• Korean Management Science Review
• /
• v.19 no.1
• /
• pp.55-66
• /
• 2002

Given a directed network, a designated arc, and lowers and upper bounds for the distance of each arc, the preprocessing shortest path problem Is a decision problem that decides whether there is some choice of distance vector such that the distance of each arc honors the given lower and upper bound restriction, and such that the designated arc is on some shortest path from a source node to a destination notre with respect to the chosen distance vector. The preprocessing shortest path problem has many real world applications such as communication and transportation network management and the problem is known to be NP-complete. In this paper, we develop an algorithm that solves the problem using the structural properties of shortest paths.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.18 no.33
• /
• pp.29-37
• /
• 1995

An Automated Storage/Retrieval Systems(AS/RS) has been gradually emphasized because of the change of production and distribution environment. This paper develops algorithm and Shortest Distance Model that can reduce the traveling time of a stacker crane for efficient operation of AS/RS. In order to reduce the traveling time of a stacker crane, we determine the order processing and then the sequencing of storage/retrieval for each item. Order processing is determined based on the SPT(Shortest Processing Time) concept considering a criterion of retrieval coordinate. The sequencing of storage/retrieval is determined based on the Shortest Distance Model by using a modified SPP(Shortest Path Problem) of network problem. A numerical example is provided to illustrate the developed algorithm and Shortest Distance Model.

• Journal of Korean Society of Transportation
• /
• v.23 no.7 s.85
• /
• pp.149-158
• /
• 2005

The object of this paper is to develop the shortest path algorithm. The existing shortest path algorithm models are developed while considering travel time and travel distance. A few problems occur in these shortest path algorithm models, which have paid no regard to cognition of users, such as when user who doesn't have complete information about the trip meets a strange road or when the route searched from the shortest path algorithm model is not commonly used by users in real network. This paper develops a shortest path algorithm model to provide ideal route that many people actually prefer. In order to provide the ideal shortest path with the consideration of travel time, travel distance and road cognition, travel time is predicted by using Kalman filtering and travel distance is predicted by using GIS attributions. The road cognition is considered by using space data of GIS. Optimal routes provided from this paper are shortest distance path, shortest time path, shortest path considering distance and cognition and shortest path considering time and cognition.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.1
• /
• pp.105-114
• /
• 2009

Recently, location-based services which provides k nearest POIs, e.g., gas stations, restaurants and banks, are essential such applications as telematics, ITS(Intelligent Transport Systems) and kiosk. For this, the Voronoi Diagram k-NN(Nearest Neighbor) search algorithm has been proposed. It retrieves k-NNs by using a file storing pre-computed network distances of POIs in Voronoi diagram. However, this algorithm causes the cost problem when expanding a Voronoi diagram. Therefore, in this paper, we propose an algorithm which generates a matrix of the shortest distance between border points of a Voronoi diagram. The shortest distance is measured each border point to all of the rest border points of a Voronoi Diagram. To retrieve desired k nearest POIs, we also propose a k-NN search algorithm using the matrix of the shortest distance. The proposed algorithms can m inim ize the cost of expanding the Voronoi diagram by accessing the pre-computed matrix of the shortest distances between border points. In addition, we show that the proposed algorithm has better performance in terms of retrieval time, compared with existing works.

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

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2002.05a
• /
• pp.8-14
• /
• 2002

This article presents a new algorithm for the K Shortest Paths Problem which develops initial K shortest paths, and repeal to expose hidden shortest paths with dual approach and to replace the longest path in the present K paths. The initial solution which comprises K shortest paths among shortest paths to traverse each arc is made from bidirectional Dijkstra algorithm. When a crossing node that have two or more inward arcs is found at least three time by turns in this K shortest paths, one inward arc of this crossing node, which has minimum detouring distance, is chosen, and a new path is exposed with joining a detouring subpath from source to this inward arc and a spur of a feasible path from this crossing node to sink. This algorithm, requires worst case time complexity of $O(Kn^2),\;and\;O(n^2)$ in the case $K{\leq}3$.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.26 no.3
• /
• pp.79-94
• /
• 2001

This paper presents a new algorithm for the K shortest paths Problem which develops initial K shortest paths, and repeat to expose hidden shortest paths with dual approach and to replace the longest path in the present K paths. The initial solution comprises K shortest paths among shortest paths to traverse each arc in a Double Shortest Arborescence which is made from bidirectional Dijkstra algorithm. When a crossing node that have two or more inward arcs is found at least three time by turns in this K shortest paths, there may be some hidden paths which are shorter than present k-th path. To expose a hidden shortest path, one inward arc of this crossing node is chose by means of minimum detouring distance calculated with dual variables, and then the hidden shortest path is exposed with joining a detouring subpath from source to this inward arc and a spur of a feasible path from this crossing node to sink. If this exposed path is shorter than the k-th path, the exposed path replaces the k-th path. This algorithm requires worst case time complexity of O(Kn$^2$), and O(n$^2$) in the case k$\leq$3.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.4
• /
• pp.131-140
• /
• 2012

The shortest path search algorithm of navigation is generally based on Dijkstra algorithm and considers only the distance using the weight. Dijkstra algorithm based on the distance mainly ought to perform the 'number of nodes 1' and requires a lot of memory, for it is to start from the starting node and to decide the shortest path for all the nodes. Also, it searches only the same identical path in case of any bottleneck due to an accident nearby, since it is based only on the distance, and hence does not have a system that searches the detour road. In order to solve this problem, this paper considers only the travelling time per road (travelling speed * distance), without applying speed criteria (smoothness, slow speed, stagnation and accident control) or road class (express road, national road and provincial road). This provides an advantage of searching the detour, considering the reality that there are differences in time take for the car to travel on different roads with same distance, due to any accident, stagnation, or repair construction. The suggested algorithm proves that it can help us to reach the destination within the shortest time, making a detour from any congested road (outbreak) on providing an information on traveling time continuously(real-time) even though there is an accident in a particular road.

• Journal of Digital Contents Society
• /
• v.13 no.3
• /
• pp.451-457
• /
• 2012

Recently, as the use of real time traffic information of a car navigation system increases rapidly with the development of Intelligent Transportation Systems (ITS), path search is getting more important. Previous algorithms, however, are mostly for the shortest distance searching and provide route information using static distance and time information. Thus they could not provide the most optimal route at the moment which changes dynamically according to traffic. Accordingly, in this study, Semantic Shortest Path algorithm with Reduction ratio & Distance(SSP_RD) is proposed to solve this problem. Additionally, a routing model based on velocity reduction ratio and distance and a dynamic route link map are proposed.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.8
• /
• pp.74-84
• /
• 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.