• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.113-116
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• 2000

The purpose of this study is to present a method for determining the k most vital arcs in shortest path problem using an evolutionary algorithm. The problem of finding the k most vital arcs in shortest path problem is to find a set of k arcs whose simultaneous removal from the network causes the greatest increase in the total length of shortest path. The problem determining the k most vital arcs in shortest path problem has known as NP-hard. Therefore, in order to deal with the problem of real world the heuristic algorithm is needed. In this study we propose to the method of finding the k-MVA in shortest path problem using an evolutionary algorithm which known as the most efficient algorithm among heuristics. For this, the expression method of individuals compatible with the characteristics of shortest path problem, the parameter values of constitution gene, size of the initial population, crossover rate and mutation rate etc. are specified and then the effective genetic algorithm will be proposed. The method presented in this study is developed using the library of the evolutionary algorithm framework (EAF) and then the performance of algorithm is analyzed through the computer experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.188-191
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• 2011

Path finding and path planning is crucial in today's world where time is an extremely valuable element. It is easy to plan the optimum path to a destination if provided a map but the same cannot be said for an unknown and unexplored environment. It will surely be exhaustive to search and explore for paths to reach the destination, not to mention planning for the optimum path. This is very much similar to finding for an exit of a maze. A very popular competition designed to tackle the maze solving ability of autonomous called Micromouse will be used as a guideline for us to design our maze. There are numerous ways one can think of to solve a maze such as Dijkstra's algorithm, flood fill algorithm, modified flood fill algorithm, partition-central algorithm [1], and potential maze solving algorithm [2]. We will analyze these algorithms from various aspects such as maze solving ability, computational complexity, and also feasibility to be implemented.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.327-333
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• 2011

Intelligent robots are widely needed in various areas of industry from extremely dangerous environments to service tasks. For autonomous mobile robots, it is significant to move itself safely to a destination point, recognizing its surroundings. Advances in sensor technology and its applications are achieved in order to develop an intelligent robot. In this paper, a mobile robot with a path-finding algorithm is presented. The path-finding algorithm is the one that does not only find a path to designated destination and also recognizes obstacles on the way, calculating its distance. 10 ultrasonic sensor are mounted on the front and rear of the mobile robot to figure out its position. Specular reflection and wide viewing angle, which are inherent characteristics of ultrasonic waves, cause errors in measuring distance.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.425-430
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• 2005

Many problems can be formulated in terms nf graphs and thus solved by graph-theoretic algorithms. This paper is concerned with finding paths between nodes over the distributed and overlapped graphs. The proposed method allows multiple agents to cooperate to find paths without merging the distributed graphs. For each graph there is a designated agent which is charged of providing path-finding service for hot graph and initiating the path-finding tasks of which path starts from the graph. The proposed method earlier on constructs an abstract graph so-called viewgraph for the distributed overlapped graphs and thus enables to extract the information about how to guide the path finding over the graphs. The viewgraph is shared by all agents which determine how to coordinate other agents for the purpose of finding paths. Each agent maintains the shortest path information among the nodes which are placed in different overlapped subgraphs of her graph. Once an agent is asked to get a path from a node on her graph to another node on another's graph, she directs other agents to provide the necessary information for finding paths.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.51-67
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• 1996

The optimal path-finding problem becomes complicated when multiple variables are simultaneously considered such as physical route length, degree of congestion, traffic capacity of intersections, number of intersections and lanes, and existence of free ways. Therefore, many researchers in various fields (management science, computer science, applied mathematics, production planning, satellite launching) attempted to solve the problem by ignoring many variables for problem simplification, by developing intelligent algorithms, or by developing high-speed hardware. In this research, an integration of expert system technique and case-based reasoning in high level with a conventional algorithms in lower level was attempted to develop an optimal path-finding system. Early application of experienced driver's knowledge and case data accumulated in case base drastically reduces number of possible combinations of optimal paths by generating promising alternatives and by eliminating non-profitable alternatives. Then, employment of a conventional optimization algorithm provides faster search mechanisms than other methods such as bidirectional algorithm and $A^*$ algorithm. The conclusion obtained from repeated laboratory experiments with real traffic data in Seoul metropolitan area shows that the integrated approach to finding optimal paths with consideration of various real world constraints provides reasonable solution in a faster way than others.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.418-418
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• 2000

This paper proposes a path planning algorithm for mobile robot. To generate an optimal path and minimum time path for a mobile robot, we use the Genetic Algorithm(GA) and Visibility Graph. After finding a minimum-distance between start and goal point, the path is revised to find the minimum time path by path-smoothing algorithm. Simulation results show that the proposed algorithms are more effective.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.35-48
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• 2008

In this paper, we propose a Dynamic Heuristic to reduce the number of node accesses and improve quality of path in the client-based navigation service. The Dynamic Heuristic is to use heuristic data from server that is calculated with traffic data. The server-based navigation service provides a path searched on server and transmits it to client, but we propose that server only provide heuristic data to client. The proposed client searches a path with heuristic transmitted data from server. We present a new algorithm for using Dynamic Heuristic in the path-finding. The algorithm bases Grid Based Path-Finding, and has minimum speed data of edges in grid. It removes several grids whose minimum speed is less than limited speed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.465-472
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• 2004

Analog CPPN-based optimal road boundary detection algorithm for autonomous vehicle is proposed. The CPPN is a massively connected analog parallel array processor. In the paper, the dynamic programming which is an efficient algorithm to find the optimal path is implemented with the CPPN algorithm. If the image of road-boundary information is utilized as an inter-cell distance, and goals and start lines are positioned at the top and the bottom of the image, respectively, the optimal path finding algorithm can be exploited for optimal road boundary detection. By virtue of the parallel and analog processing of the CPPN and the optimal solution of the dynamic programming, the proposed road boundary detection algorithm is expected to have very high speed and robust processing if it is implemented into circuits. The proposed road boundary algorithm is described and simulation results are reported.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.8
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• pp.385-393
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• 2008

The best coverage problem is finding a path whose worst distance to the sensor-set is the best among all paths. Instead, if the user stays close to its nearest two sensors, then the stability of the wireless connection may be guaranteed. So we consider the problem of finding a second best coverage path; given the sensor set U, a starting point s and a target point t, find a path whose worst distance to the second closest sensor is minimized. This paper presents an O(n logn) -time algorithm to find such a path. We also give experimental evidence showing that the connection to the sensor-set along a second best coverage path is more stable than that along the best coverage path.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.454-461
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• 2005

Car navigation system which is killer application fuses map management techniques into CPS techniques. Even if the existing navigation systems are designed for the shortest path, they are not able to cope efficiently with the change of the traffic flow and the bottleneck point of road. Therefore, it is necessary to find out shortest path algorithm based on time instead of distance which takes traffic information into consideration. In this paper, we propose a optimal path search algorithm based on the traffic information. More precisely. we introduce the system architecture for finding out optimal paths, and the limitations of the existing shortest path search algorithm are also analyzed. And then, we propose a new algorithm for finding out optimal path to make good use of the orientation of the collected traffic information.