• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.361-366
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• 2006

It is widely known that the dynamic optimal path algorithm, adopting real-time path finding, can be supporting an optimal route with which users are satisfied economically and accurately. However, this system has to search optimal routes frequently for updating them. The proposed concept of optimizing search area lets it reach heuristic optimal path rapidly and efficiently. Since optimal path should be increased in proportion to an distance between origin and destination, tremendous calculating time and highly efficient computers are required for searching long distance journey. In this paper, as a result of which the concepts of partial solution and representative path are suggested. It was possible to find an optimal route by decreasing a half area in comparison with the previous method. Furthermore, as the size of the searching area is uniform, comparatively low efficient computer is required for long distance trip.

• Journal of Korea Game Society
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• v.19 no.6
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• pp.83-90
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• 2019

Heuristic based Genetic Algorithm Pathfinding(H-GAP), a method without the need for node and edge information, can compensate the disadvantages of existing pathfinding algorithm, and perform the path search at high speed. However, because the pathfinding by H-GAP is non-node-based, it may not be an optimal path when it includes unnecessary path information. In this paper, we propose an algorithm to optimize the search path using H-GAP. The proposed algorithm optimizes the path by removing unnecessary path information through ray-tracing algorithm after the H-GAP path search is completed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.565-569
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• 2007

To find optimal path is killer application in the telematics system. The shortest path of conventional system, however, isn't always optimal path. That is, the path with minimum travelling time could be defined as optimal path in the road networks. There are techniques and algorithms for finding optimal path. Hierarchical path algorithm categorizes road networks into major layer and minor layer so that the performance of operational time increases. The path searched is accurate as much as optimal path. At above 2 system, a method to allocate minor roads to major road region influences the performance extremely. This paper proposes methods to determine search space for selecting major roads in the hierarchical path algorithm. In addition, methods which apply the proposed methods to hierarchical route algorithm is presented.

• Journal of The Korean Association of Information Education
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• v.2 no.2
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• pp.252-259
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• 1998

Vehicle navigation systems employ a certain route planning algorithm that provides the shortest path between the starting point and the destination point. The performance of a given route planning algorithm is measured through the degree of optimal route selection and the time cost to complete searching an optimal path. In this paper, various route planning algorithms are evaluated through computer simulation based on a real digital map database. Among those algorithms evaluated in this paper, the Modified Bi-directional A${\ast}$ algorithm is found to be the best algorithm for use in vehicle navigation systems.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10a
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• pp.636-638
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• 1998

WDM망을 구성하는데 있어서 광학적 파장은 가장 중요한 자원의 하나이다. 그러나 주어진 통신 요구를 모두 수용하면서 동시에 최소한의 파장만을 사용하는 WDM망의 설계 문제는 이미 NP-complete 계열의 문제인 것으로 밝혀졌으며 많은 휴리스틱 알고리즘들이 제안되었다. 본 논문에서는 임의의 물리적 망 위상(topology)과 완전 연결(full connection)형태의 통신 요구가 주어질 경우, 요구되는 파장 경로(Wavelength Path, lightpath)를 확립하기 위한 방법으로써 각 노드 사이의 최단 거리 경로를 기반으로 하여 탐색 공간을 만들고 구성된 탐색 공간 내에서 Branch-and-bound 탐색방식을 수행하는 파장 경로 설정 알고리즘을 제안한다. Branch-and-bound탐색방식은 초기에 좋은 bound조건을 가질 경우 주어진 시간 안에 보다 넓은 탐색 공간을 검색할 수 있으므로 최초의 탐색에서 가능한 좋은 성능의 파장 경로 설정을 발견할 수 있어야한다. 시뮬레이션 실험을 통하여 최초의 탐색에서 발견한 파장 경로 설정과 구성된 탐색 공간내의 최적해를 얻고, cut-set를이용하여 요구 파장 개수의 하위 한계값을 계산한후, 이를 상호 비교하여 제안된 알고리즘의 성능을 평가한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1354-1356
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• 2012

최근 ITS(Intelligent Transportation Systems)의 개발과 함께 차량용 내비게이션의 사용이 급증하면서 경로탐색의 중요성이 더욱 가속화되고 있다. 현재 차량용 내비게이션은 멀티미디어 및 정보통신 기술의 결합과 함께 다양한 기능 및 정보를 사용자에게 제공하고 있으며 이러한 기능과 정보를 사용해서 목적지점까지의 최단경로를 탐색하는 것이 내비게이션 시스템의 핵심기능이다. 이러한 경로탐색 알고리즘은 교통시스템, 통신 네트워크, 운송 시스템은 물론 이동 로봇의 경로 설정 등 다양한 분야에 사용되고 있다. 개미 집단 최적화(Ant Colony Optimization, ACO) 알고리즘은 메타 휴리스틱 탐색 방법으로 그리디 탐색(Greedy Search)뿐만 아니라 긍정적 반응의 탐색을 사용한 모집단에 근거한 접근법으로 순환 판매원 문제(Traveling Salesman Problem, TSP)를 풀기 위해 처음으로 제안되었다. 본 논문에서는 개미 집단 최적화(ACO) 알고리즘이 기존의 경로 탐색 알고리즘으로 알려진 Dijkstra 보다 최단경로 탐색에 있어서 더 적합한 알고리즘이라는 것을 설명하고자 한다.

• Journal of Korea Multimedia Society
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• v.5 no.6
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• pp.745-752
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• 2002

A* algorithm is widely used in optimal car route search which is a kind of informed search, since the locations of starting and ending points are known a priori. Unidirectional A* algorithm requires considerable search time but guarantees a optimal path, bidirectional A* algorithm does not guarantee a optimal path and takes even longer search time than unidirectional search to guarantee a optimal path. In this paper, a new bidirectional A* algorithm which requites less search time and guarantees a optimal path is proposed. To evaluate the efficiency of the proposed algorithm, several experiments are conducted in real road map and the results show that the algorithm is very effective in terms of finding a optimal path and search time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.199-202
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• 2009

The optimal path on real road network has been changed by traffic flow of roads frequently. Therefore a path finding system to find the optimal path on real network should consider traffic flow of roads that is changed on real time. The most of existing path finding methods do not consider traffic flow of roads and do not also perform efficiently if they use traffic information. In this paper, we propose an abstraction method of real road network based on the Terminal Based Navigation System (TBNS) with technique such as TPEG. TBNS can be able to provides quality of path better than before as using traffic information that is transferred by TPEG. The proposed method is to abstract real network as simple graph in order to use traffic information. It is composed boundary nodes based on real nodes, all boundary nodes that have the same of connection are merged together. The result of path finding on an abstract graph diminishes the search space.

• 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.

• 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.