• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.386-396
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• 2002

This paper presents a neural network-based near-optimal routing algorithm. It employs a modified Hopfield Neural Network (MHNN) as a means to solve the shortest path problem. It uses every piece of information that is available at the peripheral neurons in addition to the highly correlated information that is available at the local neuron. Consequently, every neuron converges speedily and optimally to a stable state. The convergence is faster than what is usually found in algorithms that employ conventional Hopfield neural networks. Computer simulations support the indicated claims. The results are relatively independent of network topology for almost all source-destination pairs, which nay be useful for implementing the routing algorithms appropriate to multi -hop packet radio networks with time-varying network topology.

• 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.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.862-866
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• 2003

Traveling Salesman Problem(TSP) is a combinational optimization problem, Genetic Algorithm(GA) and Lin-Kernighan(LK) Heuristic［1］that is Local Search Heuristic are one of the most commonly used methods to resolve TSP. In this paper, we introduce ACS(Ant Colony System) Algorithm as another approach to solve TSP and propose a new pheromone updating method. ACS uses pheromone information between cities in the Process where many ants make a tour, and is a method to find a optimal solution through recursive tour creation process. At the stage of Global Updating of ACS method, it updates pheromone of edges belonging to global best tour of created all edge. But we perform once more pheromone update about created all edges before global updating rule of original ACS is applied. At this process, we use the frequency of occurrence of each edges to update pheromone. We could offer stochastic value by pheromone about each edges, giving all edges' occurrence frequency as weight about Pheromone. This finds an optimal solution faster than existing ACS algorithm and prevent a local optima using more edges in next time search.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.304-307
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• 2006

현재 센서네트워크 분야는 여러 방면에서 이슈가 되고 있다. 해양 센서네크워크는 지상에서의 전파를 사용할 수 없으므로 음향(Acoustic)파를 사용한다. 일정거리만큼만 음파가 도달하는 환경에서 원하는 노드를 찾아가는 최적화 문제는 NP complete한 TSP 문제이다. 최적경로를 찾았을 경우 음파의 에너지 손실 또한 저전력으로 사용된다. 본 논문에서는 최적탐색기법인 유전자알고리즘을 사용하여 목적노드를 찾기위한 최적경로를 시뮬레이션 해 보았다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.1 s.6
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• pp.1-13
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• 2005

For integrated transit networks operated with diverse transit modes, it is difficult to find related literatures on the provision of multiple travel time routes information. This study proposes a methodology on how to select K number of least time transit routes in the integrated transit network with two modes, bus and subway. In the Proposed method, three constraints usually (will be) encountered for decision by users-(1) service time constraints of travel modes, (2) maximum payment fare constraints under the integrated distance based fare system, and (3) maximum number of transfer constraints - are taken into consideration in the searched routes. The experimental studies shows that the proposed method properly provides K number of least time routes. In addition, it somehow proves that by combinatorially considering three constraints the proposed method can be evaluated as to enlarge the quality as well as the diversity of route information demanded by users.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.27-32
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• 2007

3D based information is demanded increasingly as cities grow three dimensionally and buildings become large and complex. The use of 3D GIS is also getting attention as fundamental data for ubiquitous computing applications such as location-based guidance, path finding and emergency escaping. However, most 3D modeling techniques are focused on the visualization of buildings or terrains and do not have topological structures required in spatial analyses. In this paper, we introduce a method to incorporate topological relationship into 3D models by combining 2D GIS layers and 3D model. We divide indoor spaces of a 3D model into discrete objects and then define the relationship with corresponding features in 2D GIS layers through database records. We also show how to construct hallways network in the 2D-3D integrated building model. Finally, we test different cases of route finding situations inside a building such as normal origin-destination path finding and emergency evacuation.

• 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 Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.177-187
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• 2006

It is known that over one million car navigation devices are being currently used in Korea. Most. if not all, route guidance systems, however, Provide only one "best" route to users, not providing any options for various types of users to select. The current practice dose not consider each individual's different preferences. These days, a vast amount of information became available due to the rapid development in information processing technology. Thus, users Prefer choices to be given and like to select the one that suits him/her the "best" among available information. To provide such options in this Paper, we developed an algorithm that provides alternative routes that may not the "least cost" ones, but ones that are close to the "least cost" routes for users to select. The algorithm developed and introduced in the paper utilizes a link-based search method, rather than the traditional node-based search method. The link-based algorithm can still utilize the existing transportation network without any modifications, and yet enables to provide flexible route guidance to meet the various needs of users by allowing transfer to other modes and/or restricting left turns. The algorithm developed has been applied to a toy network and demonstrated successful implementation of the multi-path search algorithm for multi-purpose activities.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.129-135
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• 2010

This paper suggests a multipath establishing scheme for ad hoc networks. Data paths are established by on-demand manner. Multipath are made as a sequence of route control message exchange at route setup process. Multipath can be used as a backup path or load balancing for data exchange. Proposed scheme uses a one-hop pre-search scheme for establishing multipath between source and destination. When a node selects a next node for route reply, the node finds optimal route by exchanging route information with neighbor nodes. Simulation results show that the proposed multipath scheme has better split characteristics among multipath and higher route survivability at the environment where nodes are moving.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.7-13
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• 2008

This paper suggests a Path-planning algorithm for mobile agents. While there are a lot of studies on the path-planning for mobile agents, mathematical modeling of complex environment which constrained by spatio-temporally is very difficult and it is impossible to obtain the optimal solutions. In this paper, an optimal path-planning algorithm based on the graphic technique is presented. The working environment is divided into two areas, the one is free movable area and the other is not permissible area in which there exist obstacles and spatio-temporally constrained, and an optimal solution is obtained by using a new algorithm which is based on the well known ACO algorithm.