• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.486-488
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• 2012

본 논문에서는 로보틱스나 컴퓨터 게임 등의 다양한 분야에서 일반적으로 존재하는 동적인 환경에서 장애물 회피를 위한 경로 계획 알고리즘을 연구하였다. 제안하는 알고리즘은 전역 경로계획과 지역 경로계획의 두 단계로 이루어져 있고, A*와 가시성 그래프에 의해 구해진 전역 경로를 이동할 때에 동적 장애물을 감지하게 되면 이를 회피하기 위해 포텐샬장으로 지역 경로를 구성한다. 이 알고리즘은 포텐샬장을 A*와 결합함으로써 지역 최적화 문제를 해결하고 포텐샬장만으로 이동하는 경우에 비해 시간적인 측면에서도 더욱 효율적이다.

• Journal of Advanced Navigation Technology
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• v.19 no.2
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• pp.116-122
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• 2015

Motivated by continuous increase in flight demand, awareness of the importance in developing ways to increase aircraft operational efficiency on the airport movement area has been raised. This paper proposes a new routing algorithm for providing the shortest path in a right time, enhancing the aircraft movement efficiency. Many researches on developing algorithms have been performed, for example, Dijkstra algorithm and $A^*$ algorithm. The Dijkstra algorithm provide optimal solution but could possibly provide it with a cost of relatively longer computation time. On the other hand, $A^*$ algorithm does not guarantee the optimality of a solution. In this paper, we suggest a Hybrid $A^*$ algorithm, incorporating both algorithms to eliminate the weaknesses. Rigorous test shows the proposed Hybrid $A^*$ algorithm may achieve shorter computing time and optimality in searching the shortest 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.72-86
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• 2018

Schedule-based public transit routing algorithm computes a single route that calculated minimum travel time using the departure and arrival times for each stop according to vehicle operation plan. However, additional factors such as transfer resistance and alternative route choice are not reflected in the path finding process. Therefore, this paper proposes a improved RAPTOR that reflected transfer resistance and multi-path searching. Transfer resistance is applied at the time of transfer and different values can be set according to type of transit mode. In this study, we analyzed the algorithm's before and after results compared with actual route of passengers. It is confirmed that the proposed algorithm reflects the various route selection criteria of passengers.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.6 s.336
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• pp.23-32
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• 2005

This paper proposes a new algorithm for the energy constraint ad-hoc network which efficiently spread the energy usage over the network through the backup route scheme in order to increase the network lifetime. Recently, the various energy-efficient routing algorithms based on On-demanding method are proposed. Among them, PSR(Power-aware Source Routing) increased the network lifetime through the periodical route alternation depended on the use of the battery while DSR(Dynamice Source Routing) uses only the route selected during the route discovery phase. But PSR has a problem that it increases the route overhead because of the frequent flooding for the route alternation. For solving this problem, we propose HPSR(Hierarchical Power-aware Source Routing) which uses the backup route set during the route discovery in order to alternation the route without the flooding. HPSR increases the network lifetime due to the frequent route alternation using backup route while it decreases the routing overhead due to the reduced flooding. In this paper, we also prove the performance of HPSR through the simulation using OPNET.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.133-140
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• 2012

This paper suggests an algorithm that can shorten the complexity $O(n^2)$ of Dijkstra algorithm that is applied to the shortest path searching in real-time GPS Navigation System into an up-to-date O(n). Dijkstra algorithm manipulates the distance of the minimum length path by visiting all the nodes from the starting node. Hence, it has one disadvantage of not being able to provide the information on the shortest path every second, in a city that consists of sophisticated roads, since it has to execute number of node minus 1. The suggested algorithm, firstly, runs by means of organizing the set of out-neighbourhood nodes at each level of the tree, and root node for departure node. It also uses a method of manipulating the distance of the minimum path of all out-neighborhoods and interior of the out-neighborhoods. On applying the suggested algorithm to two sophisticated graphs consisted of bi-direction and uni-direction, we have succeeded to obtain the distance of the minimum length path, just as same as Dijkstra algorithm. In addition, it has an effect of shortening the time taken 4 times from number of node minus1 to number of level minus 1. The satisfaction of the drivers can be increased by providing the information on shortest path of detour, every second, when occurs any rush hour or any traffic congestion due to car accident, by applying this suggested algorithm to the real-time GPS system.

• Journal of the Society of Naval Architects of Korea
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• v.37 no.3
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• pp.90-98
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• 2000

Nesting and cutting path optimization have a great effect on price competitions and improvement of productivity in various industries such as the shipbuilding, the auto, the clothing, and so on. But the theoretical approach on the development of cutting path optimization algorithm, which can be applied effectively in the shipbuilding, has not been performed enough because parts are so complex and various. In this study, a new solution has been presented to solve the cutting path problem in 2-D cutting by using improved genetic algorithm. The presented optimization algorithm can search not only the cutting sequence of parts but also the position of piercing point by applying the effective neighborhood solution generating method

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.12-21
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• 2016

The emergency evacuation support system supports evacuation assistance when an urgent disaster occurs. We have implemented evacuation route search algorithm to assist people's escape when a disaster occurs such as fires or terrorism in the building. The algorithm will guide the escape route at the fastest emergency exit of each region at the emergency state. The algorithm calculates the escape route by applying the weighting factor of age groups and population density around the emergency exit and of other regions. So the system helps escape to bypass the crowded emergency exit and the disaster area, and reduces the congestion of emergency exit and overloading of evacuation route.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.8
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• pp.74-84
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• 2010

In this paper, we propose a preference-based shortest path algorithm which is combined with Ant Colony Optimization (ACO) and A* heuristic algorithm. In recent years, with the development of ITS (Intelligent Transportation Systems), there has been a resurgence of interest in a shortest path search algorithm for use in car navigation systems. Most of the shortest path search algorithms such as Dijkstra and A* aim at finding the distance or time shortest paths. However, the shortest path is not always an optimum path for the drivers who prefer choosing a less short, but more reliable or flexible path. For this reason, we propose a preference-based shortest path search algorithm which uses the properties of the links of the map. The preferences of the links are specified by the user of the car navigation system. The proposed algorithm was implemented in C and experiments were performed upon the map that includes 64 nodes with 118 links. The experimental results show that the proposed algorithm is suitable to find preference-based shortest paths as well as distance shortest paths.

• 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.