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CVRPTW Model for Cargo Collection with Heterogeneous Capacity-Fleet

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Applied Informatics (ICAI 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1051))

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Abstract

This work shows the application of the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) to collect different cargo-demand in several locations with low time disponibility to attend any vehicle. The objective of the model is to reduce the routing time in a problem with mixed vehicle-fleet. The initial step is the creation of a distance matrix by using the Google Maps API, then cargo capacities for every vehicle and time-windows for every demand point are included in the model. The problem is solved with Google-OR tools using as firt solution aproximated algoritm and as second solution one metaheuristic algorithm for local search.

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Author information

Authors and Affiliations

  1. Universidad de Bogotá Jorge Tadeo Lozano, Bogotá, Colombia

    Jorge Ivan Romero-Gelvez, William Camilo Gonzales-Cogua & Jorge Aurelio Herrera-Cuartas

Authors
  1. Jorge Ivan Romero-Gelvez
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  2. William Camilo Gonzales-Cogua
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  3. Jorge Aurelio Herrera-Cuartas
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Corresponding author

Correspondence to Jorge Ivan Romero-Gelvez .

Editor information

Editors and Affiliations

  1. Universidad Distrital Francisco Jose de Caldas, Bogota, Colombia

    Hector Florez

  2. Universidad Nacional de Loja, Loja, Ecuador

    Marcelo Leon

  3. Universidad a Distancia de Madrid, Madrid, Spain

    Jose Maria Diaz-Nafria

  4. Universidad Complutense de Madrid, Madrid, Spain

    Simone Belli

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Romero-Gelvez, J.I., Gonzales-Cogua, W.C., Herrera-Cuartas, J.A. (2019). CVRPTW Model for Cargo Collection with Heterogeneous Capacity-Fleet. In: Florez, H., Leon, M., Diaz-Nafria, J., Belli, S. (eds) Applied Informatics. ICAI 2019. Communications in Computer and Information Science, vol 1051. Springer, Cham. https://doi.org/10.1007/978-3-030-32475-9_13

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  • DOI: https://doi.org/10.1007/978-3-030-32475-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32474-2

  • Online ISBN: 978-3-030-32475-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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