• Journal of Korea Port Economic Association
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• v.36 no.3
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• pp.137-154
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• 2020

In this study, we analyze the performance of five major port distriparks and present a development plan. The analysis groups the performance into three categories: revitalization of companies in port distriparks, contribution to the port volume, and contribution to the national economy. The key parameters examined in detail include the ratio of hinterland volume to port volume (container and total cargo), port volume growth contribution rate, and job creation. Our results indicate that Gwangyang and Ulsan Ports showed steady growth for all the indicators analyzed, while Gwangyang Port was the only one among the five ports to display consistent steady growth. The results suggest that to achieve consistent growth, high value-added and specialized port distriparks based on the local economy should be established.

• Journal of Navigation and Port Research
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• v.32 no.1
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• pp.81-88
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• 2008

The forecast of a container traffic has been very important for port plan and development. Generally, statistic methods, such as regression analysis, ARIMA, have been much used for traffic forecasting. Recent research activities in forecasting with artificial neural networks(ANNs) suggest that ANNs can be a promising alternative to the traditional linear methods. In this paper, a hybrid methodology that combines both ARIMA and ANN models is proposed to take advantage of the unique strength of ARIMA and ANN models in linear and nonlinear modeling. The results with port traffic data indicate that effectiveness can differ according to the characteristics of ports.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.314-315
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• 2018

본 연구는 사회연결망 분석을 활용하여 2012년부터 2016년까지 부산항을 기항하는 컨테이너 정기선 항로 패턴 분석을 통해 세계 주요항만과의 중심성을 파악하여 부산항과 연결되어 있는 항만 네트워크의 구조적인 특성을 파악하였다. 부산항 컨테이너 정기선 항로 네트워크상에 연결정도 중심성, 근접중심성, 매개중심성이 높은 항만은 싱가포르항으로 분석되었으며, 실제 연도별 부산항 주요 국가 항만별 처리 물동량 순위와 부산항 컨테이너 정기선 항로 네트워크 중심성 분석 결과 간 순위 비교는 서로 상이한 것으로 나타났다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.11a
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• pp.174-176
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• 2011

부산항 컨테이너 하역시장의 안정화를 위해서는 시장의 구조적 문제해결이 긴요하다. 이 연구에서는 부산항의 현황과 문제점을 살펴본 후, 컨테이너 물동량과 유효하역능력을 비교 분석하여 운영구조 개편을 위한 컨테이너부두 통합운영 방안을 제시하였다. 특히 이 연구에서는 통합운영 구도 및 프로세스는 물론 신항으로의 북항부두 대체 적정시기를 제안하였다.

• Journal of Navigation and Port Research
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• v.34 no.5
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• pp.397-404
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• 2010

The Currently, most cargos of container transshipment between Busan Port and New Port are transported over land, and the rest is transported by barge. This study estimated firstly the traffic between those ports through simulations in order to analyze the feasibility of container transshipment by barge. It forecasted annual profitability using determinants to affect on the barge business by the traffic, and then, discussed the feasibility. This study supposed the flexible scenarios with 50%, 60%, 80%, or 100% transshipment and the 25 monthly barge service numbers between two ports, and measured the influences of different factors according to the above various scenarios. And then the sales were evaluated by the different traffics and freights scenarios provided the business would be actually operated. Finally, Net incomes were simulated to analyze the feasibility of different scenarios by various traffics and freights. The net income should be positive to get the feasibility. To achieve this, the minimum traffic should be secured and the lowest freight per TEU should be determined. While all countries of the world is controlling CO2 emissions and emphasizes the green logistics, this study contributed to solve at the same time the problems about the pollution and the efficiency of transportation by reviewing positively the feasibility of barge transportation as an alternative to transportation overland.

• Journal of Navigation and Port Research
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• v.35 no.1
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• pp.83-91
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• 2011

The accuracy of forecasting is remarkably important to reduce total cost or to increase customer services, so it has been studied by many researchers. In this paper, the artificial neural network (ANN), one of the most popular nonlinear forecasting methods, is compared with autoregressive integrated moving average(ARIMA) model through performing a prediction of container traffic. It uses a hybrid methodology that combines both the linear ARIAM and the nonlinear ANN model to improve forecasting performance. Also, it compares the methodology with other models in performance for prediction. In designing network structure, this work specially applies the genetic algorithm which is known as the effectively optimal algorithm in the huge and complex sample space. It includes the time delayed neural network (TDNN) as well as multi-layer perceptron (MLP) which is the most popular neural network model. Experimental results indicate that both ANN and Hybrid models outperform ARIMA model.

• Journal of Korea Port Economic Association
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• v.27 no.4
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• pp.187-205
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• 2011

In considering the size of container logistic flow of Korea, one-port as a hub port is desirable in Busan Port, but as development of Busan Port and Gwangyang Port began as two-ports, they are good as mega hub ports. In case when ports of other regions such as Incheon Port are additionally developed, it is very likely that they become feeder ports rather than mega hub ports. As capital area uses Incheon Port and Pyeongtaek Port for transportation, fierce competition arises due to excessive facilities of terminal companies and it is not easy to be profitable. Therefore, it is more profitable to develop regional hub ports centering on near-sea routes of Korea China Japan rather than local ports such as Incheon Port and Pyeongtaek Port for intensive trade and transportation in the capital area. To mitigate excessive competition between container terminal companies, we need administrative guidance to maintain adequacy through comparing tariffs between ports of Japan and China which are in competitive relations with Korean ports. This study analysed efficiency of container terminal companies in Gwangyang Port, Busan Port and Incheon Port using data for five years from 2006 to 2010. As analytical variables, length of quay, floor area of yard, the number of cranes and employees were analytical variables and a total freight volume was a productive factor.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.254-259
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• 1998

오늘날 컨테이너의 과다한 물동량 증가로 인하여 수작업으로 이루어지는 컨테이너 식별자를 처리하는데 어려움을 겪고 있는 가운데, 이를 자동으로 인식하고 그 결과를 항만 물류 처리 자동화 시스템에 적용하고자 하는 필요성이 대두되고 있다. 이에 본 논문에서는 컨테이너의 인식 처리를 자동화하기 위한 방안으로 컨테이너의 식별자 인식에 신경망 알고리즘의 하나인 Back-propagation을 적용하였으며, BP 알고리즘을 적용하기 위해서 적절한 scaling 비율을 구하고, 학습 DB를 구축하여 기존의 식별자 인식보다 신속하고 정확한 처리가 가능하도록 구현하였다.

• Journal of Korean Port Research
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• v.11 no.1
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• pp.1-11
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• 1997

The conventional methods of container forecasting is done through regression methods based on GNP growth trends and by other forecasting methods proposed by several authors. However these efforts prove to be inadequate with visible weakness and a more reasonable approach need to be determined. The succeeding sections elaborate the methodology and approach adopted. The results are then compared through a case study involving the forecast figures derived by the Pusan Port Authority and the values obtained by MRCS model introduced in this paper.

• 해운
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• no.8 s.19
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• pp.37-37
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• 2005