• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.61-62
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• 2023

There have been cases where the number of port workers has temporarily decreased due to COVID-19. To prevent the spread of COVID-19, a number of workers were quarantined, resulting in bottlenecks and waiting throughout the port operation process, increasing the congestion of terminals. As a result, problems such as a decrease in terminal operation efficiency occurred. However, it is understood that congestion centered on unloading equipment inside the terminal is not clearly calculated. Terminal congestion is thought to be a key factor directly related to the operational efficiency of the terminal. The congestion calculation method generally used in various fields measures congestion based on image-based data. Due to the nature of the loading and unloading equipment that moves according to the quantitative loading plan, it is unreasonable to apply the existing congestion calculation method. Therefore, this study presented a method of calculating terminal congestion using equipment waiting time and turnaround time, and verified the statistical significance of the congestion calculated using data from Terminal A of Busan Port.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.344-350
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• 2022

Due to the increase in container cargo volume, the congestion of container terminals is increasing and the waiting time of gate in-out trucks has significantly lengthened at container yards and gates, resulting in severe inefficiency in gate in-out truck operations as well as port operations. To resolve this problem, the Busan Port Authority and terminal operator provide services such VBS, terminal congestion information, and expected operation processing time information. However, the visible effect remains insufficient, as it may differ from actual waiting time.. Thus, as basic data to resolve this problem, this study presents deep learning based average gate in-out truck waiting time prediction models, using container gate in-out information at Busan New Port. As a result of verifying the predictive rate through comparison with the actual average waiting time, it was confirmed that the proposed predictive models showed high predictive rate.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.57-58
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• 2018

As interest in the Internet of Things increases, technologies are being studied to handle information exchanged between things using the Internet of Things. Specially, as container terminals are automated, the use of the Internet of Things in the terminals increases and varies. However, the use of the Internet of Things to enhance the efficiency of the container terminal operation is insufficient. Currently, the container terminal shows that the arrival pattern of the external truck is concentrated at a particular time. This resuls in gate congestion and affects the waiting times of the truck. The damage is caused by environmental pollution problems and social problems in neighboring port areas. Therefore, in this thesis, we will analyze the causes of the external truck's waiting time problems affecting the gate congestion at container terminals and study methods to mitigate congestion under Internet of Things environment.

• Journal of Navigation and Port Research
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• v.45 no.3
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• pp.148-154
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• 2021

With advancements of quay side handling equipment and technologies, congestion in terminal operation has moved to the storage yard side from the quay side. The importance of storage yard management has increased in overall terminal operation. Thus, many studies have been conducted to optimize the storage yard management of container terminals. However, there is no academic work to estimate the change of storage yard occupancy ratio by itself in the future. This paper examines the probability of storage yard occupancy ratio in the container terminal of Busan New port using the Markov chain analysis which explains probability change with passing time. The result shows that it is most likely to have the probability of maintaining a high level of storage yard occupancy ratio in the container terminal of Busan New Port.

• Journal of Korean Port Research
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• v.5 no.2
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• pp.19-37
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• 1991

This work aims to : establish a model of the container physical distribution system of Pusan port comprising 4 sub-systems of a navigational system, on-dock cargo handling/transfer/storage system, off-dock CY system and an in-land transport system : examine the system regarding the cargo handling capability of the port and analyse the cost of the physical distribution system. The overall findings are as follows : Firstly in the navigational system, average tonnage of the ships visiting the Busan container terminal was 33,055 GRT in 1990. The distribution of the arrival intervals of the ships' arriving at BCTOC was exponential distribution of $Y=e^{-x/5.52}$ with 95% confidence, whereas that of the ships service time was Erlangian distribution(K=4) with 95% confidence, Ships' arrival and service pattern at the terminal, therefore, was Poisson Input Erlangian Service, and ships' average waiting times was 28.55 hours In this case 8berths were required for the arriving ships to wait less than one hour. Secondly an annual container through put that can be handled by the 9cranes at the terminal was found to be 683,000 TEU in case ships waiting time is one hour and 806,000 TEU in case ships waiting is 2 hours in-port transfer capability was 913,000 TEU when berth occupancy rate(9) was 0.5. This means that there was heavy congestion in the port when considering the fact that a total amount of 1,300,000 TEU was handled in the terminal in 1990. Thirdly when the cost of port congestion was not considered optimum cargo volume to be handled by a ship at a time was 235.7 VAN. When the ships' waiting time was set at 1 hour, optimum annual cargo handling capacity at the terminal was calculated to be 386,070 VAN(609,990 TEU), whereas when the ships' waiting time was set at 2 hours, it was calculated to be 467,738 VAN(739,027 TEU). Fourthly, when the cost of port congestion was considered optimum cargo volume to be handled by a ship at a time was 314.5 VAN. When the ships' waiting time was set at I hour optimum annual cargo handling capacity at the terminal was calculated to be 388.416(613.697 TEU), whereas when the ships' waiting time was set 2 hours, it was calculated to be 462,381 VAN(730,562 TEU).

• Journal of Korean Port Research
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• v.9 no.2
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• pp.39-49
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• 1995

Recently, the traffic volume has been greatly increased partly because of high growth rate of domestic and world economy, and partly because of increased transhipment demand resulting from the destruction of Kobe port by earthqwake early this year. So, container facilities in Pusan Port are under serious congestion. The congestion costs in connection with container traffic in Pusan Port is estimated to be 29.3 billion won in 1994. In 1995 the situation is still worsening. PECT has continued to grow annually by 35% in cargo handling exceeding more than 31% of the total container volumes handled in Korea. The BOR of container berths in PECT in 1994 is 75% reflecting extreme congestion in container traffic. The reason for such serious congestion in PECT is the shortage of container handling facilities in comparison with ever-increasing cargo traffic. In order to solve the provisional problem, the shortage of handling capacity, a model developed to optimize the operation of PECT is described and demonstrated. The model minimizes total port costs, including the costs of dock labour, facilities and equipment, ship, containers, and cargo. The object of this study is, through the model results, mainly to determine the optimal combination of berths and cranes under various circumstances and to show that total costs per ship or unit of cargo served can be reduced by increasing the number of cranes per berth and berth utilization above present levels. Eventually, the results obtained with this model in PECT suggest that increase to 3 in the number of cranes per existing berth could reduce the need for major investments in berths and even reduce operating costs.

• The Journal of Information Systems
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• v.33 no.2
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• pp.125-142
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• 2024

Purpose The purpose of this study is to identify and analyze the key factors influencing congestion in the in-out transportation at port container terminals, and to design of a predictive model for in-out congestion based on these analysis. This study focused on architecting a deep learning-based predictive model. Design/methodology/approach This study was conducted through the following methodology. First, hypotheses were established and data were analyzed to examine the impact of vessel schedules and external truck schedules on in-out transportation. Next, explored time series forecasting models to a design the architecture for deep learning-based predictive model. Findings According to the empirical analysis results, this study confirmed that vessel schedules significantly affect in-out transportation. Specifically, the volume of transportation increases as the vessel arrival/departure time and the cargo cutoff time approach. Additionally, significant congestion patterns in transportation volume depending on the day of the week and the time of day were observed.

• Journal of the Korean Institute of Navigation
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• v.11 no.1
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• pp.39-65
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• 1987

Since the middle of 1950's, containerization has been rapidly spread over the world in virtue of great merits providing to interensts, and the fundamental changes in port management and prot operations are resulted. As the container terminal is a complex system which is consisted of various subsystems, the treatment for improving the productivity is required in a comprehensive fashion, both in each of its parts and as an integrated system. This paper aims to make an intensive analysis of the Busan Container Terminal system, especially focusing on its subsystems such as ship operation system, storage system and transfer system. First of all, the intrinsic capacity of various subsystems is calculated and it is checked whether the current operation is being performed effectively through the formal analysis. Secondly, the suggestion is presented to improve the operation by considering the throughput that the port of Busan will have to accept in the near future. The results are as follows; 1) As the inefficiency is due to the imbalance between various subsystems at Busan terminal, transfer equipment level must be up to 31% for straddle carrier and 67% transfer crane above all. 2) The yard capacity must be increased by reducing the free dwell time of containers in order to accept the traffic volume smoothly in the near future. 3) The better way to reduce the port congestion is to change berthing rule from the FIFP to the Pre-allocated system by considering the ship arrival pattern.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.477-487
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• 2020

The inefficient operation of Busan New Port is due to container-terminal operators being dispersed in small groups, rather than being integrated. This dispersion increased following the reorganization of global shipping alliances in 2016 and causes unnecessary Inter-terminal Transportation(ITT) and ship delays. Studies of integrated operations for larger container terminals show that integration is not going well, however, due to the pre-emptive task that follows the integrated operation. Therefore, in this study, we divided the integrated operation into stages based on a simulated model of the container terminals in Busan New Port. The simulation took into account future increases in the ship's enlargement and terminal congestion, and the operational effects of each type of integrated operation were analyzed and evaluated.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.314-324
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• 2021

Competition between ports around the world is intensifying to attract transshipment cargo. However, recently, there have been concerns about the departure of transshipment cargo volume at Busan Port, such as the lifting of the cabotage policy in China's shipping sector and the implementation of a safe fare system. In terms of operation, terminal congestion and vehicle waiting time are seriously occurring due to imbalance in the transshipment volume of each terminal and vehicles concentrated in a specific time period. In this paper, we propose a method of inter-terminal transportation (ITT) using buffer space to solve the problem caused by inefficient ITT systems and presented a mixed integer programming (MIP) for the problem. The effect of using the buffer space was analyzed for various work volumes and capacity fluctuation ranges by applying the terminal congestion pattern and ITT vehicle in/out pattern based on the Busan New Port data.