• 제목/요약/키워드: container model

검색결과 812건 처리시간 0.024초

크레인 대수의 제약을 고려한 선석계획 문제에 대한 발견적 해법 (A Heuristic Algorithm for Berth Planning with a Limited Number of Cranes)

  • 박영만;김갑환
    • 한국항해항만학회지
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    • 제35권1호
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    • pp.63-70
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    • 2011
  • 본 연구는 컨테이너 터미널에서 선박의 선적작업을 위한 선석배정 및 크레인 할당문제를 동시에 결정하는 문제를 다루고 있다. 실제 컨테이너 터미널에서 고려하고 있는 다양한 형태의 제약을 고려하여 선석계획 및 크레인할당 문제에 대한 혼합정수모델을 제시하였다. 제안된 문제에 대해 좋은 해를 짧은 시간 안에 구하기 위하여 발견적 해법을 제시하였다. 또한 수치예제를 이용하여 제시된 발견적 기법의 수행도를 비교분석하였다. 분석결과 제시된 기법은 짧은 시간 안에 좋은 해를 제공하는 것으로 나타났다.

철도 터미널 화물열차 작업선배정에 관한 연구 (A Study on the Assigning Track of Freight Trains in a Rail Container Terminal)

  • 김경민;박범환;김동희;홍순흠
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2010년도 춘계학술대회 논문집
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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.

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2,500TEU CONTAINER 선형개발에 대한 실험적 연구 (An Experimental Study on the Hull Form Development of the 2,500TEU Container Vessel)

  • 이귀주;이창훈;최영달;최영빈
    • 한국해양공학회:학술대회논문집
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    • 한국해양공학회 2000년도 추계학술대회 논문집
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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).

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화물컨테이너 운송을 위한 시뮬레이티드 어닐링 기반의 차량경로계획 (Simulated Annealing Based Vehicle Routing Planning for Freight Container Transportation)

  • 이상헌;최해정
    • 산업공학
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    • 제20권2호
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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.

컨테이너 선박 마스터 적하계획을 위한 심층강화학습 모형 (Deep Q-Learning Network Model for Container Ship Master Stowage Plan)

  • 신재영;류현승
    • 한국산업융합학회 논문집
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    • 제24권1호
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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.

승법계절 ARIMA 모형에 의한 부산항 컨테이너 물동량 추정과 예측 (Forecasting the Container Throughput of the Busan Port using a Seasonal Multiplicative ARIMA Model)

  • 이재득
    • 한국항만경제학회지
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    • 제29권3호
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    • pp.1-23
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    • 2013
  • 본 연구는 1992년부터 2011년까지 월별자료를 사용하여 여러 가지 시계열 추정모델과 승법 계절 ARIMA 모형을 설정하여 부산항의 컨테이너 물동량을 추정하고 예측하였다. 여러 가지 모델로 추정한 결과 부산항의 컨테이너 물동량과 물동량 변동 모두 계절을 승법한 ARIMA 모델 $(1,0,1){\times}(1,0,1)_{12}$로 추정하였을 때, 추정결과와 Akaike information, Schwarz, Hannan-Quin 기준 등으로 보아, 가장 좋은 ARIMA 추정과 예측 모형으로 나타났다. 그리하여 부산항 물동량 추정의 최적모형인 ARIMA $(1,0,1){\times}(1,0,1)_{12}$ 모형에 의해 향후 8년간 96개월에 대한 부산항 물동량 미래 예측치(2013-2020년)를 월별로 추정하여 예측한 결과 2013년부터 부산의 물동량은 연도별로 조금씩 지속적으로 증가하는 추세를 보일 것으로 나타났다. ARIMA $(1,0,1){\times}(1,0,1)_{12}$ 모형에 의한 부산항의 컨테이너 물동량의 연도별 예측량은 2013년 1천 891만 TEU, 2014년 2천 34만 TEU, 2015년 2천 188만 TEU, 2016년 2천 353만 TEU, 2017년 2천 531만 TEU, 2018년 2천 722만 TEU 그리고 2020년 3천 148만 TEU 등으로 나타났다.

우리나라 컨테이너터미널 효율성 분석에 관한 연구 - 부산항, 광양항을 중심으로 - (A Study on the Efficiency Analysis of Korean Container Terminal - Focus on Busan Port, Gwangyang Port -)

  • 최민승;송재영;류동근;박병근
    • 한국항해항만학회지
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    • 제31권1호
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    • pp.89-97
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    • 2007
  • 본 연구에서는 국내 컨테이너 전용 터미널(부산항 8개 터미널, 광양항 6개 터미널)을 대상으로 DEA(Data Envelopment Analysis) 모형을 통해 효율성을 분석하였다. 일정 시점을 대상으로 한 분석이 아니라, 1998년$\sim$2005년 동안의 효율성 분석을 실시하였으며, 이를 통해 각 터미널의 효율성 변화를 살펴보았다. 본 논문의 분석 결과는 우리나라 터미널의 상대적인 효율성 값을 제시해 줄 뿐만 아니라 신규 터미널 생성, 운영사의 변화, 터미널의 통합 운영 등에 따른 터미널 생산성의 변화 등을 제시하여 줌으로써 터미널 운영사의 향후 운영전략에 시사점을 제공하고 있다.

A Numerical Study of Turbulent Flow Around a Twin-Skeg Container Ship Model with Appendages

  • Kim, Hyoung-Tae;Lee, Pyung-Kuk;Kim, Hee-Taek
    • Journal of Ship and Ocean Technology
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    • 제10권4호
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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.

컨테이너 터미널 내 반출입 차량 체류시간 예측 모형 (Prediciton Model for External Truck Turnaround Time in Container Terminal)

  • 김영일;신재영
    • 한국항해항만학회지
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    • 제48권1호
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    • pp.27-33
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    • 2024
  • 코로나 팬데믹 이후 컨테이너 터미널 내 혼잡도 증가에 따라 반출입 차량 작업 대기 및 체류시간이 급증하여 반출입 작업 비효율이 극심한 실정이다. 이에 항만 당국은 반출입예약시스템(Vehicle Booking System; VBS)을 구축하여 시범운영 중에 있으나 이해관계자 간 정보공유 문제 및 컨테이너 운송 주체의 미온적 참여 등으로 인해 개선효과가 뚜렷하지 않다. 따라서 본 연구에서는 반출입 차량의 작업 대기 및 체류시간 문제의 해결을 위한 기초자료로써, 딥러닝 기반의 반출입 차량 체류시간 예측 모형을 제시하였다. 실제 컨테이너 터미널의 반출입 운영 데이터를 통해 제시한 예측 모형을 실험하고 실제 데이터와 비교하여 예측 정확도를 검증한 결과 제시한 예측 모형이 높은 예측 정확도를 보이는 것을 확인하였다.

MIXED INTEGER PROGRAMMING MODELS FOR DISPATCHING VEHICLES AT A CONTAINER TERMINAL

  • ZHANG LI WEI;YE RONG;HUANG SHELL YING;HSU WEN JING
    • Journal of applied mathematics & informatics
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    • 제17권1_2_3호
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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.