• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.79-86
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• 2012

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and various such systems have been recently studied. For a successful economic ship routing system, an efficient algorithm is needed to search an optimal geographical path, and most of the previous systems were approaching to that problem through a minimal static-cost path search algorithm based on the Dijkstra algorithm. To apply that kind of search algorithm, the cost of every edge assigned with the estimated fuel consumption should be constant. However, that assumption is not practical at all considering that the actual fuel consumption is determined by the weather condition when the ship will pass the edge. To overcome such a limitation, we propose a new optimal ship routing system based on a minimal dynamic-cost path search algorithm by properly modifying the Dijkstra algorithm. In addition, we propose a method which efficiently reduces the search space by using the $A^*$ algorithm to decrease the running time. We compared our system with the shortest path-based sailing method over ten testing routes and observed that the former reduced the estimated fuel consumption than the latter by 2.36% on average and the maximum 4.82% with little difference of estimated time of arrival.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.234-235
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• 2012

본 논문에서는 개미 집단 최적화(Ant Colony Optimization, ACO) 알고리즘을 적용한 감속률에 따른 동적 상황인식 경로 선정 방법을 제안한다. 최근 ITS(Intelligent Transportation Systems)의 개발과 함께 차량용 내비게이션의 실시간 교통 정보를 이용하는 수요가 급증하면서, 경로탐색의 중요성이 더욱 가속화되고 있다. 현재 차량용 내비게이션은 멀티미디어 및 정보통신 기술의 결합과 함께 다양한 기능 및 정보를 사용자에게 제공하고 있으며, 이러한 경로탐색 알고리즘은 교통시스템, 통신 네트워크, 운송 시스템 등 다양한 분야에 적용되고 있다. 본 논문에서는 감속률에 따른 동적 상황인식 경로 선정 방법을 제안함으로써, 최단 시간 및 최소 비용의 정보를 제공해 줄 뿐만 아니라 교통정체로 인한 사회적 비용 감소의 효과를 가져다 줄 것으로 기대한다.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.77-88
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• 2006

The purpose of this study is to Propose the time dependent K-least time path algorithm applicable to a real-time based operation strategy in multi-modal transportation network. For this purpose, we developed the extended method based on entire path deletion method which was used in the static K-least time path algorithm. This method was applied to time dependent K-least time path algorithm to find k least time paths in order based on both time dependant mode-link travel time and transfer cost In particular, this algorithm find the optimal solution, easily describing transfer behavior, such as walking and waiting for transfer by applying a link-based time dependent label. Finally, we examined the verification and application of the Proposed algorithm through case study.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.39-46
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• 2009

Generally, Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost in case of that there is no way determined by heuristic function or there are 2 way more which have almost same cost. In this paper, we propose an abstract graph for path-finding with dynamic information. The abstract graph is a simple graph as real road network is abstracted. The abstract graph is created by fixed-size cells and real road network. Path-finding with the abstract graph is composed of two step searching, path-finding on the abstract graph and on the real road network. We performed path-finding algorithm with the abstract graph against A* algorithm based on fixed-size cells on road network that consists of 106,254 edges. In result of evaluation of performance, cost of exploring in path-finding with the abstract graph is about 3~30% less than A* algorithm based on fixed-size cells. Quality of path in path-finding with the abstract graph is, However, about 1.5~6.6% more than A* algorithm based on fixed-size cells because edges eliminated are not candidates for path-finding.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.195-201
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• 2007

A minimum terminal path decomposition of a tree is defined as a partition of the tree into edge-disjoint terminal-to-terminal paths that minimizes the weight of the longest path. In this paper, we present an $O({\mid}V{\mid}^2$time algorithm to find a minimum terminal path decomposition of trees. The algorithm reduces the given optimization problem to the binary search using the corresponding decision problem, the problem to decide whether the cost of a minimum terminal path decomposition is at most l. This decision problem is solved by dynamic programing in a single traversal of the tree.