• Journal of Navigation and Port Research
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• v.35 no.1
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• pp.63-70
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• 2011

This paper discusses the problem of scheduling berth and container cranes simultaneously in port container terminals. A mixed-integer programming model is formulated by considering various practical constraints. A heuristic algorithm is suggested for solving the mathematical model. A numerical experiment was conducted to test the performance of the suggested heuristic algorithm.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1209-1214
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• 2010

In these days, rail container service is being more important because it has relatively simple network. In addition, small lot sizes of shipment, frequent shipment, and demand for flexible service are important characteristics in rail container transportation. Efficient container operation at terminals is important in reducing transportation costs and load/unload time. This paper describes the assigning track of freight trains in the railway freight terminal. The paper addresses the operational requirements and facility restrictions to construct a mathematical model for track assignment. In addition, it suggests several types of objectives for the model.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2000.10a
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• pp.261-264
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• 2000

Two hull forms of 2, 500 TEU Container Vessel, designed by Daedong Shipbuilding CO., LTD. were tested at the Circulating Water Channel of Chosun University for the evaluation of resistance performance. The test results of resistance, wave profile measurement and trim-sinkage measurement are compared in the form of diagrams and figures, and the results are discussed. A conclusion is drawn that the performance of modified form (model number : CU-201F2A2) is improved about 8% resistance performance at the design speed compare with original form (model number : CU-201F1A1).

• IE interfaces
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• v.20 no.2
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• pp.204-215
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• 2007

This paper addresses vehicle routing planning in freight container transportation systems where a number of loaded containers are to be delivered to their destination places. The system under consideration is static in that all transportation requirements are predetermined at the beginning of a planning horizon. A two-phased procedure is presented for freight container transportation. In the first phase, the optimal model is presented to determine optimal total time to perform given transportation requirements and the minimum of number of vehicles required. Based on the results from the optimal model, in the second phase, ASA(Accelerated Simulated Annealing) algorithm is presented to perform all transportation requirements with the least number of vehicles by improving initial vehicle routing planning constructed by greedy method. It is found that ASA algorithm has an excellent global searching ability through various experiments in comparison with existing methods.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.19-29
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• 2021

In the Port Logistics system, Container Stowage planning is an important issue for cost-effective efficiency improvements. At present, Planners are mainly carrying out Stowage planning by manual or semi-automatically. However, as the trend of super-large container ships continues, it is difficult to calculate an efficient Stowage plan with manpower. With the recent rapid development of artificial intelligence-related technologies, many studies have been conducted to apply enhanced learning to optimization problems. Accordingly, in this paper, we intend to develop and present a Deep Q-Learning Network model for the Master Stowage planning of Container ships.

• Journal of Korea Port Economic Association
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• v.29 no.3
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• pp.1-23
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• 2013

This paper estimates and forecasts the container throughput of Busan port using the monthly data for years 1992-2011. To do this, this paper uses the several seasonal multiplicative ARIMA models. Among several ARIMA models, the seasonal multiplicative ARIMA model $(1,0,1){\times}(1,0,1)_{12}$ is selected as the best model by AIC, SC and Hannan-Quin information criteria. According to the forecasting values of the selected seasonal multiplicative ARIMA model $(1,0,1){\times}(1,0,1)_{12}$, the container throughput of Busan port for 2013-2020 will increase steadily annually, but there will be some volatile variations monthly due to the seasonality and other factors. Thus, to forecast the future container throughput of Busan port and to develop the Busan port efficiently, we need to use and analyze the seasonal multiplicative ARIMA model $(1,0,1){\times}(1,0,1)_{12}$.

• Journal of Navigation and Port Research
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• v.31 no.1 s.117
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• pp.89-97
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• 2007

This paper presented a approach to the measurement of efficiency in container terminals in Korea. To perform this objective, it used Data envelopment analysis(DEA) which has particular applicability in the service sector. DEA as mathematical programming techniques enables relative efficiency ratings to be derived within a set of analysed units. So this paper investigated the efficiency employing DEA-CCR and DEA-BCC Model on data for 15 container terminals from 1998 through 2005. Results of this paper, suggested to some plan for operation strategy in Container terminals.

• Journal of Ship and Ocean Technology
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• v.10 no.4
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• pp.12-23
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• 2006

In this paper, a numerical study is carried out to investigate the turbulent flow around a twin-skeg container ship model with rudders including propeller effects. A commercial CFD code, FLUENT is used with body forces distributed on the propeller disk to simulate the ship stem and wake flows with the propeller in operation. A multi-block, matching, structured grid system has been generated for the container ship hull with twin-skegs in consideration of rudders and body-force propeller disks. The RANS equations for incompressible fluid flows are solved numerically by using a finite volume method. For the turbulence closure, a Reynolds stress model is used in conjunction with a wall function. Computations are carried out for the bare hull as well as the hull with appendages of a twin-skeg container ship model. For the bare hull, the computational results are compared with experimental data and show generally a good agreement. For the hull with appendages, the changes of the stem flow by the rudders and the propellers have been analyzed based on the computed result since there is no experimental data available for comparison. It is found the flow incoming to the rudders has an angle of attack due to the influence of the skegs and thereby the hull surface pressure and the limiting streamlines are changed slightly by the rudders. The axial velocity of the propeller disk is found to be accelerated overall by about 35% due to the propeller operation with the rudders. The area and the magnitude of low pressure on the hull surface enlarge with the flow acceleration caused by the propeller. The propellers are found to have an effect on up to the position where the skeg begins. The propeller slipstream is disturbed strongly by the rudders and the flow is accelerated further and the transverse velocity vectors are weakened due to the flow rectifying effect of the rudder.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.27-33
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• 2024

Following the COVID-19 pandemic, congestion within container terminals has led to a significant increase in waiting time and turnaround time for external trucks, resulting in a severe inefficiency in gate-in and gate-out operations. In response, port authorities have implemented a Vehicle Booking System (VBS) for external trucks. It is currently in a pilot operation. However, due to issues such as information sharing among stakeholders and lukewarm participation from container transport entities, its improvement effects are not pronounced. Therefore, this study proposed a deep learning-based predictive model for external trucks turnaround time as a foundational dataset for addressing problems of waiting time for external trucks' turnaround time. We experimented with the presented predictive model using actual operational data from a container terminal, verifying its predictive accuracy by comparing it with real data. Results confirmed that the proposed predictive model exhibited a high level of accuracy in its predictions.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.145-170
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• 2005

This paper presents scheduling models for dispatching vehicles to accomplish a sequence of container jobs at the container terminal, in which the starting times as well as the order of vehicles for carrying out these jobs need to be determined. To deal with this scheduling problem, three mixed 0-1 integer programming models, Model 1, Model 2 and Model 3 are provided. We present interesting techniques to reformulate the two mixed integer programming models, Model 1 and Model 2, as pure 0-1 integer programming problems with simple constraint sets and present a lower bound for the optimal value of Model 1. Model 3 is a complicated mixed integer programming model because it involves a set of non-smooth constraints, but it can be proved that its solutions may be obtained by the so-called greedy algorithm. We present numerical results showing that Model 3 is the best among these three models and the greedy algorithm is capable of solving large scale problems.