• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.943-948
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• 2018

In this paper, we propose a hybrid approach of combining $A^*$ and Genetic algorithm in the path search problem. In $A^*$, the cost from a start node to the intermediate node is optimized in principle but the path from that intermediate node to the goal node is generated and tested based on the cumulated cost and the next node in a priority queue is chosen to be tested. In that process, we adopt the genetic algorithm principle in that the group of nodes to generate the next node from an intermediate node is tested by its fitness function. Top two nodes are selected to use crossover or mutation operation to generate the next generation. If generated nodes are qualified, those nodes are inserted to the priority queue. The proposed method is compared with the original sequential selection and the random selection of the next searching path in $A^*$ algorithm and the result verifies the superiority of the proposed method.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2918-2920
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• 2005

본 논문에서는 네비게이션 시스템 사용 시 교통 체증 등의 상황이 발생하여 최적 경로를 따라 가는 경우의 소요시간이 실제 예상시간보다 크게 증가하게 되는 경우 주변의 샛길을 이용하여 보다 빠른 시간에 체증 구간을 회피하여 목적지에 도착 할 수 있게 하는 알고리즘을 제안하고 이를 항법서버에 구현한다. 교통 체증상황이 발생하는 경우 경로 탐색시의 각 길에 대한 weighting 을 조절함으로써 원래 최적경로와 다른 우회로를 찾아 낼 수 있도록 한다. 상용화 되어있는 네비게이션 단말기를 사용하였으며 PC 시뮬레이터와 개발 서버를 이용하여 샛길 탐색 기능을 구현하였다. 최적경로 탐색에는 A* 알고리즘을 응용하였으며 최적경로에서 샛길 탐색구간을 구하여 전체 경로를 탐색하는 알고리즘을 구현하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.835-838
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• 2008

Many researches on hierarchical path search have been studied so far. Even though partitioning regions is essential part, the researches are not enough. This paper proposes two efficient methods to partition regions: 1)a method based on voronoi algorithm in which a major node is central point of a region, 2) a method based on fired grid that partitions regions into major and minor. The performances of the proposed methods are compared with the conventional hierarchical path search method in which a region is formed by the boundary line of nearest 4 points of a major node in terms of the path search time and the accuracy. The results obtained from the experiments show that the method based on voronoi achieves short execution time and the method based grid achieves high accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.687-693
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• 2012

In this paper, we propose a optimal deployment method for cooperative exploration of swarm robots. The proposed method consists of two parts such as optimal deployment and path planning. The optimal area deployment is proposed by the K-mean Algorithm and Voronoi tessellation. The path planning is proposed by the potential field method and A* Algorithm. Finally, the numerical experiments demonstrate the effectiveness and feasibility of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.25-32
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• 2015

The Genetic algorithm is a search algorithm using evaluation, genetic operator, natural selection to populational solution iteratively. The convergence and divergence characteristic of genetic algorithm are affected by selection strategy, generation replacement method, genetic operator when genetic algorithm is designed. This paper proposes fast convergence genetic algorithm for time-limited robot path planning. In urgent situation, genetic algorithm for robot path planning does not have enough time for computation, resulting in quality degradation of found path. Proposed genetic algorithm uses fast converging selection strategy and generation replacement method. Proposed genetic algorithm also uses not only traditional crossover and mutation operator but additional genetic operator for shortening the distance of found path. In this way, proposed genetic algorithm find reasonable path in time-limited situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2037-2043
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• 2015

Proposed algorithm in this thesis introduced cells, units of router group, to conduct distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm. Also, through this experiment, in case of a network was damaged in existing optimal path algorithm, Dijkstra algorithm, the proposed algorithm was designed to route an alternative path and also as it has a 2nd shortest path in cells of the damaged network so it is faster than Dijkstra algorithm, The study showed that the proposal algorithm can support routing of alternative path, if Dijkstra algorithm is damaged in a network.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.2
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• pp.12-21
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• 2013

This study developed searching network reduction algorithm for reduce shortest path searching time. Developed algorithm is searching nodes that have the including possibility of less weights path than temporal path that consists minimum number of nodes and minimum sum of the straight line distances. The node that has the including possibility of shortest path is the node that the sum of straight line distance from start node and straight line distance to target node is less than the value that temporary path's weights divided by minimum weights units. If searching network reconstitutes only these nodes, the time of shortest path searching will be reduced. This developed algorithm has much effectiveness that start node and target node is close in large network.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.244-247
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• 2013

본 논문에서는 목적지들의 중요도를 이용하여 강화학습에 의한 목적지 경로 탐색을 제안한다. 일반적인 목적지 경로탐색은 목적지의 중요도나 방문빈도를 고려하지 않는 최단경로탐색을 수행한다. 그러므로 방문객들의 요구에는 맞지 않는 경로를 탐색한다. 강화학습의 특징은 관심 대상에 대한 구체적인 지배 규칙의 정보 없이도 최적화된 행동 방식을 학습시킬 수 있는 특징이 있다. 이를 이용하면 주요목적지를 누락시키지 않고 방문객들의 요구에 만족하는 경로를 탐색할 수 있다. 기존에 이용되고 있는 경로탐색 알고리즘과 강화학습기법이 적용된 알고리즘을 서로 분석하여 비교한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.102-108
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• 2012

The paper proposes an algorithm which finds a nonlinear cut path for a printed grayscale touching character image. The conventional algorithms were observed to fail in situations of complicated touching. We analyzed those situations, and based on the analysis results we identified problematic issues of the conventional algorithms. We modified the conventional algorithms in two aspects. First we propose a new penalizing term which is probable to guide correctly the cut path for touching situations difficult to separate. Second the preposed algorithm adopts a strategy of producing both the downward and upward paths and selecting better one. The experimental results on actual touching character images showed that the proposed algorithm was superior th conventional algorithms by 3~4% in terms of success ratio of separation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.349-352
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• 2005

이 논문에서는 분산된 생물학의 대사 네트워크들이 있을 때, 이를 통합하지 않은 상태에서 경로검색을 하는 분산 알고리즘을 제안한다. 대사 네트워크는 여러 데이터베이스에 존재하며 서로 중복되는 데이터를 가지고 있다. 제안한 방법은 네트워크 사이의 중첩이 있는 부분을 하이퍼 노드로 하고, 네트워크 자체는 하이퍼 에지로 하는 추상 하이퍼 그래프를 만들어서, 이를 이용한 상위수준의 경로를 구축한다. 각 네트워크내의 중첩된 영역간의 경로를 미리 계산해 둔 다음, 상위수준의 경로에 기반하여 분산된 대사네트워크 간에 존재하는 경로를 검색한다. 추상 하이퍼 그래프는 데이터베이스를 하이퍼 노드로 하는 것에 대한 경로탐색을 한 다음, 그 경로에 따라 데이터베이스 내에 존재하는 대사경로를 탐색한다. 이때 존재하는 대사경로가 많기 때문에 각각의 대사경로를 하이퍼 노드로 하는 추상 하이퍼 그래프를 만들어 경로를 탐색하고 나서 그 하위 노드에 대해 경로탐색을 한다. 이는 분산된 네트워크를 통합할 저장 공간 및 탐색시간을 줄일 수 있다는 장점이 있다.