Abstract
The use of Geographic Information Systems has increased considerably since the eighties and nineties. As one of their most demanding applications we can mention shortest paths search. Several studies about shortest path search show the feasibility of using graphs for this purpose. Dijkstra’s algorithm is one of the classic shortest path search algorithms. This algorithm is not well suited for shortest path search in large graphs. This is the reason why various modifications to Dijkstra’s algorithm have been proposed by several authors using heuristics to reduce the run time of shortest path search. One of the most used heuristic algorithms is the A* algorithm, the main goal is to reduce the run time by reducing the search space. This article proposes a modification of Dijkstra’s shortest path search algorithm in reduced graphs. It shows that the cost of the path found in this work, is equal to the cost of the path found using Dijkstra’s algorithm in the original graph. The results of finding the shortest path, applying the proposed algorithm, Dijkstra’s algorithm and A* algorithm, are compared. This comparison shows that, by applying the approach proposed, it is possible to obtain the optimal path in a similar or even in less time than when using heuristic algorithms.
Highlights
From a practical point of view, a Geographic Information System (GIS) is a computer system capable of handling georeferenced data
A GIS should facilitate the relationship between socio-economic data and geographic data, this can be achieved through the generation of thematic maps (Jiang et al 2010), a service for generating this kind of maps is described by (RodríguezTorres and Rodríguez-Puente 2010)
As is impractical to obtain an optimal heuristics for this purpose, we can state that the proposal obtains a response in a lower run time t√han Dijkstra and A* algorithm if a condition n1 = |Vr| ≤ (n) is satisfied
Summary
From a practical point of view, a Geographic Information System (GIS) is a computer system capable of handling georeferenced data. These kinds of data refer to information associated with geographic coordinates (longitude, latitude). The relevance of a GIS is closely related to the ability of building models or representations coming from the real world. This kind of system is very important because it facilitates the decision-making process and has a high social impact. Among the most demanded features in GIS we can mention those related to the analysis of routes, some examples are as follows:
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