• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.181-188
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• 2007

Undirected Rural Postman Problem(URPP) is a problem that finds a shortest tour traversing the given arcs at least once in a given network. The URPP is one of the basic network problems used in solving the various real-world problems. And it is known as NP-Complete. URPP is an arc-oriented problem that the direction of a tour in an arc has to be considered. Hence, In URPP, it is difficult to use the algorithm for Traveling Salesman Problem (TSP), which is a node-oriented problem, directly. This paper proposes the decoding algorithm using graph transformation in the genetic algorithm for URPP. That is, you can find the entire tour traversing without considering the direction of arcs by transforming the arc-oriented graph into the node-oriented graph. This paper compares the performances of the proposed algorithm with an existing algorithm. In the simulation results, the proposed algorithm obtained better than the existing algorithm

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.81-91
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• 2005

The Traveling Salesman Problem(TSP) is one of the NP-complete (None-deterministic Polynomial time complete) route optimization problems. Its calculation time increases very rapidly as the number of nodes does. Therefore, the near optimum solution has been searched by heuristic algorithms rather than the real optimum has. This paper reviews the Ant System Algorithm(ANS), an heuristic algorithm of TSP and its applicability in the parcel delivery service in Korea. ASA, which is an heuristic algorithm of NP-complete has been studied by M. Dorigo in the early 1990. ASA finds the optimum route by the probabilistic method based on the cumulated pheromone on the links by ants. ASA has been known as one of the efficient heuristic algorithms in terms of its calculation time and result. Its applications have been expanded to vehicle routing problems, network management and highway alignment planning. The precise criteria for vehicle routing has not been set up in the parcel delivery service of Korea. Vehicle routing has been determined by the vehicle deriver himself or herself. In this paper the applicability of ASA to the parcel delivery service has been reviewed. When the driver s vehicle routing is assumed to follow the Nearest Neighbor Algorithm (NNA) with 20 nodes (pick-up and drop-off places) in $10Km{\times}10Km$ service area, his or her decision was compared with ASA's one. Also, ASA showed better results than NNA as the number of nodes increases from 10 to 200. If ASA is applied, the transport cost savings could be expected in the parcel delivery service in Korea.

• The Journal of Bigdata
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• v.7 no.2
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• pp.129-137
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• 2022

With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.425-430
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• 2005

Many problems can be formulated in terms nf graphs and thus solved by graph-theoretic algorithms. This paper is concerned with finding paths between nodes over the distributed and overlapped graphs. The proposed method allows multiple agents to cooperate to find paths without merging the distributed graphs. For each graph there is a designated agent which is charged of providing path-finding service for hot graph and initiating the path-finding tasks of which path starts from the graph. The proposed method earlier on constructs an abstract graph so-called viewgraph for the distributed overlapped graphs and thus enables to extract the information about how to guide the path finding over the graphs. The viewgraph is shared by all agents which determine how to coordinate other agents for the purpose of finding paths. Each agent maintains the shortest path information among the nodes which are placed in different overlapped subgraphs of her graph. Once an agent is asked to get a path from a node on her graph to another node on another's graph, she directs other agents to provide the necessary information for finding paths.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.128-133
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• 2022

This paper deals with the graph in which the weights of edges are given the distances between two end vertices on a metric space. In particular, we will study about a path P with n vertices for these graphs. We obtain a new graph $\bar{P}$ by augmenting an edge to P. Then the length of the shortest path between two vertices on $\bar{P}$ is considered and we focus on the maximum of these lengths. This maximum is called the diameter of the graph $\bar{P}$. We wish to find the augmented edge to minimize the diameter of $\bar{P}$. Especially, for an arbitrary real number λ > 0, we should determine whether the diameter of $\bar{P}$ is less than or equal to λ and we propose an O(n)-time algorithm for this problem, which improves on the time complexity O(nlogn) previously known. Using this decision algorithm, for the length D of P, we provide an O(nlogD)-time algorithm to find the minimum of the diameter of $\bar{P}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1215-1223
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• 2014

In multi-hop wireless networks, a message transmission path is set up on demand by a route discovery step, where a shortest path is used in general. The shortest path, however, normally uses the nodes near the center area, which causes a high traffic load in that area and reduces the message transmission reliability. We propose a stable routing protocol considering the remaining energy of nodes. Our protocol uses ETX as a link performance estimator and tries to avoid the nodes with smaller energy. By doing this, we can reduce the route failure probability and packet loss. We have evaluated the performance of the proposed protocol using QualNet and compared with AODV and MRFR protocols. The simulation result shows that our protocol has a similar performance as MRFR in terms of end-to-end message reception ratio, average message delay and delay jitter, but outperforms MRFR in terms of traffic load distribution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.193-205
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• 2011

This paper suggests $p$-facility locations in $m$ candidate locations and $n$ areas in optimal cost side(population${\times}$shortest distance). This problem has been classified by NP-complete because there is not a polynomial time algorithm. In this paper, we suggests reverse-delete method that deletes a candidate facility one by one from $p=m$ until $p=2$. As a result of the proposed algorithm for the $5{\times}5$ and $7{\times}7$, the initial solution is obtained. For the Swain's 55-node network, we obtain the optimal solution through a solution improvement process with $p=4$ and it by using the initial solution with $p=5$.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.556-559
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• 2020

최근 태풍, 지진, 산불, 산사태, 전쟁 등 다양한 재난 상황으로 인한 인명피해와 자금 손실이 꾸준히 발생하고 있고 현재 이를 예방하고 복구하기 위해 많은 인력과 자금이 소요되고 있는 실정이다. 이러한 여러 재난 상황을 미리 감시하고 재난 발생의 빠른 인지 및 대처를 위해 본 논문에서는 인공지능 기반의 재난 드론 시스템을 설계 및 개발하였다. 본 연구에서는 사람이 감시하기 힘든 지역에 여러 대의 재난 드론을 이용하며 딥러닝 기반의 최단 경로 알고리즘을 적용해 각각의 드론이 최적의 경로로 효율적 탐색을 실시한다. 또한 드론의 근본적 문제인 배터리 용량 부족에 대한 문제점을 해결하기 위해 Ant Colony Optimization (ACO) 기술을 이용하여 각 드론의 최적 경로를 결정하게 된다. 제안한 시스템 구현을 위해 여러 재난 상황 중 산불 상황에 적용하였으며 전송된 데이터를 기반으로 산불지도를 만들고, 빔프로젝터를 탑재한 드론이 출동한 소방관에게 산불지도를 시각적으로 보여주었다. 제안한 시스템에서는 여러 대의 드론이 최적 경로 탐색 및 객체인식을 동시에 수행함으로써 빠른 시간 내에 재난 상황을 인지할 수 있다. 본 연구를 바탕으로 재난 드론 인프라를 구축하고 조난자 탐색(바다, 산, 밀림), 드론을 이용한 자체적인 화재진압, 방범 드론 등에 활용할 수 있다.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.1-9
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• 2016

Computational Fluid Dynamics(CFD) is a branch of fluid mechanics that solves partial differential equations which represent fluid flows by a set of algebraic equations using computers. Even though it requires multifarious variables, only selected ones are stored because of the lack of storage capacity. It causes the requirement of secondary variable calculations at analyzing time. In this paper, we suggest an efficient method to estimate optimal calculation paths for secondary variables. First, we suggest a converting technique from a dependency graph to a ordinary directed graph. We also suggest a technique to find the shortest path from any initial variables to target variables. We applied our method to a tool for data analysis and visualization to evaluate the efficiency of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.767-773
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• 2014

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and there have been various systems which have been recently studied. For a successful economic ship routing system, it is needed to properly control an engine power or change a geographical path considering weather forecast. An optimal geographical path is difficult to be determined, though, because it is a minimal dynamic-cost path search problem where the actual fuel consumption is dynamically variable by the weather condition when the ship will pass the area. In this paper, we propose an geographical path-search algorithm based on evolutionary strategy to efficiently search a good quality solution out of tremendous candidate solutions. We tested our approach with the shortest path-based sailing method over seven testing routes and observed that the former reduced the estimated fuel consumption than the latter by 1.82% on average and the maximum 2.49% with little difference of estimated time of arrival. In particular, we observed that our method can find a path to avoid bad weather through a case analysis.