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Optimization of the University Transportation by Contraction Hierarchies Method and Clustering Algorithms

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Hybrid Artificial Intelligent Systems (HAIS 2018)

Abstract

This research work focuses on the study of different models of solution reflected in the literature, which treat the optimization of the routing of vehicles by nodes and the optimal route for the university transport service. With the recent expansion of the facilities of a university institution, the allocation of the routes for the transport of its students, became more complex. As a result, geographic information systems (GIS) tools and operations research methodologies are applied, such as graph theory and vehicular routing problems, to facilitate mobilization and improve the students transport service, as well as optimizing the transfer time and utilization of the available transport units. An optimal route management procedure has been implemented to maximize the level of service of student transport using the K-means clustering algorithm and the method of node contraction hierarchies, with low cost due to the use of free software.

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Correspondence to Leandro L. Lorente-Leyva .

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Herrera-Granda, I.D. et al. (2018). Optimization of the University Transportation by Contraction Hierarchies Method and Clustering Algorithms. In: de Cos Juez, F., et al. Hybrid Artificial Intelligent Systems. HAIS 2018. Lecture Notes in Computer Science(), vol 10870. Springer, Cham. https://doi.org/10.1007/978-3-319-92639-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-92639-1_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92638-4

  • Online ISBN: 978-3-319-92639-1

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