• 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 Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.2
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• pp.12-21
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• 2013

This study developed searching network reduction algorithm for reduce shortest path searching time. Developed algorithm is searching nodes that have the including possibility of less weights path than temporal path that consists minimum number of nodes and minimum sum of the straight line distances. The node that has the including possibility of shortest path is the node that the sum of straight line distance from start node and straight line distance to target node is less than the value that temporary path's weights divided by minimum weights units. If searching network reconstitutes only these nodes, the time of shortest path searching will be reduced. This developed algorithm has much effectiveness that start node and target node is close in large network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.939-955
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• 2010

With the progress of IT and mobile positioning technologies, various types of location-based services (LBS) have been proposed and implemented. Finding a shortest path between two nodes is one of the most fundamental tasks in many LBS related applications. So far, there have been many research efforts on the shortest path finding problem. For instance, $A^*$ algorithm estimates neighboring nodes using a heuristic function and selects minimum cost node as the closest one to the destination. Pruning method, which is known to outperform the A* algorithm, improves its routing performance by avoiding unnecessary exploration in the search space. For pruning, shortest paths for all node pairs in a map need to be pre-computed, from which a shortest path container is generated for each edge. The container for an edge consists of all the destination nodes whose shortest path passes through the edge and possibly some unnecessary nodes. These containers are used during routing to prune unnecessary node visits. However, this method shows poor performance as the number of unnecessary nodes included in the container increases. In this paper, we focus on this problem and propose a new border line-based pruning scheme for path routing which can reduce the number of unnecessary node visits significantly. Through extensive experiments on randomly-generated, various complexity of maps, we empirically find out optimal number of border lines for clipping containers and compare its performance with other methods.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.337-340
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• 1999

At each iteration, the path is either extended by adding a new node, or contracted by deleting its terminal node. When the destination becomes the terminal node of the path, the algorithm terminate. In the process of finding the shortest path to given destination, the algorithm visits other node, there by obtaining a shortest path from the origin to them. We show here that when the auction algorithm is applied to this equivalent program with some special rules for choosing the initial object prices and the person submitting a bid at each iteration, one obtains the generic form of the $\varepsilon$-relaxation method. Thus, the two methods are mathematically equivalent

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.491-498
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• 1997

Geographic Infprmation System(GIS)is being apply to extended from specified ppkication to general purpose deu to the omprovement of computing power.As one part of postal Integarated Information Servies, Postalroute Optimication system(PROS) is comprsed of the composed of the shortest pathe genrator for providing fast and shortest route of postal delivery, the ischronal area generator, the boudary relacation generator, GIS engine, road map, and rdelational database , etc.This paper is related to creation algorithm of the shortest path generation (SPAWD;Shortest Path Algorithm With Direction)from PEOS model.To differ from the exsting shortest path generating methods, this paper suggests SPAWD alforithm for searching destinations of fast time between start and destination points with dirdstion.It comapares and analyzes the new algorithm with existion algorithms, and suggests directions of future studies.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.298-306
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• 2013

Nowadays, a transporter manager plans the schedule of the block transportation by considering the experience of the manager, the production process of the blocks and the priority of the block transportation in shipyard. The schedule planning of the block transportation should be rearranged for the reflection of the path blocking cases occurred by unexpected obstacles or delays in transportation. In this paper, the optimal block transportation path planning system is developed for rearranging the schedule of the block transportation by considering the damaged path. $A^*$ algorithm is applied to calculate the new shortest path between the departure and arrival of the blocks transported through the damaged path. In this algorithm, the first node of the damaged path is considered as the starting position of the new shortest path, and then the shortest path calculation is completed if the new shortest path is connected to the one of nodes in the original path. In addition, the data structure for the algorithm is designed. This optimal block transportation path planning system is applied to the Philippine Subic shipyard and the ability of the rapid path modification is verified.

• 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 the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.425-433
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• 2012

Dijkstra's algorithm is one of well-known methods to find shortest paths over a network. However, more research on $A^*$ algorithm is necessary to discover the shortest route to a goal point with the heuristic information rather than Dijkstra's algorithm which aims to find a path considering only the shortest distance to any point for an optimal path search. Therefore, in this paper, we compared Dijkstra's algorithm and $A^*$ algorithm for bicycle route selection. For this purpose, the horizontal distance according to slope angle and average speed were calculated based on factors which influence bicycle route selection. And bicycle routes were selected considering the shortest distance or time-dependent shortest path using Dijkstra's or $A^*$ algorithm. The result indicated that the $A^*$ algorithm performs faster than Dijkstra's algorithm on processing time in large study areas. For the future, optimal path selection algorithm can be used for bicycle route plan or a real-time mobile services.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.17-26
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• 1998

Shortest path problem in road network with turn penalties and prohibitions frequently arises from various transportation optimization models. In this paper, we propose a new algorithm for the shortest Path problem with turn prohibitions and delays. The proposed algorithm maintains distance labels of arcs, which is similar to labels of nodes of Dijkstra's algorithm. Fibonacci heap implementation of the proposed algorithm solves the problem in O(mn ＋ mlogm). We provide a new insight in transforming network with turn penalties and prohibitions into another network in which turn penalties and prohibitions are implicitly considered. The proposed algorithm is implemented using new data structure and compared with Ziliaskopoulos' algorithm. Computational results show that the proposed algorithm is very efficient.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.27-28
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• 2010

Finding shortest path technique running time differs depending on applying of the algorithm and data, and also used a lot of difference in effectiveness depending on the environment occurs. Therefore, the algorithm and environment based on this study, the relationship between optimal solutions and compare running time.