• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.6
• /
• pp.445-452
• /
• 2016

This paper discusses the dynamics and control problem of an overhead shuttle system (OSS), which is a critical part of the automated container terminal at a port. The main purpose of the OSS is efficient automated transport function of containers, which also requires high precision and safety. A major difference between the OSS and the conventional container crane is the configuration of the cables for hoisting the spreader. A mathematical model of the OSS is developed here for the first time, which results in an eight-pole system. Also, open loop control methods (trapezoidal and notch-type velocity profiles) are investigated so that the command input to the overhead shuttle produces the minimum possible sway of the payload. Simulation results show that the vibration suppression capability of the OSS is superior to the conventional overhead container crane, which is partially due to the cable configuration.

• Journal of the Korea Society of Computer and Information
• /
• v.7 no.1
• /
• pp.62-67
• /
• 2002

Construction of automated terminal is urgently demanded to gain the foundation of hub-port in north east Asia. Therefore I suggest an adequate operating system model of automated terminal in Korea. In this paper the aim of automated terminal operating system is satisfied, four basic models are divided according to moving course of export and import cargo of each automated equipments, several input data are changed and analyzed dynamically by Trial and Error method, and then an optimized operating system model is designed. It is a Premise that all the yard equipments described in this paper must be automatic except quay crane.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2007.12a
• /
• pp.335-336
• /
• 2007

This paper propose a heuristic method that divides the block into some work regions to operate stacking cranes efficiently in a automated container terminal where the blocks with non-crossing stacking cranes(SC) are laid out in perpendicular to the quay. Typically, fund over between SCS and trucks occur at each side if the blocks, and each if the landside and seaside SCS is responsible for the jobs that occur at its own side. When a container to be fetched is located far from fund over point, the SC should move a long distance and the interference between the two cranes am occur, which decreases the productivity of the SCS. Therefore, our method divides the block into two exclusive and one shared regions and let the containers located far from their fund over points to be transferred to the shared region by the other side crane before they are carried out. Although simple this method am reduce the crane movement and the interference between the two cranes. Simulation experiment shows that our proposed method significantly improves the productivity if the container terminal than previous heuristic that does not divide work regions.

• Journal of Intelligence and Information Systems
• /
• v.14 no.4
• /
• pp.103-116
• /
• 2008

This paper proposes quay crane (QC) scheduling algorithms that determine the working sequence of QCs over ship bays in a container vessel in automated container terminals. We propose two scheduling algorithms that examine the distribution of export containers in the stacking yard and determine the sequence of ship bays to balance the workload distribution among the yard blocks. One of the algorithms is a simple heuristic algorithm which dynamically selects the next ship bay based on the entropy of workloads among yard blocks whenever a QC finishes loading containers at a ship bay and the other uses genetic algorithm to search the optimal sequence of ship bays. To evaluate the fitness of each chromosome in the genetic algorithm, we have devised a method that is able to calculate an approximation of loading time of container vessels considering the workloads among yard blocks. Simulation experiments have been carried out to compare the efficiency of the proposed algorithms. The results show that our QC scheduling algorithms are efficient in reducing the turn-around time of container vessels.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.2
• /
• pp.41-48
• /
• 2002

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1999.04a
• /
• pp.306-307
• /
• 1999

• Journal of Navigation and Port Research
• /
• v.42 no.1
• /
• pp.47-56
• /
• 2018

In this study, the focus is on the issue of whether a container terminal is facing the limitation of its productivity for serving mega-vessels with numerous containers. In order to enhance the terminal operations, a new conceptual design of the container handling system have been proposed. This research focuses on the rail-based container transport system and its operations. This system consists of rail-based shuttle cranes and rail-based transporters called flatcars. The deadlock problem for managing automated transporters in container terminals has been an important issue for a long measurement of time. Therefore, this study defines the deadlock situation and proposes its avoidance rules at the rail-based container transport system, which is required to handle numerous container throughput operations. The deadlock in the rail-based container transport system is classified into two parts: deadlock between cranes and flatcars; deadlock between flatcars. We developed the simulation model for use with characterizing and analyzing the rail-based container transport system. By running the simulation, we derived possible deadlock situations, and propose the several deadlock avoidance algorithms to provide results for these identified situations. In the simulation experiments, the performances of the deadlock avoidance algorithms are compared according to the frequency of deadlocks as noted in the simulations.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.11
• /
• pp.1106-1110
• /
• 2010

This paper proposes a method of optimizing a stacking strategy for an automated container terminal using multi-objective evolutionary algorithms (MOEAs). Since the yard productivities of seaside and landside are conflicting objectives to be optimized, it is impossible to maximize them simultaneously. Therefore, we derive a Pareto optimal set instead of a single best solution using an MOEA. Preliminary experiments showed that the population is frequently stuck in local optima because of the difficulty of the given problem depending on the yard occupancy rate. To cope with this problem, we propose another method of simultaneously optimizing two problems with different difficulties so that diverse solutions can be preserved in the population. Experimental results showed the proposed method can derive better stacking policies than the compared method solving a single problem given the same computational costs.

• Journal of Navigation and Port Research
• /
• v.31 no.10
• /
• pp.869-877
• /
• 2007

This paper proposes a realtime scheduling method using local search algorithm for non-crossable yard cranes in automated container terminal. To take into consideration the dynamic property of yard crane operation and satisfy the real time constraint, the proposed method repeatedly builds crane schedule for the jobs in a fixed length look-ahead horizon whenever a new job is requested In addition, the proposed method enables the co-operation between yard cranes through prior re-handling and re-positioning in order to resolve the workload imbalance problem between the two cranes, which is one of the primary causes that lower the performance of yard cranes. Simulation-based experiments have shown that the proposed method outperforms the heuristic based methods, and the cooperation scheme contributes a lot to the performance improvement.

• Journal of Navigation and Port Research
• /
• v.32 no.10
• /
• pp.837-844
• /
• 2008

In an automated container terminal, various factors affect the operation of container handling equipment such as quay cranes and AGVs, and thus calculating the exact operation time is nearly infeasible. This uncertainty makes it difficult to dispatch AGVs well. In this paper, we propose a simulation-based AGV dispatching algorithm When dispatching an AGV to an operation, the proposed algorithm conducts multiple stochastic simulation for the succeeding AGV operations for the predetermined period to collect stochastic samples of the result of the dispatching. In the stochastic simulation, the uncertainty of crane operations is represented as a simple probability distribution and the operation time of a crane is determined according to this. A dispatching option is evaluated by the total delay time of quay cranes which is estimated by averaging the quay crane delay of each simulation In order to collect a sufficient number of samples that guarantee the credibility of the evaluation, we devised a high-speed simulator that simulates AGV operation The effectiveness of the proposed algorithm is validated by simulation experiments.