• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11B
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• pp.972-984
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• 2003

In this paper, new on-line routing algorithms with a bandwidth constraint are proposed. The proposed algorithms may be used for a dynamic LSP setup in MPLS network. We extend the WSP algorithm, the SWP algorithm and a utilization-based routing algorithm into the proposed algorithms by slightly modified K-shortest loopless path algorithms. The performances such as accepted bandwidth, accepted request number and average path length of the proposed and the previous algorithms are evaluated through extensive simulations. All simulations are conducted under the condition that any node can be an ingress or egress node for a LSP setup. The simulation results show that the proposed algorithms have the good performances in most cases in comparison to the previous algorithms. Under the heavy load condition, the algorithms based on the minimum hop path perform better than any other algorithms.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.1-23
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• 2005

The shortest-paths problem is a fundamental problem in graph theory and finds diverse applications in various fields. This is why shortest path algorithms have been designed more thoroughly than any other algorithm in graph theory. A large number of optimization problems are mathematically equivalent to the problem of finding shortest paths in a graph. The shortest-path between a pair of vertices is defined as the path with shortest length between the pair of vertices. The shortest path from one vertex to another often gives the best way to route a message between the vertices. This paper presents an $O(n^2)$ time sequential algorithm and an $O(n^2/p+logn)$ time parallel algorithm on EREW PRAM model for solving all pairs shortest paths problem on circular-arc graphs, where p and n represent respectively the number of processors and the number of vertices of the circular-arc graph.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.179-188
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• 2001

We analyze the property of candidate node set in the network graph, and propose an algorithm to decrease shortest path-finding computation time by using multiple dynamic-range queue(MDRQ) structure. This MDRQ structure is newly created for effective management of the candidate node set. The MDRQ algorithm is the shortest path-finding algorithm that varies range and size of queue to be used in managing candidate node set, in considering the properties that distribution of candidate node set is constant and size of candidate node set rapidly change. This algorithm belongs to label-correcting algorithm class. Nevertheless, because re-entering of candidate node can be decreased, the shortest path-finding computation time is noticeably decreased. Through the experiment, the MDRQ algorithm is same or superior to the other label-correcting algorithms in the graph which re-entering of candidate node didn’t frequently happened. Moreover the MDRQ algorithm is superior to the other label-correcting algorithms and is about 20 percent superior to the other label-setting algorithms in the graph which re-entering of candidate node frequently happened.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.649-659
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• 2017

Typically, a smart car is equipped with access to the Internet and a wireless local area network. Moreover, a smart car is equipped with a global positioning system (GPS) based navigation system that presents a map to a user for recommending the shortest path to a desired destination. This paper presents the design and implementation of a real-time shortest path search system for directed and dynamic roads. Herein, we attempt to simulate real-world road environments, while considering changes in the ratio of directed roads and in road conditions, such as traffic accidents and congestions. Further, we analyze the effect of the ratio of directed roads and road conditions on the communication cost between the server and vehicles and the arrival times of vehicles. In this study, we compare and analyze distance-based shortest path algorithms and driving time-based shortest path algorithms while varying the number of vehicles to search for the shortest path, road conditions, and ratio of directed roads.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.2
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• pp.47-58
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• 2001

The purpose of this study is to present methods for determining the k most vital arcs (k-MVAs) in shortest path problem (SPP) using evolutionary algorithms. The problem of finding the k-MVAs in SPP is to find a set of k arcs whose simultaneous removal from the network causes the greatest increase in the shortest distance between two specified nodes. Generally, the problem of determining the k-MVAs in SPP has been known as NP-hard. Therefore, to deal with problems of the real world, heuristic algorithms are needed. In this study we present three kinds of evolutionary algorithms for finding the k-MVAs in SPP, and then to evaluate the performance of proposed algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.38-45
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• 2012

Finding shortest paths on time dependent networks is an important task for scheduling and routing plan and real-time navigation system in ITS. In this research, one-to-one time dependent shortest path algorithms based on link flow speeds on urban networks are proposed. For this work, first we select three general shortest path algorithms such as Graph growth algorithm with two queues, Dijkstra's algorithm with approximate buckets and Dijkstra's algorithm with double buckets. These algorithms were developed to compute shortest distance paths from one node to all nodes in a network and have proven to be fast and efficient algorithms in real networks. These algorithms are extended to compute a time dependent shortest path from an origin node to a destination node in real urban networks. Three extended algorithms are implemented on a data set from real urban networks to test and evaluate three algorithms. A data set consists of 4 urban street networks for Anaheim, CA, Baltimore, MD, Chicago, IL, and Philadelphia, PA. Based on the computational results, among the three algorithms for TDSP, the extended Dijkstra's algorithm with double buckets is recommended to solve one-to-one time dependent shortest path for urban street networks.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1327-1332
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• 2018

An AGV(Automated Guided Vehicle) where is running on production automated system is related efficiency of production system similarly. On previous study proposed a path collision avoidance algorithms using shortest path of AGV. Running time about loading and unloading with shortest path of AGV is important factor to decide the production system efficiency. In this paper, we propose a method of shortest path and shortest time. Also propose the decision making method of collision avoidance position for setup a shortest runway for next command. To do verify the proposed method consist a simulation for AGV. Finally, we compare and analyse the proposed system between the existing system and show that our system can effectively the performance.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.121-131
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• 2004

The K-shortest path algorithms are largely classified into two groups: oneis for finding loopless path (simple path), another loop paths. In terms of cimputational complexities, in general the loop-paths-finding ones are considered more efficient and easier to be handled than the loopless-paths-finding. The entire path deletion methods have been known as the best efficient algorithms among the proposed K-shortest path algorithms. These algorithms exploit the K-th network transformation to prevent the same path, which was already selected as the (K-1)th path, from being redetected. Nevertheless, these algorithms have a critical limitationto be applied in the practical traffic networks because the loops, in which the same modes and links can be unlimitedly repeated, are not preventable. This research develops a way to be able to selectively control loop-paths by applying link-label. This research takes an advantage of the link-based shortest path algorithms that since the algorithms can take care of two links simultaneouslyin the searching process, the generation of loops can be controlled in the concatenation process of the searched link and the preceded link. In concatenation of two links, since the precede link can be treated a sub-shortest to this link from the origination, whether both the node and the link of the searched link were already existed or not can be evaluated. Terefore, both the node-loopless path, in which the same node is not appeared, and the link-loopless, in which the same link is not appeared, can be separately controlled. Especially, the concept of the link-loopless path is expended to take into consideration reasonable route choice behaviors such as U-Turn, P-Turn, and Turn-Penalty, which are frequently witnessed in urban traffic network with intersections. The applicability of the proposed method is verified through case studies.

• Journal of the military operations research society of Korea
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• v.17 no.2
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• pp.72-89
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• 1991

In transportation network problems, it is often desirable to select multiple number of the shortect paths. On problems of finding these paths, algorithms have been developed to choose single shortest path, k-shortest paths and k-shortest paths via p-specified nodes in a network. These problems consider the time as the main factor. In wartime, we must consider availability as well as time to determine the shortest transportation path, since we must take into account enemy's threat. Therefore, this paper addresses the problem of finding the shortest transportation path considering both time and availability. To accomplish the objective of this study, values of k-shortest paths are computed using the algorithm for finding the k-shortest paths. Then availabilties of those paths are computed through simulation considering factors such as rates of suffering attack, damage and repair rates of the paths. An optimal path is selected using any one of the four decision rules that combine the value and availability of a path.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.43-54
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• 1996

This paper presents new heuristic search algorithms for searching rectilinear r(L1), link metric, and combined shortest paths in the presence of orthogonal obstacles. The GMD(GuidedMinimum Detour) algorithm combines the best features of maze-running algorithms and line-search algorithms. The SGMD(Line-by-Line GuidedMinimum Detour)algorithm is a modiffication of the GMD algorithm that improves efficiency using line-by-line extensions. Our GMD and LGMD algorithms always find a rectilinear shortest path using the guided A search method without constructing a connection graph that contains a shortest path. The GMD and the LGMD algorithms can be implemented in O(m＋eloge＋NlogN) and O(eloge＋NlogN) time, respectively, and O(e＋N) space, where m is the total number of searched nodes, is the number of boundary sides of obstacles, and N is the total number of searched line segment. Based on the LGMD algorithm, we consider not only the problems of finding a link metric shortest path in terms of the number of bends, but also the combined L1 metric and Link Metric shortest path in terms of the length and the number of bands.