loading operation time and the release operation time. Re-marshalling is to rearrange the containers in the container yard to the advantageous position to shorten the working time using the spare time of the automated yard crane. This study assumed the automated container terminal with a perpendicular layout and deals with the inter-bay re-marshalling planning problem in a yard block. The inter-bay re-marshalling plan determines the container to be moved, the location to be relocated, and the sequence of relocation operations. This study presents a mixed integer programming model that simultaneously determines the storage location and the operation sequence while satisfying the spatial availability during the re-marshalling. Numerical experiments are conducted to understand re-marshalling operation using a beam search method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.443-449
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• 2004

In this paper, we established a simulation model for transport vehicle that carries the container transportation between apron and yard block on automated container terminal with a perpendicular yard layout. Usually, the efficiency of container terminal is evaluated by productivity of container cranes at apron, and though there are enough support of transport vehicles and yard cranes, can improve the productivity of container cranes. Especially, transport vehicle is very important factor in productivity of container cranes and has variable work productivity according to loading and unloading situation of container cranes. Therefore, a method that can estimate work productivity of transport vehicle efficiently is required. We analyzed work productivity of transport vehicle using simulation model that has state transition of transport vehicle. We performed various simulation experiment and analyzed work productivity of transport vehicle and calculated the required number of transport vehicle by container crane additionally.

• Journal of Navigation and Port Research
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• v.28 no.10 s.96
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• pp.891-897
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• 2004

This paper provided a simulation model for transport vehicles that carry container from the ship to yard block and vice versa at automated container terminal with a perpendicular yard layout. Usually, the efficiency of container terminal is evaluated by the productivity of container cranes at apron, and the stevedoring system for transport vehicles and yard cranes should be supported enough to improve productivity of container cranes. Especially, transport vehicle is very important factor in the productivity of container cranes and the performance of transport vehicles are changed according to the number and traveling type of vehicles. For these reason, a method that can estimate productivity of transport vehicle is required Finally, we developed the simulation model to analyze the productivity of transport vehicle and presented the productivity of container cranes for a varying operation of transport vehicles.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.85-94
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• 2008

Automated Guided Vehicles (AGVs) are important equipment in automated container terminals. To utilize AGVs for transporting containers from a position to another, the deadlock is a serious problem that must be solved before they are deployed to real operations. This study assumes that traveling area for AGVs are divided into a large number of grid-blocks and, as a method of traffic control, grid-blocks are reserved in advance during the travel of AGVs. The purposes of the reservation are to make the room between AGVs and to prevent deadlocks. Because the size of an AGV is much larger than the size of a grid-block on guide paths, this study assumes an AGV may occupy more than one grid-block at the same time. This study suggests a method for constructing a table of reservation schedules by using a simulation. A sensitivity analysis was conducted to evaluate the performance of the reservation method in this study.

• 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.

• 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 Navigation and Port Research
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• v.30 no.6 s.112
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• pp.457-464
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• 2006

Remarshalling operation is one of the operations considered important in an automated container terminal to perform quickly loading operations and delivery operations. It arranges the containers scattered at a verticla yard block in order to reduce the transfer time and the rehandling time of ATC(Automated Transfer Crane)s. This paper deals with the remarshalling planning problem minimizing the weighted operation time. This problem can be decomposed into 2 subproblems, storage space assignment problem and operation sequencing problem Storage space assignment problem decides to where containers are transported in terms of transportation time cost.. With results of a previous subproblem, operation sequence problem determines the ATC operation sequence, which minimizes the dead-heading of ATC This study formulates each subproblem with mixed integer program and dynamic program. To illustrate the proposed model, we propose an instance to explain the process of remarshalling planning.

• 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.

• Journal of Navigation and Port Research
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• v.36 no.8
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• pp.665-671
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• 2012

A remarshalling is studied as an important operational strategy in an automated container terminal to enhance the productivity of container handling. This means the rearrangements of the containers scattered at a vertical yard block. The dispatching problem for remarshalling is selecting the remarshalling operation considering the available operation time and deciding the operation sequencing to maximize the effectiveness of remarshalling. This study develops the optimal mathematical model for yard crane dispatching problem with mixed integer program and explains dispatching problem using an example. However it is difficult to apply this model to a field problem because of its computational time. Therefore, we compare the representative 5 dispatching rules for real world adaption. In a numerical experiment, maximum weight ratio(MR) rule shows an overall outstanding performance.