자동화 컨테이너 터미널의 효율적인 운영을 위해서는 QC 의 지연 작업시간 최소화가 요구된다. 따라서 QC 와 장치장을 오가는 운송수단인 AGV의 효율적인 주행이 필요하다. 그리고 AGV 의 효율적인 운영을 위해서는 교착상태를 방지하기 위한 운영논리의 개발이 필수적이다. 본 연구는 컨테이너 터미널에서 사용될 수 있는 교착방지를 위한 ...
자동화 컨테이너 터미널의 효율적인 운영을 위해서는 QC 의 지연 작업시간 최소화가 요구된다. 따라서 QC 와 장치장을 오가는 운송수단인 AGV의 효율적인 주행이 필요하다. 그리고 AGV 의 효율적인 운영을 위해서는 교착상태를 방지하기 위한 운영논리의 개발이 필수적이다. 본 연구는 컨테이너 터미널에서 사용될 수 있는 교착방지를 위한 알고리즘 개발을 목표로 하였다. 기존의 교착방지 알고리즘은 차량이 교착구간에 도착할 때마다 그 때의 상황을 고려하여 교착방지를 위한 예약스케줄을 작성하는 방식이었으나 이는 지나치게 많은 계산시간을 소요한다는 단점이 있었다. 이를 극복하기 위하여 본 연구에서는 하나의 경로에 대해서 예약스케줄을 작성하여 두고 반복적으로 사용하는 예약 스케줄 표 방식을 제안하였다. 실험 결과 예약스케줄 표 방식은 그때그때의 주행경로에 대한 예약스케줄링을 위하여 계산시간이 필요 없기 때문에 AGV 의 실시간 운영을 위하여 유용한 방식임을 알 수 있었다.
자동화 컨테이너 터미널의 효율적인 운영을 위해서는 QC 의 지연 작업시간 최소화가 요구된다. 따라서 QC 와 장치장을 오가는 운송수단인 AGV의 효율적인 주행이 필요하다. 그리고 AGV 의 효율적인 운영을 위해서는 교착상태를 방지하기 위한 운영논리의 개발이 필수적이다. 본 연구는 컨테이너 터미널에서 사용될 수 있는 교착방지를 위한 알고리즘 개발을 목표로 하였다. 기존의 교착방지 알고리즘은 차량이 교착구간에 도착할 때마다 그 때의 상황을 고려하여 교착방지를 위한 예약스케줄을 작성하는 방식이었으나 이는 지나치게 많은 계산시간을 소요한다는 단점이 있었다. 이를 극복하기 위하여 본 연구에서는 하나의 경로에 대해서 예약스케줄을 작성하여 두고 반복적으로 사용하는 예약 스케줄 표 방식을 제안하였다. 실험 결과 예약스케줄 표 방식은 그때그때의 주행경로에 대한 예약스케줄링을 위하여 계산시간이 필요 없기 때문에 AGV 의 실시간 운영을 위하여 유용한 방식임을 알 수 있었다.
This thesis focuses on designing and operational issues for optimization of transport systems in port container terminals. The designing problems include the yard layout problem, the vehicle sizing problem, and the path design problem. The operational problems include problems of dispatching and rou...
This thesis focuses on designing and operational issues for optimization of transport systems in port container terminals. The designing problems include the yard layout problem, the vehicle sizing problem, and the path design problem. The operational problems include problems of dispatching and routing vehicles and problems of traffic control and deadlock prevention. The efficiency of an entire port container terminal depends on the efficiency of three handling subsystems such as a quay crane system, a transport system and a yard crane system. Among these three subsystems, the transport system plays a connecting key role of the two remaining subsystems. There are two factors considered in Chapter 2. One is the impact of storage yard designs on the performance of a transport system. The other is the impact of vehicle dispatching rules and yard operation rules on the terminal productivity. Regarding the yard design, a method was proposed for determining specifications of the yard considering the travel distance of vehicles and the storage capacity of the yard simultaneously. Moreover, it was discussed how to determine the layout and the dimension of yard blocks with a given length and width of a yard. A simulation study was used to evaluate the alternatives of the yard layout. One of the most important tactical problems for the efficient operation of container terminals is to determine the usage of the storage space. There are two different strategies for the usage of the storage space. One is the mixed strategy, in which the outbound and inbound containers are mixed in the same block. The other is the segregated strategy, in which the outbound and inbound containers are stacked in the different blocks. The performance of the different strategies for the space usage depends on the types of handling equipment in the yard and the number of handling vehicles allocated to each block. A simulation model was developed by considering various handling characteristics of yard cranes and used to evaluate the performances of various space usage and vehicle allocation strategies. Chapter 3 presents a method to estimate the productivity of the ship operation in container terminals. The productivity of the ship operation is influenced by the specifications of each piece of equipment, the layout of the terminal, and the operational strategies. The handling equipments considered in this study are QC (Quay Crane), RMGC (Rail Mounted Gantry Crane), and TR (Transporter). A simulation experiment was conducted to derive a regression equation for estimating the number of vehicles to satisfy a specified throughput capacity of a container handling system. Chapter 4 provides a method for designing flow path networks for automated transporters including automated guided vehicles, automated shuttle carriers, automated straddle carriers, and automated lifting vehicles. The objective of this problem is to minimize the travel time considering not only the moving time on guide paths but also the waiting time at intersections, merging positions, and transfer points. The travel time consists of the moving time and the waiting time. The waiting time can be estimated by a simulation study. It is noted that the congestion may be evaluated by considering waiting time at intersections and merging points on the guide path network. For example, additional time from merging and intersecting paths can be collected from simulation studies. In some cases, these parameters may be used for users to modify the design alternatives. Additional time may be added in such cases as (1) the case that two routes are merged; (2) the case that two routes are crossing each other. These cases must be modeled in the objective function. Chapter 5 suggests a routing method for Automated Guided Vehicles (AGVs) in port terminals by using a Q-learning technique. One of the most important issues for the efficient operation of automated guided vehicle system is to find the shortest time route instead of the shortest distance route, which is usually being used in practice. The waiting time must be accurately estimated to calculate the travel time. This study proposes a method to estimate the waiting time of vehicles resulting from the interference among vehicles during the travel by using the Q-learning technique. A simulation experiment was performed to evaluate the performance of the learning algorithm. The performance of the learning-based routes was compared with that of the shortest distance routes by a simulation study. Chapter 6 proposes a deadlock prevention algorithm for AGVS in port container terminal. Deadlock is a serious problem that must be solved before AGVs are deployed to real operations. This study assumes that the traveling area for AGVs is divided into a large number of grid-blocks and grid-blocks are reserved in advance during the travel of AGVs. The purposes of the reservation are to make the headway between AGVs and to prevent deadlocks. As the size of an AGV is much larger than the size of a grid-block on guide paths, this study assumes an AGV may occupy more than one grid-block at the same time. This study suggests a method to construct a table of reservation schedules by using a simulation. A sensitivity analysis is conducted to evaluate the performance of the reservation method in this study. The results of this study can be utilized in the transportation system of container terminals. The various methods provided in this study may be used to design not only physical structures but also various operational strategies of the transportation system in various types of container terminals.
This thesis focuses on designing and operational issues for optimization of transport systems in port container terminals. The designing problems include the yard layout problem, the vehicle sizing problem, and the path design problem. The operational problems include problems of dispatching and routing vehicles and problems of traffic control and deadlock prevention. The efficiency of an entire port container terminal depends on the efficiency of three handling subsystems such as a quay crane system, a transport system and a yard crane system. Among these three subsystems, the transport system plays a connecting key role of the two remaining subsystems. There are two factors considered in Chapter 2. One is the impact of storage yard designs on the performance of a transport system. The other is the impact of vehicle dispatching rules and yard operation rules on the terminal productivity. Regarding the yard design, a method was proposed for determining specifications of the yard considering the travel distance of vehicles and the storage capacity of the yard simultaneously. Moreover, it was discussed how to determine the layout and the dimension of yard blocks with a given length and width of a yard. A simulation study was used to evaluate the alternatives of the yard layout. One of the most important tactical problems for the efficient operation of container terminals is to determine the usage of the storage space. There are two different strategies for the usage of the storage space. One is the mixed strategy, in which the outbound and inbound containers are mixed in the same block. The other is the segregated strategy, in which the outbound and inbound containers are stacked in the different blocks. The performance of the different strategies for the space usage depends on the types of handling equipment in the yard and the number of handling vehicles allocated to each block. A simulation model was developed by considering various handling characteristics of yard cranes and used to evaluate the performances of various space usage and vehicle allocation strategies. Chapter 3 presents a method to estimate the productivity of the ship operation in container terminals. The productivity of the ship operation is influenced by the specifications of each piece of equipment, the layout of the terminal, and the operational strategies. The handling equipments considered in this study are QC (Quay Crane), RMGC (Rail Mounted Gantry Crane), and TR (Transporter). A simulation experiment was conducted to derive a regression equation for estimating the number of vehicles to satisfy a specified throughput capacity of a container handling system. Chapter 4 provides a method for designing flow path networks for automated transporters including automated guided vehicles, automated shuttle carriers, automated straddle carriers, and automated lifting vehicles. The objective of this problem is to minimize the travel time considering not only the moving time on guide paths but also the waiting time at intersections, merging positions, and transfer points. The travel time consists of the moving time and the waiting time. The waiting time can be estimated by a simulation study. It is noted that the congestion may be evaluated by considering waiting time at intersections and merging points on the guide path network. For example, additional time from merging and intersecting paths can be collected from simulation studies. In some cases, these parameters may be used for users to modify the design alternatives. Additional time may be added in such cases as (1) the case that two routes are merged; (2) the case that two routes are crossing each other. These cases must be modeled in the objective function. Chapter 5 suggests a routing method for Automated Guided Vehicles (AGVs) in port terminals by using a Q-learning technique. One of the most important issues for the efficient operation of automated guided vehicle system is to find the shortest time route instead of the shortest distance route, which is usually being used in practice. The waiting time must be accurately estimated to calculate the travel time. This study proposes a method to estimate the waiting time of vehicles resulting from the interference among vehicles during the travel by using the Q-learning technique. A simulation experiment was performed to evaluate the performance of the learning algorithm. The performance of the learning-based routes was compared with that of the shortest distance routes by a simulation study. Chapter 6 proposes a deadlock prevention algorithm for AGVS in port container terminal. Deadlock is a serious problem that must be solved before AGVs are deployed to real operations. This study assumes that the traveling area for AGVs is divided into a large number of grid-blocks and grid-blocks are reserved in advance during the travel of AGVs. The purposes of the reservation are to make the headway between AGVs and to prevent deadlocks. As the size of an AGV is much larger than the size of a grid-block on guide paths, this study assumes an AGV may occupy more than one grid-block at the same time. This study suggests a method to construct a table of reservation schedules by using a simulation. A sensitivity analysis is conducted to evaluate the performance of the reservation method in this study. The results of this study can be utilized in the transportation system of container terminals. The various methods provided in this study may be used to design not only physical structures but also various operational strategies of the transportation system in various types of container terminals.
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