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A Multi-objective Metaheuristic for a Green UAV Grid Routing Problem

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Variable Neighborhood Search (ICVNS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12010))

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Abstract

This paper deals with Unmanned Aerial Vehicle (UAV) routing in dynamic grid scenarios with limited battery autonomy and multiple charging stations. The problem is inspired by real-world constraints, specially designed for overcoming challenges of a limited vehicle driving range. Recently, these kinds of vehicles have started to be used for delivering and collecting products, requiring experts in several knowledge fields to manage this novel logistics. Inspired by a multi-criteria view of real systems, we consider different objective functions introduced in the literature. A multi-objective variant of Variable Neighborhood Search is considered for finding a set of non-dominated solutions, while respecting the navigation over forbidden areas and also battery capacity. A case of study was developed where one UAV has to attend clients spread throughout a grid representing a map. The drone starts in a given grid point with a given battery charge, where the grid is composed by four different kinds of points: a regular one and three special (prohibited, recharge and client delivery). Any sequence of valid adjacent points forms a route, but since this yields a huge number of combinations, a pre-processing technique is proposed to pre-compute distances in a given dynamic scenario. Computational results demonstrate the performance of different variants of the proposed algorithm.

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Notes

  1. 1.

    The current work considers that the dynamic data is passed as input, so that no changes need to be performed during the search. As instances already consider arbitrary drone initial location and capacity (battery load), a time-dependent variant can be considered as an extension of this work (see Sect. 5).

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Acknowledgment

Vitor N. Coelho would like to thank the Brazilian agency FAPERJ (E-26/202.868/2016). Luiz S. Ochi was supported by FAPERJ and CNPq (301593/2013-2), Igor M. Coelho and Elias L. Marques Jr. by FAPERJ. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) - Finance Code 001.

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Authors and Affiliations

  1. Institute of Computer Science, Universidade Federal Fluminense, Niterói, Brazil

    Elias L. Marques Jr., Vitor N. Coelho & Luiz S. Ochi

  2. Computer Science Department, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil

    Igor M. Coelho

  3. REDEMAT – Rede Temática em Engenharia de Materiais, Universidade Federal de São João del Rey, São João del Rei, Brazil

    Bruno N. Coelho

Authors
  1. Elias L. Marques Jr.
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  2. Vitor N. Coelho
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  3. Igor M. Coelho
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  4. Bruno N. Coelho
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  5. Luiz S. Ochi
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Corresponding authors

Correspondence to Elias L. Marques Jr. , Vitor N. Coelho , Igor M. Coelho , Bruno N. Coelho or Luiz S. Ochi .

Editor information

Editors and Affiliations

  1. Institut National de Statistique et d'Economie Appliquée (INSEA), Rabat, Morocco

    Rachid Benmansour

  2. University of Macedonia, Thessaloniki, Greece

    Angelo Sifaleras

  3. Khalifa University, Abu Dhabi, United Arab Emirates

    Nenad Mladenović

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Marques, E.L., Coelho, V.N., Coelho, I.M., Coelho, B.N., Ochi, L.S. (2020). A Multi-objective Metaheuristic for a Green UAV Grid Routing Problem. In: Benmansour, R., Sifaleras, A., Mladenović, N. (eds) Variable Neighborhood Search. ICVNS 2019. Lecture Notes in Computer Science(), vol 12010. Springer, Cham. https://doi.org/10.1007/978-3-030-44932-2_11

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  • DOI: https://doi.org/10.1007/978-3-030-44932-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-44931-5

  • Online ISBN: 978-3-030-44932-2

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