• Korean Management Science Review
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• v.19 no.1
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• pp.55-66
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• 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 the Korea Society of Computer and Information
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• v.26 no.3
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• pp.111-117
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• 2021

The delivery problem on a graph is that of minimizing the object delivery time from one vertex to another vertex on a graph with m vertices using n various speed robot agents. In this paper, we propose two optimal solution algorithms for the delivery problem on a graph with time complexity of O(㎥n) and O(㎥). After preprocessing to obtain the shortest path for all pairs of the graph, our algorithm processed by obtaining the shortest delivery path in the order of the vertices with the least delivery time. Assuming that the graph reflects the terrain on which to solve the problem, our O(㎥) algorithm actually has a time complexity of O(㎡n) as only one preprocessing is required for the various deployment of n robot agents.

• Journal of IKEEE
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• v.11 no.4
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• pp.348-357
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• 2007

Due to the improved performance and cost of personal mobile devices and rapid progress of wireless communication technology, the number of users who utilize these devices is increasing. This trend requires various types of services be available to users. So far, there have been many solutions provided for the shortest path problem. But, technologies which can offer various recommendation services to user depending on user’s current location are focused on Euclidean spaces rather than road network. Thus, in this paper, we extend the previous work to satisfy this requirement on road network database. Our proposed scheme requires pre-computation for the efficient query processing. In the preprocessing step, we first partition the input road network into a fixed number of Voronoi polygons and then pre-compute routing information for each polygon. In the meantime, we select the number of Voronoi polygons in proposition to the scale of road network. Through this selection, the required size of pre-computation is linearly increasing to the size of road network. Using this pre-computated information, we can process queries more quickly. Through experiments, we have shown that our proposed scheme can achieve excellent performance in terms of scheduling time and the number of visited nodes.