• Journal of Korean Port Research
• /
• v.3 no.1
• /
• pp.35-55
• /
• 1989

Today, about 99% of total import and export cargo in Korea is being transported through the port. The general trends of cargo handling show increases in capacity and speed, In order to cope with these trends, it is not only required to raise the efficiencies of port operation and function but also necessary to decide the optimal amount of the skilled labor force for cargo handling in the port. Cargo handling in the port is basically relied on the cargo handling facilities. Therefore, it is very important to reserve the amount of labor force for cargo handling system has been developed up to a certain level but the personnel management system which is the superior structure has not been followed well. In this study, therefore, we show a method to determine the required amount of labor force for cargo handling considering the amount of cargo and type of cargo handling work per each cargo, and the optimal amount labor force in cope with the fluctuation of the basic cargo handling labor force with respect to the time of in and out cargo flow in the viewpoint of minimizing the expences due to reservation of extra labor force than needed and firing employment of labor force using the Dynamic Programming. The derived algorithm is introduced into the computer simulation for Pusan port with the analyzed real data such as amount of cargo handling in the port with respect to working hour, cargo capacity, working step, the ratio of cargo handling facility and actual number of workers and we estimated the required labor force. As a result of analysis the labor force of Pusan port showed the over-employment such as maximum 21.4%, minimum 8.2% when we assumed that the averages of actual working hours and days were 8 hours in a day and 20 day in a month.

• Journal of the Korean Institute of Navigation
• /
• v.15 no.3
• /
• pp.13-24
• /
• 1991

This paper aims to determining the optimal capacity of Pusan port in view point of Container Physical Distribution cost. It has been established a coast model of the container physical distribution system in Pusan port is composed of 4 sub-systems and in-land transport system. Cargo handling system, transfer & storage system and in-land transport system, and analyzed the cost model of the system. From this analysis, we found that the system had 7 routes including in-land transport by rail or road and coastal transport by feeder ship between Pusan port and cargo owner's door. Though railway transport cost was relatively cheap, but, it was limited to choose railway transport routes due to the introducing of transport cargo allocation practice caused by shortage of railway transport capacity. The physical distribution ost for total import & export container through Pusan port was composed of 4.47% in port entring cost, 12.98% in cargo handling cost, 7.44% in transfer & storage cost and 75.11% in in-land transport cost. Investigation in case of BCTOC verified the results as follows. 1) The optimal level of one time cargo handling was verified 236VAN (377TEU) and annual optimal handling capacity was calculated in 516, 840VAN(826, 944TEU) where berth occupancy is $\rho$=0.6 when regardless of port congestion cost, 2) The optimal level of one time cargo handling was verified 252VAN (403TEU) and annual optimal handling capacity was calculated in 502, 110VAN (803, 376TEU) where berth occupancy is $\rho$=0.58 when considering of port congestion cost.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.10
• /
• pp.2454-2460
• /
• 2013

So far, the port cargo handling capacity of general cargo was computed using simple formulae based on mathematical models. However, this simple calculation could not be able to reflect the reality. Thus, the simulation method was applied in this paper to overcome the limitation that the calculation method used in the past studies has. The process occurring from arrival to departure of a ship, which is reflecting the process rules of berth, was modeled to estimate the optimum level of handling capacity by using an example of the loading and unloading of an appropriated wharf at the harbor, and simulation was performed by developing the prototype. The actual processing capability of Mukho port was compared to the estimated capability calculated using the simulation method and the optimum level of capability could be computed by repeatedly simulating the input variable condition of the simulation prototype.

• Journal of Navigation and Port Research
• /
• v.30 no.10 s.116
• /
• pp.793-800
• /
• 2006

The purpose of this paper is to show a way for extracting the core input and output variable in Korean seaports by using principal component analysis and DEA(data envelopment analysis). Two inputs(birthing capacity, and cargo handling capacity) and three outputs(export cargo handling amount, import cargo handling amount, and number of ship calls), and three cross sectional data(1995, 2000, and 2004) for 26 Korean seaports are considered for measuring the efficiencies of 21 DEA models. 21 models can be treated as variables and efficiencies as observations for extracting the core inputs and outputs variables by using principal component analysis. An empirical main result indicates that core input variable is cargo handling capacity, and core output is the number of ship calls. The Korean seaport authority can adopt the DEA and principal component analysis for deciding the development and investment to each seaport.

• Journal of Korea Port Economic Association
• /
• v.19 no.2
• /
• pp.55-67
• /
• 2003

The purpose of this study is to estimate and forecast the marine trading volumes based on the structural model. We employ GPH cointegration test since the structural model must be stationary to get the accurate predicted values. The empirical results show that our model is stationary. This paper also applies variance decompositions and impulse-response functions to the structural model composed of exchange rate, domestic industrial activity, and world business. The results indicate that while both loading and unloading volumes respond positively to the shocks in income and then decay very slowly, their responses are different to the shocks in exchange tate.

• Journal of Korean Port Research
• /
• v.5 no.2
• /
• pp.19-37
• /
• 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 Navigation and Port Research
• /
• v.31 no.5 s.121
• /
• pp.403-408
• /
• 2007

The purpose of this paper is to show a way for measuring the rankings of efficient seaports in Korea by using DEA(data envelopment analysis) and model suggested by Jahanshahloo et al(2006). Two inputs(birthing capacity, and cargo handling capacity) and three outputs(export cargo handling amount, import cargo handling amount, and number of ship calls), and one cross sectional data(2004) for 26 Korean seaports are considered for measuring the efficiencies. An empirical main result indicates that ranking order of efficient seaports are Okpo, Samcheok Ulsan, Daesan, Busan, Gohyun Ports. Samcheok Port is classified as the most strong efficient port among 16 general ports except 10 container ports. The Korean seaport authority can adopt the new measurement way introduced in this paper for measuring the exact ranking order of efficient seaports when it decides the development and investment to each efficient seaport.

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

• Journal of the Korean Institute of Navigation
• /
• v.5 no.1
• /
• pp.1-23
• /
• 1981

As far as transportation problems are concerned, the minimization of transportation cost is the most prevailing object. But in some cases, the cargo delivery time is the utter problem rather than the cost. For instance, we may imagine the case that the delivery of the construction materials is delayed behind the schedule and this makes the construction cost increased because of idle time of other materials and man power, in addition to the indemnity. Therefore the allocation of ships, in marine transportation which is now the main route of overseas trade, to the needed area on the required time is to be appropriately performed. However, there are several restrictions for cargo delivery to meet the demand, such as ship's size, number to be employed and cargo handling capacity of the ports, etc. And there are some other factors to be considered, that is, the degree of necessities of commodities, on their kinds, amount, and the time of arrival, etc. This paper deals with the problem of optimum allocation of ships emphasizing the cargo delivery time adopting Linear Programming technique with those cargo delivery restrictions and factors transformed by introducing the multi-speed conception, the conversion of multi-commodity to a single commodity, allowable delivery time, weight penalty number and nominating priority. This paper presents a case of optimum allocation of ships in the light of cargo delivery time for a construction company which has two different construction places and analyzes the result. This study will give a planner a good tool for optimum planning of maring transportation and be used for decision of schemes.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 1998.10a
• /
• pp.107-115
• /
• 1998

For the purpose of building the simulation model on cargo handling capacity of container terminal, we composed a model of container logistics system which has a 4 subsystems ; cargo handling, transportation, storage system and Gate complex system. Several date used in simulation gained through spot research and basic statistic analysis using raw data from January to Jane in 1998. The results of this study are as follows ; First, average available ratio of each subsystem was G/C 50%, Y/T 57.5%, storage system 56%, Gate complex 50%, and there was no subsystem occurring specific bottleneck. Second, comparing the results of simulation to the results of basic statistics, we can verify suitability of this simulation model. Third, Comparing the results of this study to the results of existed study, we were able to confirm a change of BCTOC container logistics system under IMF situation.