• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.193-203
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• 2012

This study analyzed regular transportation costs between port warehouses and processing plants and between processing plants and central distribution centers and further transportation costs relations according to empty transfer rates in each circulation by examining the distribution routes of imported grain including wheat, barley, corn, and soybean, namely port warehouses, processing plants, and central distribution centers. Based on the results, the study compared and reviewed the logistics transportation costs. The analysis results of the alternative model show that logistics operational costs could be considerably cut down by introducing a flexible vehicle transportation operational method, which is to change the vehicle loading parts for proper substitute transportation after unloading and transport them to other locations such as central distribution centers instead of returning empty, as an alternative to high operational costs deriving from empty vehicle operation in each circulation after unloading items in case of transportation of imported grain and processed items. The results allow for a more realistic approach to general problems with large-scale distribution network operation and provide a theoretical foundation to serve as a guide to establish policies for corporate operation of imported grain logistics systems.

• Journal of Navigation and Port Research
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• v.29 no.9
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• pp.789-793
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• 2005

The container terminals in Korea usually adopts both the bar code and the image recognition systems at the gate complex to capture necessary information on containers passing through the gate. With the rapid advancement of Information Technology(IT) these systems, however, seem to make the user not satisfied due to the inherent limitations such as the long process time taken, low rate of recognition etc., This paper, therefore, examines the adoption of Radio Frequency Identification (RFID) technology to container terminals, and tried to get some implication for the way to improve the productivity of the terminal. The results imply that some improvement in the gate and storage yard operation is feasible by the benefit of using the information of vehicles and containers collected in advance by RFID technology.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.79-91
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• 2024

Large warehouses are building automation systems to increase efficiency. However, small warehouses, military bases, and local stores are unable to introduce automated logistics systems due to lack of space and budget, and are handling tasks manually, failing to improve efficiency. To solve this problem, this study designed small loading and unloading equipment that can be mounted on transportation vehicles. The equipment can be controlled remotely and is automatically controlled from the point where pallets loaded with cargo are visible using real-time video from an attached camera. Cargo recognition and control command generation for automatic control are achieved through a newly designed deep learning model. This model is designed to be optimized for loading and unloading equipment and mission environments based on the YOLOv3 structure. The trained model recognized 10 types of palettes with different shapes and colors with an average accuracy of 100% and estimated the state with an accuracy of 99.47%. In addition, control commands were created to insert forks into pallets without failure in 14 scenarios assuming actual loading and unloading situations.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.67-75
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• 2021

Despite the increase in sales of imported vehicles in Korea, research on the sales forecast of parts logistics centers is very limited. This study aims to perform a sales prediction on bestselling goods in the automobile part logistics center. System dynamics was adopted as a methodology for the prediction method, which considered causal relationship of variables that affected the dynamic characteristics and feedback loops. The analysis results showed that the consumable sales amount of oil increased over time. As a result of conducting the MAPE, the model was assessed to be a reasonable predictive model of 31.3%. In addition, the sales of battery products increased from every October in both of actual and predicted data followed by the peak sales in December and then decrease from next February. This study has academic implications that it secured actual data of specific imported automobile part logistics center, which has not done before in previous studies and quantitatively analyzed the prediction of the quantity of released goods of future sales through system dynamics.

• Journal of the Korea Safety Management & Science
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• v.19 no.3
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• pp.129-135
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• 2017

The respective delivering vehicle loaded with the own cargo moves into the respective delivery area. At the base, the delivery points D1 and D2, for example, have the same starting point but the destination is different. The average delivering time of the delivery vehicle is mostly more than 8 hours a day. Therefore, the efficiency of delivery is generally low. In this study, the deliveries will be forwarded from a base station to a delivery point where cross docking will be applied to a single vehicle, and will be distributed from the cross docking point through cross docking. If the distribution is implemented, one vehicle will not have to be operated from the base to the cross docking point. In that case, logistics cost will be reasonably saved by the reduction of transportation cost and labor time. If one vehicle only runs from the base to the cross docking point, each vehicle will be operated in two shifts, and the vehicle operation can be efficiently implemented. This research model is based on the assumption that the 3 types of ratios between the traffic volume of the vehicles starting at the base and the vehicles waiting at the cross docking point are set to the first ratio of 30% to 70%, the second ratio of 50% to 50% and the final ratio of 70% to 30%. As a result of the study, The delivery time in the cross docking point is much higher than that in present on the condition that the cargo volume in the D2 area is more than 50%. Likewise, the delivery time is slightly higher on the condition that the cargo volume is less than 50%. Time is reduced in terms of 50% model like AS-IS model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.319-322
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• 2014

Due to the active use of the internet currently, the transportation volume of logistics firms is dramatically increasing, but it is not easy to secure available vehicles and vehicle suppliers, so it is the most important for logistics companies to streamline transportations management and process. For such reason, there have been a number of studies to deal with VRP and VSP for efficient vehicle allocation planning of vehicle suppliers and vehicles. But it is hard to reflect traffic situations changing everyday and detailed geographic conditions, and it requires big scale of database and huge calculation time consumption as increase number of depots, which is very inefficient. For solving the vehicle allocation planning problems of 3PL firms with various constraints due to the transportation cost, this paper suggest new vehicle allocation information system and an algorithm based transportation cost/income. Also this paper presents actual results applied to a logistics company. As a result, the transportation profit of vehicle suppliers increased by 11 percent in average, when the developed transportation cost-based vehicle allocation system applied.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.160-167
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• 2023

This study focuses on the development of a Last-Mile delivery service using unmanned vehicles to deliver goods directly to the end consumer utilizing drones to perform autonomous delivery missions and an image-based precision landing algorithm for handoff to a robot in an intermediate facility. As the logistics market continues to grow rapidly, parcel volumes increase exponentially each year. However, due to low delivery fees, the workload of delivery personnel is increasing, resulting in a decrease in the quality of delivery services. To address this issue, the research team conducted a study on a Last-Mile delivery service using unmanned vehicles and conducted research on the necessary technologies for drone-based goods transportation in this paper. The flight scenario begins with the drone carrying the goods from a pickup location to the rooftop of a building where the final delivery destination is located. There is a handoff facility on the rooftop of the building, and a marker on the roof must be accurately landed upon. The mission is complete once the goods are delivered and the drone returns to its original location. The research team developed a mission planning algorithm to perform the above scenario automatically and constructed an algorithm to recognize the marker through a camera sensor and achieve a precision landing. The performance of the developed system has been verified through multiple trial operations within ETRI.

• The Journal of Bigdata
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• v.7 no.2
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• pp.129-137
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• 2022

With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.75-96
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• 2016

This paper investigates the usefulness of drones in an urban delivery system. We define the vehicle and drone routing problem with time window (VDRPTW) and present a model that can describe a dual mode delivery system consisting of drones and vehicles in the metropolitan area. Drones are relatively free from traffic congestion but have limited flight range and capacity. Vehicles are not free from traffic congestion, and the complexity of urban road network reduces the efficiency of vehicles. Using drones and vehicles together can reduce inefficiency of the urban delivery system because of their complementary cooperation. In this paper, we assume that drones operate in a point-to-point manner between the depot and customers, and that customers in the need of fast delivery are willing to pay additional charges. For the experiment datasets, we use instances of Solomon (1987), which are well known in the Vehicle Routing Problem society. Moreover, to mirror the urban logistics demand trend, customers who want fast delivery are added to the Solomon's instances. We propose a hybrid evolutionary algorithm for solving VDRPTW. The experiment results provide different useful insights according to the geographical distributions of customers. In the instances where customers are randomly located and in instances where some customers are randomly located while others form some clusters, the dual mode delivery system displays lower total cost and higher customer satisfaction. In instances with clustered customers, the dual mode delivery system exhibits narrow competition for the total cost with the delivery system that uses only vehicles. In this case, using drones and vehicles together can reduce the level of dissatisfaction of customers who take their cargo over the time-window. From the view point of strategic flexibility, the dual mode delivery system appears to be more interesting. In meeting the objective of maximizing customer satisfaction, the use of drones and vehicles incurs less cost and requires fewer resources.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.26-36
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• 2021

The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation's characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles' route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.