• Journal of Korean Port Research
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• v.4 no.1
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• pp.3-20
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• 1990

The Port of Pusan, the largest port in Korea, handled 23% of total sea borne cargo movement, 14% of imported cargo, 58% of exported cargo and 95% of container cargo in 1989. Also the port of Pusan has been played a key role in handing container cargo throughout the last 10 years. The paper is aimed to survey the effect of sea borne cargo movement to urban transportation, that is, to find traffic volume arising by general/bulk cargoes through the port and to estimate vehicle rated of container tractor tailer on the roads between terminal including conventional piers and ODCY, and finally the following results are obtained. (1) AADV of truck to transport general/bulk cargoes are 6,322 units in 1989,and routes penetrate into the center of city and pass through the most of urban arterials. (2) In the container transport, if HVEF is adopted to 3 of tractor trailer, AVR in each transport freeway 13.7%. (3) IF HVEF is adopted to 6 of tractor trailer. AVR are as follows: BooDoo-Ro 44.1%, WooAm-Ro 39.3%, SooYoung-Ro 17.8%, Urban freeway 20.3%. Based upon these results, the following suggestions were drawn : o ODCY scattered around the city should be unified in a few groups to raise port productivity. o Rail service for inland container transportation should be escalated to relieve urban traffic congestion. o Coastal feeder service between terminal and hinterland should be studied to restrict the penetration of container tractor trailer into the central parts in the urban areas. o Exclusive freeway system for effective container transportation should be implemented to reduce urban traffic delay.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.131-132
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• 2009

The container terminal can be divided into berth-side, yard area and gate. Until now, many studies related to the improvement of the terminal operation efficiency have been focused on berth and yard productivity. With regard to gate operation, existing studies were examined from hardware perspectives such as non-stop system using RFID(Radio Frequency Identification) or OCR(Optical Character Reader). Relatively little research has been curried out on the improvement of the gate in/out process. In this regard, this paper proposes the method to improve the terminal operation efficiency.

• 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).

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.331-336
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• 2004

In order to strengthen the competitiveness of port against calling for the huge vessel and reducing the shipping service time, the productivity of container terminal must be improved. This productivity variously results according to the kinds of productivity evaluation model, input elements like yard, equipment, employee, facility, etc,. But, it is discussed that the productivity is measured by partial productivity evaluation model or general input elements. Therefore, we measured for the productivity of the container terminal using the Developed the data Envelopment Analysis (DEA), which is developed in order to evaluate the relative efficiency of decision making units - it's difficult to clear cause and effect between input and output. We measured the whole productivity of container terminal in Busan according to decision of the correct input elements. And we investigated the change of the productivity measurement result according to input elements, presents more accurate productivity evaluation model in container terminal.

• Journal of Navigation and Port Research
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• v.38 no.4
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• pp.399-407
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• 2014

Due to the increase of container terminals, as the volume of terminals become distributed, the competition of preserving existing volume and inviting new volume are becoming fierce, and various ways for processing terminal volume and inviting volume are being sought. Container terminal efforts to maximize efficiency in order to improve the volume handling capability and productivity by both expansion of the latest equipment and development of the latest terminal system. There are a variety of factors that influence the improvement of productivity at container terminals. Among them, in the case of yard transfer equipment, if it were to convert from the method of a Yard Tractor(YT) being fixed allocated to a certain Gantry Cranes(GC) to a Pooling System that processes in a method that properly distributes and allocates a Yard Tractor(YT) to multiple Gantry Cranes(GC), the terminal productivity and the fusibility of YT may be increased. The KPI which is an indicator for the productivity at container terminals is GC productivity and since GC productivity cannot exceed the speed of physical GC operations, a Pooling System is applied to increase productivity which its meaning and effect is massive. Here in the Report, we produce the Pooling Algorithm system to improve the efficiency of the transported equipments in container terminal which is actually applying for this method and have compared Non pooling system with Pooling system in the fields. By introducing a transfer equipment pooling system and enhancing the productivity compared to other terminals, it may become an essential factor for increasing the continuous service quality and profitability in terms of terminal business.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.309-313
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• 1998

Delay time of receiving and delivery is one of important factors that should be considered in the evaluation of the customer service level of a container terminal. In this study, dispatching rules are tested with the objective of minimizing the service delay time for arriving outside trucks. A dynamic programming model is suggested for a static dispatching problem in which all the truck arrivals are known in advance. In order to overcome the excessive computational time of the dynamic programming technique, several heuristic rules are suggested that can be applied in practices. A simulation study is carried out to test the performances of the heuristic rules.

• Journal of Korea Port Economic Association
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• v.28 no.4
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• pp.275-298
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• 2012

Terminal operators have provided special services such as loading, discharging, stowage of cargo to the owner, and carriers of the sea, which contribute the domestic and international logistics. For smooth flow of logistics, container terminal should reserve spaces for inbound and outbound logistics. However, if it is unable to provide the spaces, which can be caused by labour strikes or terminal lockouts and so on, national logistic system and financial management of terminal operators can be seriously affected. In order to minimize these kinds of problems, terminal operators impose high rate of charges ("overstorage charge") to the accumulated cargoes and/or containers, which are stipulated in terminal service agreement. Nevertheless, if there is no terminal service agreement with an owner of cargo and/or container, any kind of charge can cause legal problems (conflict ??) between the cargo and terminal operator. In this regard, I would like to study on the definition of overstorage charge and the legal issue of it based on the Busan district court's judgment. In particular, I will propose a special right of commercial lien and public auction for terminal operators to settle accumulated cargoes in container terminal.

• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.69-82
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• 2018

The number of ships serviced at the container terminals in Busan is increasing by 2.9% per year. In spite of the increase in calling ships, there are no official records of waiting rate by the port authority. This study attempts to compare the theoretical ship waiting ratio and actual ship waiting ratio. The actual ship waiting ratio of container terminals is acquired from the 2014 to 2016 data of PORT-MIS and Terminal Operating System (TOS). Furthermore, methods and procedures to measure the actual ship's waiting rate of container terminal are proposed for ongoing measurement. In drawing the theoretical ship waiting ratio, the queuing theory is applied after deploying the ship arrival probability distribution and ship service probability distribution by the Chi Square method. As a result, the total number of ships waiting in a terminal for three years was 587, the average monthly service time and the average waiting time was 13.8 hours and 17.1 hours, respectively, and the monthly number of waiting ships was 16.3. Meanwhile, according to the queuing theory with multi servers, the ship waiting ratio is 31.1% on a 70% berth occupancy ratio. The reason behind the huge gap is the congested sailing in the peak days of the week, such as Sunday, Tuesday, and Wednesday. In addition, the number of waiting ships recorded on Sundays was twice as much as the average number of waiting ships.

• Journal of Navigation and Port Research
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• v.34 no.3
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• pp.235-242
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• 2010

In recent years, the busan port is now facing a serious crisis. Exterally, though worldwide economics depression is a serious factor, cuttthroat competition between north port and new port since new port open lead to decrease terminal profitability and busan port image. The essential cause is crowed with terminal operators. therefore, This paper empirically analyze the container terminal integration factor solving busan port problem affecting the competitiveness performance. According to research results, integration between operators will be to acomplish global terminal, and so, contribute to increase service power, port productivity, cargoes and to be hub-port at the north-east asia. These results show political suggestions for importance of repid integration to improve busan port's competitiveness.

• Journal of Korea Port Economic Association
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• v.32 no.2
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• pp.137-156
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• 2016

This study analyzes the optimal service levels of exclusive container terminals in terms of the optimal berth occupancy rate and the ships' waiting ratios, based on the number of berths. We develop a simulation model using berth throughput data from pier P, Busan New Port, a representative port in Korea, and apply the simulation results to different numbers of berths. In addition to the above results, we analyze the financial data and costs of delayed ships and delayed cargoes for the past three years from the viewpoints of the terminal operation company (TOC), shipping companies, and shippers to identify the optimal service level for berth occupancy rates that generate the highest net profit. The results show that the optimal levels in the container terminal are a 63.4% berth occupancy rate and 10.6% ship waiting ratio in berth 4,66.0% and 9.6% in berth 5, and 69.0% and 8.5% in berth 6. However, the results of the 2013 study by the Ministry of Maritime Affairs and Fisheries showed significantly different optimal service levels: a 57.1% berth occupancy rate and 7.4% ship waiting ratio in berth 4; 63.4% and 6.6% in berth 5; and 66.6% and 5.6% in berth 6. This suggests that optimal service level could change depending on when the analysis is performed. In other words, factors affecting the optimal service levels include exchange rates, revenue, cost per TEU, inventory cost per TEU, and the oil price. Thus, optimal service levels can never be fixed. Therefore, the optimal service levels for container terminals need to be able to change relatively quickly, depending on factors such as fluctuations in the economy, the oil price, and exchange rates.