• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.137-143
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• 2017

In this paper, we propose optimal route searching algorithm using ANN(Artificial Neural Network) and implement route searching system. Our proposed scheme shows that the route using artificial neural network is almost same as the route using Dijkstra's algorithm but the time in our propose algorithm is shorter than that of existing Dijkstra's algorithm. Proposed route searching method using artificial neural network has better performance than exiting route searching method because it use several weight value in making different routes. Through simulation, we show that our proposed routing system improves the performance and reduces time to make route irrespective of the number of hidden layers.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.5
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• pp.574-584
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• 2017

In this paper, the optimizing path finding control method is studied for a Legged-robot. It's named TITAN-VIII. It has a lot of advantages over the wheeled robot in the ability to walk freely on an irregular ground. However, the moving speed on the ground of the Legged-robot is slower than the Wheeled-robot's. Consequently, the purpose of the method is presented in this paper to minimize its time when it walks to a goal. It find the path, our approach is based on an algorithm which is called Dijkstra's algorithm. In the rest of paper, the various posture of the robot is discussed to keep the robot always in the statically stable. Based on above works, the math formulas are presented to determine the joint angles of the robot. After that an algorithm is designed to find and keep robot on the desired trajectory. Experimental results of the proposed method are demonstrated in the last of paper.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.472-478
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• 2017

In this paper, we deals with optimizing traffic signal timing in grid networks by using a network topology design method. Optimizing traffic signal timing includes minimizing delay time delay between departure and destination by interlocking straight traffic signal in the minimum spanning tree(MST). On the assumption that users of network abide by the paths provided in this paper, this paper shows optimizing traffic signal timing in grid networks. the paths provided in this paper is gathered by using Dijkstra algorithm used in computer networks. The results indicate minimizing delay time of passing through the grid network and interlocking traffic signal in the grid network.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.721-726
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• 2012

In this paper, we proposed an efficient algorithm based on SPFA(shortest path faster algorithm), which is an improved the Bellman-Ford algorithm. The Bellman-Ford algorithm can be used on graphs with negative edge weights unlike Dijkstra's algorithm. And SPFA algorithm used a queue to store the nodes, to avoid redundancy, though the Bellman-Ford algorithm takes a long time to update the nodes table. In this improved algorithm, an adjacency list is also used to store each vertex of the graph, applying dynamic optimal approach. And a queue is used to store the data. The improved algorithm can find the optimal path by continuous relaxation operation to the new node. Simulations to compare the efficiencies for Dijkstra's algorithm, SPFA algorithm and improved Bellman-Ford were taken. The result shows that Dijkstra's algorithm, SPFA algorithm have almost same efficiency on the random graphs, the improved algorithm, although the improved algorithm is not desirable, on grid maps the proposed algorithm is very efficient. The proposed algorithm has reduced two-third times processing time than SPFA algorithm.

• Journal of Korea Game Society
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• v.17 no.5
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• pp.123-132
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• 2017

The path-finding algorithm refers to an algorithm for navigating the route order from the current position to the destination in a virtual world in a game. The conventional path-finding algorithm performs graph search based on cost such as A-Star and Dijkstra. A-Star and Dijkstra require movable node and edge data in the world map, so it is difficult to apply online games with lots of map data. In this paper, we provide a Heuristic-based Genetic Algorithm Path-finding(HGAP) using Genetic Algorithm(GA). Genetic Algorithm is a path-finding algorithm applicable to game with variable environment and lots of map data. It seek solutions through mating, crossing, mutation and evolutionary operations without the map data. The proposed algorithm is based on Binary-Coded Genetic Algorithm and searches for a path by performing a heuristic operation that estimates a path to a destination to arrive at a destination more quickly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.38-45
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• 2012

Finding shortest paths on time dependent networks is an important task for scheduling and routing plan and real-time navigation system in ITS. In this research, one-to-one time dependent shortest path algorithms based on link flow speeds on urban networks are proposed. For this work, first we select three general shortest path algorithms such as Graph growth algorithm with two queues, Dijkstra's algorithm with approximate buckets and Dijkstra's algorithm with double buckets. These algorithms were developed to compute shortest distance paths from one node to all nodes in a network and have proven to be fast and efficient algorithms in real networks. These algorithms are extended to compute a time dependent shortest path from an origin node to a destination node in real urban networks. Three extended algorithms are implemented on a data set from real urban networks to test and evaluate three algorithms. A data set consists of 4 urban street networks for Anaheim, CA, Baltimore, MD, Chicago, IL, and Philadelphia, PA. Based on the computational results, among the three algorithms for TDSP, the extended Dijkstra's algorithm with double buckets is recommended to solve one-to-one time dependent shortest path for urban street networks.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.79-86
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• 2020

In this paper, we propose an efficient emotional relaxation framework using Dijkstra algorithm based on anisotropic features. Emotional relaxation is as important as emotional analysis. This is a framework that can automatically alleviate the person's depression or loneliness. This is very important for HCI (Human-Computer Interaction). In this paper, 1) Emotion value changing from facial expression is calculated using Microsoft's Emotion API, 2) Using these differences in emotion values, we recognize abnormal feelings such as depression or loneliness. 3) Finally, emotional mesh based matching process considering the emotional histogram and anisotropic characteristics is proposed, which suggests emotional relaxation to the user. In this paper, we propose a system which can recognize the change of emotion easily by using face image and train personal emotion by emotion relaxation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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• pp.67-75
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• 2001

This paper presents a fast and effective methodology for service restoration in large-scale distribution systems. The service restoration problem is formulated as a constrained optimization problem and requires the fast computation time and superior solution because the more unfaulted out-of-service area should be restored as soon as possible. The proposed methodology is designed to consider the fast computation time and priority service restoration by dijkstra algorithm and fuzzy theory in large-scale distribution systems. Simulation results demonstrate the validity and effectiveness of the proposed on a 26-bus and 140-bus system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.729-731
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• 2016

The efficiency of genetic algorithm may be improved, as genetic generation increases. However, a number of algorithms are needed until desired results are obtained. In addition, if Hoc unit increases when linked to a network, there may be a need to compare with all the cases, which would result in many algorithms at a time, and if a single process deals with such algorithms, the efficiency will decrease. Therefore, efficiency of overall network will be decreased in the end. Proposal algorithm in this thesis introduced cells, units of router group, for distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm.

• Korean Journal of Computational Design and Engineering
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• v.6 no.3
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• pp.174-183
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• 2001

This study proposes an improved genetic algorithm (GA) to derive solutions for facility layout problems having inner walls and passages. The proposed algorithm models the layout of facilities on a flour-segmented chromosome. Improved solutions are produced by employing genetic operations known as selection, crossover, inversion, mutation, and refinement of these genes for successive generations. All relationships between the facilities and passages are represented as an adjacency graph. The shortest path and distance between two facilities are calculated using Dijkstra's algorithm of graph theory. Comparative testing shows that the proposed algorithm performs better than other existing algorithm for the optimal facility layout design. Finally, the proposed algorithm is applied to ship compartment layout problems with the computational results compared to an actual ship compartment layout.