• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.149-154
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• 2017

Recently, container terminal operators have made efforts to develop an efficient remarshalling plan in response to the increase in automation of equipment handling and transport of containers in the terminals. Usually, containers are handled by multiple AYCs(automated yard cranes) in-yard in an automated container terminal, and terminal operators establish a remarshalling plan using slack time to increase the efficiency of ship operation. This study develops the optimal mathematical model through mixed integer programming as a solution to the problem of dispatching multiple AYCs. Considering the difficulty of direct application to the field due to computation time, we analyze the five prototypical dispatching rules for real world adaptation. A numerical experiment found that the maximum weight ratio (MR) rule and the maximum weight (MW) rule are the ideal dispatching solutions to the multiple AYCs dispatching problem.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.203-208
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• 2004

The objective of this study is to analyze the efficiency of marshalling work using ATC(automated transfer crane) for ACT(automated container terminal). It is important fact to assignment of containers, because the character of ACT which block layout is vertical for berth and there are four other works which are inbound, oubound, loading and unloading in one block. And then there is need which assignment of containers with remarshaling work using ATCs in one block. Therefore, we analyze the efficiency of remarshaling work using simulation and suggest the assignment methodology of containers in yard

• 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.

• Journal of Navigation and Port Research
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• v.31 no.8
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• pp.705-710
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• 2007

The productivity of automated container terminals is significantly affected by not only the speed related performances of automated transfer cranes(ATCs) but also the sizes of container blocks. In this paper, it is discussed how to determine the size of import container blocks considering both the container handling times of an ATC and their storage space. Firstly, evaluation models are suggested for the container handling times of an ATC in a typical import container blocks. Secondly, three mathematical formulations are suggested to determine the size of import container blocks. Numerical experiments for the suggested models to determine the size of import container block are provided.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.255-261
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• 2005

The purpose of this paper is to analyze transport ability of Automated Guided Vehicle(AGV) and Double Stack Vehicle(DSV) at Automated Container Terminal(ACT). Usually, the main difference of AGV and DSV is capacity of container that they can transport between apron and yard block at once. AGV can carry out two 20 feet or one 40 feet maritime containers, but DSV can carry out four 20 feet or two 40 feet maritime containers. Therefore, DSV may improve more efficiency of stevedoring system of container terminal. In this paper, a simulation model using a graphics simulation system is developed to compare the proposed DSV with the current AGV at automated container terminal. The paper includes examples, performance tests and a discussion of simulation results.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.119-126
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• 2017

As container vessels get larger, container terminals are also likely to grow. The problem that arises is that the growing volume should be handled in the same amount of time as before. Container terminals are introducing an automation system in order to overcome the limitations of existing manual methods and to continuously reduce operating expenses. Because, Manual handling of carrying containers gate in and out of terminals causes inaccurate data, which results in confusion. An alternative is for containers to be labeled with barcodes that can be scanned into a system with a scanner, but this takes quite a long time and is inconvenient. A RFID system, also known as a gate automation system, can solve these problems by reducing the time of gate management with a technology that detects number identification plates, helping operators more efficiently perform gate management work. Having said that, with this system, when container damage is detected, gate operators make and keep documents manually. These documents, which are insufficient evidence in proving container damage, result in customer claims. In addition, it is difficult for gate operators and other workers to manage containers, exposing them to danger and accidents. This study suggests that if an automation system is introduced at gates, containers can be managed by a video storage system in order to better document damage The video system maintains information on container damage, allowing operators the ability to search for videos they need upon customer request, also allowing them to be better prepared for customer claims. In addition, this system reduces necessary personnel and risk of accidents near gates by integrating a wide range of work.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.357-364
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• 2007

장치장 재정돈이란 장치장 크레인의 유휴시간을 활용하여 최대의 효율로 적하작업을 할 수 있도록 장치장의 컨테이너들을 미리 재배치하는 작업을 말한다. 본 논문에서는 수직 배치 자동화 컨테이너 터미널의 장치장을 대상으로 블록 내 재정돈 작업 계획을 수립하는 알고리즘을 제안한다. 제안된 알고리즘은 장치장 재정돈 작업 계획을 목표 장치형태 결정 및 크레인 작업 계획의 2단계로 나누어 수립한다. 시뮬레이션 시스템을 이용하여 재정돈을 수행하기 전과 후의 장치장에 대해 적하 작업 효율을 비교한 결과 재정돈 후 안벽 크레인의 대기 시간이 감소하고, 장치장의 재취급 작업 수가 줄어드는 등 적하 작업 효율이 향상되는 것을 확인하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.253-254
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• 2007

오늘날 자동화 컨테이너 터미널은 대부분 AGV(Automated Guided Vehicle) 기반의 무인이송시스템을 운영하고 있다. AGV는 컨테이너의 상하차 작업 시 타장비의 도움을 필요로 한다. 이로 인하여 장비 간 대기시간이 발생하며, 이는 생산성을 떨어뜨리는 요인이 된다. 이와 같은 문제점을 해결한 무인이송장비로 ALV(Automated Lifting Vehicle)가 있다. ALV는 자가하역기능이 있어 타장비의 도움 없이 상하차 작업이 가능하다. 본 연구에서는 시뮬레이션을 통하여 각 이송시스템의 생산성을 비교하였다. 시뮬레이션은 이송시스템의 배차 방식과 안벽장비의 종류를 다양하게 설정하고, 무인이송장비의 가감속 운동 및 충돌을 고려하였다. 시뮬레이션 결과 소수의 경우를 제외하고는 ALV 기반의 이송시스템이 AGV 기반의 이송시스템보다 높은 생산성을 보여주었다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.179-180
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• 2009

자동화 컨테이너 터미널의 생산성을 향상시키기 위해서는 안벽크레인의 작업 지연 시간을 최소화하는 것이 중요하다. 안벽크레인의 작업 지연 시간은 이송 차량들이 효율적으로 주행하여 제 시간에 필요한 위치에 컨테이너를 운반함으로써 단축이 가능하다. 이송차량의 주행 경로는 사전에 결정된 레이아웃에서 최단 거리, 최단 시간 경로 등의 라우팅 방법을 통해 결정된다. 주행 경로 레이아웃은 안벽크레인의 작업이 진행됨에 따라 안벽 크레인의 위치, 작업 물량 및 병목지점이 변화하므로 동적으로 조정한 필요가 있다. 본 논문에서는 안벽 크레인의 위치 변화에 따라 주행 경로 레이아웃을 동적으로 최적화하는 방안을 제안한다. 제안방안의 효율성은 시뮬레이션 실험을 통해 검증하였다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.591-595
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• 2010

In this paper, a method that dynamically adapts the traffic flow of automated guided vehicles (AGVs) used in automated container terminals to the changing operational condition is presented. In a container terminal, the AGVs are vulnerable to traffic congestion because a large number of AGVs operate in a limited area. In addition, dynamically changing operational condition requires the traffic flow of AGVs to be continuously adjusted to keep up with the change. The proposed method utilizes a genetic algorithm to optimize the traffic flow. Exploiting the dynamic nature of the problem an approach that reuses the results of the previous search is tried to speed up the convergence of the genetic algorithm. The results of simulation experiments show the efficiency of the proposed method.