• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.43-54
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• 1996

This paper presents new heuristic search algorithms for searching rectilinear r(L1), link metric, and combined shortest paths in the presence of orthogonal obstacles. The GMD(GuidedMinimum Detour) algorithm combines the best features of maze-running algorithms and line-search algorithms. The SGMD(Line-by-Line GuidedMinimum Detour)algorithm is a modiffication of the GMD algorithm that improves efficiency using line-by-line extensions. Our GMD and LGMD algorithms always find a rectilinear shortest path using the guided A search method without constructing a connection graph that contains a shortest path. The GMD and the LGMD algorithms can be implemented in O(m＋eloge＋NlogN) and O(eloge＋NlogN) time, respectively, and O(e＋N) space, where m is the total number of searched nodes, is the number of boundary sides of obstacles, and N is the total number of searched line segment. Based on the LGMD algorithm, we consider not only the problems of finding a link metric shortest path in terms of the number of bends, but also the combined L1 metric and Link Metric shortest path in terms of the length and the number of bands.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.807-810
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• 2009

In this paper, we consider the shortest path problems in a simple polygon. The shortest path between two points inside a polygon P is a minimum-length path among all paths connecting them which don't pass by the exterior of P. A linear time algorithm for computing the shortest path in a general simple polygon requires triangulating a polygon as preprocessing. The linear time triangulating is known to very complex to understand and implement it. It is also inefficient in cases without very large input size. In this paper, we present the customized shortest path algorithms for specific polygon classes such as star-shaped polygons, edge-visible polygons, and monotone polygons. These algorithms need not triangulating as preprocessing, so they are simple and run very fast in linear time.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.171-179
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• 2005

This paper presents the algorithm using fuzzy inference that preestimates each link speed changed by different kinds of road situations. The elements we are considered are time zone, rainfall probability information and lane control information. This paper is consists of three parts. First of all we set up the fuzzy variables, and preestimate link speed changed by various road situations. For this process, we build the membership functions for each fuzzy variable and establish the fuzzy inference relations to find how fuzzy variables influence on link speed. Second, using backtracking method, we search the shortest route influenced by link speed changed by fuzzy inference. Third, we apply this algorithm to hypothetical network and find the shortest path. As a result, it is shown that this algorithm choose appropriate roundabout path according to the changing road situations.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.199-207
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• 2012

In this paper, we designed and implemented path search system using GPS information in photo. The system extracts EXIF information included in a photo to get path information and performs path search by applying the shortest path algorithm with the use of GPS information out of information, which was extracted in this way. And then it shows the obtained path information on web by utilizing Yahoo Map API. For this, the system is designed using a method of extracting location information in a photo and path sorting through applying the shortest path algorithm. UI(User Interface) was implemented using Yahoo Map API. Based on that, we implemented path search service using photo file that is included GPS information.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.430-448
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• 2001

In navigation system, a primary task is to compute the minimum cost route from the current location to the destination. One of major problems for navigation systems is that a significant amount of computation time is required when the digital road map is large. Since navigation systems are real time systems, it is critical that the path be computed while satisfying a time constraint. In this paper, we have developed a HiTi(Hierarchical MulTi) graph model for hierarchically structuring large digital road maps to speedup the minimum cost path computation. We propose a new shortest path algorithm named SPAH, which utilizes HiTi graph model of a digital road map for its computation. We prove that the shortest path computed by SPAH is the optimal. Our performance analysis of SPAH also showed that it significantly reduces the computation time over exiting methods. We present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.1-8
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• 2007

People tend to spend more time in indoor spaces than before such as shopping malls and subway stations. As buildings become larger and more complex, people feel difficulty in finding their ways to destinations. Consequently, a means to provide better paths can aid people in reducing time for finding ways. Routing information in large indoor spaces is especially required in emergency cases as fire, power failure and terror. This study suggests to compute optimal paths using $A^*$ algorithm based on raster GIS data structure. The suggested method can be used either in daily lives for path provision or in emergency cases for evacuation, and is illustrated on a campus building.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.42-48
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• 1999

Consider the situation that informations necessary to solve a certain problem are distributed among processors on a network. It is called a distributed algorithm that in this situation each processor exchanges the message with adjacent processors to solve the problems. This paper proposes a distributed algorithm to solve the problem that constructs the weighted shortest path tree in an asynchronous network system. In general, a distributed algorithm is estimated by the number of messages(message complexity of the distributed algorithm proposed in this paper are O(n53) and O(nln) respectively. where n is the number of processors on the network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.12A
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• pp.1879-1886
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• 2000

향후 컴퓨터 망은 버스트한 트래픽이 주종을 이룬다. OSPF 또는 RIP와 같은 최단경로 라우팅 프로토콜은 단일 경로의 라우팅으로 인해 병목을 초래하는 단점이 존재한다. 따라서, 발, 착신 노드간에 선택된 단일경로는 높은 정체를 유발하는 반면 다른 다수의 경로는 낮은 활용도를 나타낸다. 따라서, 본 고에서는 제한된 난수(bounded randomization)를 통해 전체 망에서 데이터 트래픽을 분산하는 라우팅 방법을 제안한다. 이 방법은 병목을 제거함으로서 망의 성능을 향상시킨다. 각각의 데이터 메시지는 원천 s에서 목적지 d로 전송되며 본 고에서 라우팅 프로토콜은 선택되는 망노드 집합의 a로부터 중간 노드 e를 무작위로 선택하고 데이터 메시지를 s에서 e까지의 최단경로로 라우팅을 한다. 이어서, e에서 d까지의 최단경로를 통해 데이터 메시지를 라우팅한다. 이는 각각의 원천과 목적지간 대역폭의 효율성을 증가시킨다. 본 고의 실험결과는 전체의 망에서 제안된 트래픽 분산 라우팅 프로토콜에서 기대치의 처리량(throughput), 메시지 손실과 메시지 지연에 따른 망성능 향상을 증명하고 있다. 그리고, 본 고의 알고리즘의 구현은 단지 최단경로 라우팅 프로토콜의 단순한 확장으로 가능하다.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.77-86
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• 2000

The shortest path problem is one of the mathematical Programming models that can be conveniently solved through the use of networks. The common shortest Path Problem is to minimize a single objective function such as distance, time or cost between two specified nodes in a transportation network. The sing1e objective model is not sufficient to reflect any Practical Problem with multiple conflicting objectives in the real world applications. In this paper, we consider the shortest Path Problem under multiple objective environment. Wile the shortest path problem with single objective is solvable in Polynomial time, the shortest Path Problem with multiple objectives is NP-complete. A genetic a1gorithm approach is developed to deal with this Problem. The results of the experimental investigation of the effectiveness of the algorithm are also Presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.311-312
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• 2009

$A^*$ 알고리즘을 이용한 경로 계획은 이동 로봇이나 게임 유닛이 주어진 환경에서 장애물과 충돌 없이 이동 가능한 경로를 찾는데 많이 사용된다. 그러나 $A^*$ 알고리즘은 출발 지점에서 목적 지점까지의 최단 거리를 갖는 경로를 찾는다. 두 지점 사이에 장애물이 있는 경우, 최단 경로는 보통 두 지점 사이의 장애물의 모서리를 스치는 경로이다. 따라서 로봇이나 게임 유닛이 최단 경로로 이동할 때, 장애물의 모서리에 부딪힐 수 있는 위험성이 커진다. 일반적인 격자 지도의 한 셀은 장애물이 있는 경우의 무한대의 비용과 장애물이 없는 경우의 비용을 갖는다. 본 논문에서는 장애물에 가까울수록 장애물이 없는 경우보다 높은 비용을 갖는 점층적 격자 지도(gradation grid map)를 이용한다. 점층적 격자 지도를 통해 $A^*$ 알고리즘은 장애물 근처의 높은 비용을 갖는 셀을 되도록 통과하지 않는 경로, 즉 보다 안전한 경로를 생성한다.