• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.191-194
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• 2003

Location-allocation problem is known as one of the important problem faced in Industrial Engineering and Operations Research fielde. There are many variations on this problem for different applications, however, most of them consider no obstacle existing. Since the location-allocation problem with obstacles is very complex and with many infeasible solutions, no direct method is effective to solve it. In this paper we propose a hybrid Genetic Algorithm (hGA) method for solving this problem. The proposed hGA is based on Lagrangian relaxation method and Dijkstra's shortest path algorithm. To enhance the proposed hGA, a Fuzzy Logic Controller (FLC) approach is also adopted to auto-tune the GA parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.392-398
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• 2008

We propose a new path planning method for autonomous mobile robots. To maximize the utility of mobile robots, the collision-free shortest path should be generated by on-line computation. In this paper, we develop an effective and practical method to generate a good solution by lower computation time. The initial path is obtained from skeleton graph by Dijkstra's algorithm. Then the path is improved by changing the graph and path dynamically. We apply the dynamic programming algorithm into the stage of improvement. Simulation results are presented to verify the performance of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.53-60
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• 2010

We propose a motion planning method for autonomous mobile robots. In order to minimize traveling time, a smooth path and a time optimal velocity profile should be generated under kinematic and dynamic constraints. In this paper, we develop an effective and practical method to generate a good solution with lower computation time. The initial path is obtained from voronoi diagram by Dijkstra's algorithm. Then the path is improved by changing the graph and path simultaneously. We apply the dynamic programming algorithm into the stage of improvement. Simulation results are presented to verify the performance of the proposed method.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.311-312
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• 2007

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the Maklink graph method. At first, we produce the path of a mobile robot a the static environment. And then we find midpoints of each path using the Maklink graph. Finally the ant colony optimization algorithm is adopted to get a shortest path. In this paper, we prove the performance of the proposed algorithm is better than that of the Dijkstra algorithm through simulation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.45-56
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• 2007

As function and scale of the transit center get larger, the efficient guidance system in the transit center is essential for transit users in order to find their efficient routes. Although there are several studies concerning optimal path for the road, but insufficient studies are executed about optimal path inside the building. Thus, this study is to develop the algorithm about optimal path for car owner from the basement parking lot to user's destination in the transfer station. Based on Dijkstra algorithm which calculate horizontal distance, several factors such as fatigue, freshness, preference, and required time in using moving devices are objectively computed through rank-sum and arithmetic-sum method. Moreover, optimal public transportation is provided for transferrer in the transfer station by Neuro-Fuzzy model which is reflected on people's tendency about public transportation mode choice. Lastly, some scenarios demonstrate the efficiency of optimal path algorithm for pedestrian in this study. As a result of verification the case through the model developed in this study is 75 % more effective in the scenario reflected on different vertical distance, and $24.5\;{\sim}\;107.7\;%$ more effective in the scenario considering different horizontal distance, respectively.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.17-29
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• 2010

A container terminal productivity is maximized by a minimized time for processing containers. So, we have been elevated the container terminal productivity through an improvement of computing system, but there are a limitation because of problems for transportation management and method. A Y/T(Yard Tractor), which is a representative transportation, is able to do only one process, loading or unloading, at one time. So if the Y/T can do loading and unloading step by step at a same time, the processing time would be shortened. In this paper, we proposed an effective operating process of Y/T(Yard Tractor) Multi-Cycle System by applying RTLS(Real Time Location System) to Y/T(Yard Tractor) in order to improve the process of loading and unloading at the container terminal. For this, we described Multi-Cycle System. This system consists of a real time location of Y/T based on RTLS, an indicating of Y/T location in real time with GIS technology, and an algorithm(Dijkstra's algorithm) of the shortest distance. And we used the system in container terminal process and could improve the container terminal productivity. As the result of simulation for the proposed system in this paper, we could verify that 9% of driving distance was reduced compared with the existing rate and 19% of driving distance was reduced compared with the maximum rate. Consequently, we could find out the container performance is maximized.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2221-2229
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• 2006

Optimal path search algorithm which is a killer application of mobile device to utilize location information should consider traffic flows of the roads as well as the distance between a departure and destination. The existing path search algorithms, however, are net able to cope efficiently with the change of the traffic flows. In this paper, we propose a new optimal path search algorithm. The algorithm takes the current flows into consideration in order to reduce the cost to get destination. It decomposes the road network into Fixed Grid to get variable heuristics. We also carry out the experiments with Dijkstra and Ar algorithm in terms of the execution time, the number of node accesses and the accuracy of path. The results obtained from the experimental tests show the proposed algorithm outperforms the others. The algorithm is highly expected to be useful in a advanced telematics systems.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1483-1492
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• 1996

In this paper, related on the postal business with the GIS(Geographics Information System), it discusses design and implementation of the PROS(Postal Route Optimization System) model and its main module, the shortest path generation algorithm, for supporting to postal route managements. It explains examples requirements of postal route system, and suggests the efficient PROS model using our developed shortest path generation algorithm. Because the shortest path algorithm adopts not only consider the Dijkstra algorithm of graph theory, but also the method with the direction property, PROS can be implemented with fast and efficient route search. PROS is mainly constituted of the Shortest Generator, the Isochronal Area Generator, and the Path Rearrangement Generator. It also exploits the GIS engine and the spatial DBMS (Data Base Management System) for processing coordinates in the map and geographical features. PROS can be used in the management of postal delivery business and delivery area and route, and in the rearrangement of route. In the near future, it can be also applied to commercial delivery businesses, guides of routs and traffic informations, and auto navigation system with GPS(Global Positioning System).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.11-14
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• 2003

In this paper, we use Fuzzy Logic and Potential field method for optimal path planning of an autonomous mobile robot and apply to navigation for real-time mobile robot in 2D dynamic environment. For safe navigation of the robot, we use both Global and Local path planning. Global path planning is computed off-line using sell-decomposition and Dijkstra algorithm and Local path planning is computed on-line with sensor information using potential field method and Fuzzy Logic. We can get gravitation between two feature points and repulsive force between obstacle and robot through potential field. It is described as a summation of the result of repulsive force between obstacle and robot which is considered as an input through Fuzzy Logic and gravitation to a feature point. With this force, the robot fan get to desired target point safely and fast avoiding obstacles. We Implemented the proposed algorithm with Pioneer-DXE robot in this paper.