• 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.

• 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.

• 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 the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.195-201
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• 2010

Recently, the necessity of the autonomous mobile robot is emphasized in order to enlarge the scope of activity and actively cope with the change of work environment. This paper proposes the algorithm which enables the mobile robot to avoid obstacles and lead it to the destination by the shortest path. And we verify the usability by a simulation. We made the algorithm with micro-GA and $\lambda$-geometry MRA. The area of simulation is limited to 320(width)$\times$200(length) pixels and one pixel is one centimeter. When we planned the path with only $\lambda$-geometry MRA, we could find the direction for path planning but could not find the shortest path. But when we planned the path with $\lambda$-geometry MRA and micro-GA, we could find the shortest path. So the algorithm enables us to find the direction for path planning and the shortest path.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.79-93
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• 2009

For developing the location based service which is individualized and specialized according to the characteristic of the users, the spatio-temporal pattern mining for extracting the meaningful and useful patterns among the various patterns of the mobile object on the spatio-temporal area is needed. Thus, in this paper, as the practical application toward the development of the location based service in which it is able to apply to the real life through the pattern mining from the huge historical data of mobile object, we are proposed STOMP(using Frequency of sequence and Weight) that is the new mining method for extracting the patterns with spatial and temporal constraint based on the problems of mining the optimal moving pattern which are defined in STOMP(F)[25]. Proposed method is the pattern mining method compositively using weighted value(weights) (a distance, the time, a cost, and etc) for our previous research(STOMP(F)[25]) that it uses only the pattern frequent occurrence. As to, it is the method determining the moving pattern in which the pattern frequent occurrence is above special threshold and the weight is most a little bit required among moving patterns of the object as the optimal path. And also, it can search the optimal path more accurate and faster than existing methods($A^*$, Dijkstra algorithm) or with only using pattern frequent occurrence due to less accesses to nodes by using the heuristic moving history.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.19-27
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• 2007

We have implemented a WWW homepage which finds an optimal route for users. There already exist many web sites which provide the optimal route when a start and a destination cities are given. However, none of them can find the optimal route when a number of cities to be visited. The problem of finding the optimal route starting at a given start city and visiting through all the given intermediate cities and finally returning to the start city is called Travelling Sales Person(TSP) problem. TSP is a well known exponential time complexity problem. We have implemented an artificial intelligent search algorithm for TSP on our homepage. The main feature of our algorithm is that the destination may not be the same as the start city whereas all of the existing heuristic algorithms for TSP assume that the start and the destination cities are the same. The web page asks a user to select all the cities he or she wants to visit(including start and destination city), then it finds a sequence of the cities such that the user would travel minimum distance if he or she visits the cities in the order of the sequence. This paper presents algorithms used in the homepage.

• Journal of Korea Multimedia Society
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• v.7 no.10
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• pp.1421-1435
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• 2004

When various work was given from user, the existing mobile agent model migrated from node to node and process the work at the point that much traffics according to passive routing schedule are happened, until it makes service the work result, time cost of round work process for the distributed nodes are increased. Therefore, the existing agent systems need migration method to solve the problems of agent size increment or a lack of interoperability among agent systems. To solve these problems in this thesis, we design and implement an CORBA-based Mobile Agent Model(CMAM) for the efficient work process into the distributed nodes, when the mobile agents are migrated among the nodes, using an optimal path search by sensing of network traffic.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.17-24
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• 2020

The traveling salesman problem is an algorithmic problem tasked with finding the shortest route that a salesman visits, visiting each city and returning to the started city. Due to the exponential time complexity of TSP, it's hard to implement on cases like amusement park or delivery. Also, TSP is hard to meet user's demand that is associated with multi-dimensional attributes like travel time, interests, waiting time because it uses only one attribute - distance between nodes. This paper proposed Top-n Skyline-Multi Dimension TSP to resolve formerly adverted problems. The proposed algorithm finds the shortest route faster than the existing method by decreasing the number of operations, selecting multi-dimensional nodes according to the dominance of skyline. In the simulation, we compared computation time of dynamic programming algorithm to the proposed a TS-MDT algorithm, and it showed that TS-MDT was faster than dynamic programming algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.351-356
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• 2022

Among the path planning methods used to generate the ship's path, the graph search-based method is widely used because it has the advantage of its completeness, optimality. In order to apply the graph-based search method to the berthing path plan, the deviation from the path must be minimized. Path following suitability should be considered essential, since path deviation during berthing can lead to collisions with berthing facilities. However, existing studies of graph search-based berthing path planning are dangerous for application to real-world navigation environments because they produce results with a course change just before berthing. Therefore, in this paper, we develop a cost function suitable for path following, and propose a 3D A* algorithm that applies it. In addition, in order to evaluate the suitability for the actual operating environment, the results of the path generation of the algorithm are compared with the trajectory of the data collected by manned operations.