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A UAV location and routing problem with spatio-temporal synchronization constraints solved by ant colony optimization

Author

Listed:
  • Oktay Yılmaz

    (National Defense University)

  • Ertan Yakıcı

    (National Defense University)

  • Mumtaz Karatas

    (National Defense University
    Bahcesehir University)

Abstract

In this study, we introduce an optimization problem which attempts to optimize location and routing of a homogeneous unmanned aerial vehicle fleet. The problem also allocates the available capacity to the potential locations while it sustains the feasibility defined by synchronization constraints which include time windows at visited points, capacity monitoring in the stations and a limited number of multiple sorties. A mixed integer linear programming formulation for the problem is given and a heuristic method based on ant colony optimization approach is suggested. The suggested heuristic is compared to a commercial solver, a greedy heuristic and a simpler version of the suggested heuristic. We have observed that the suggested heuristic provides the best solutions, while the commercial solver is able to produce only poor solutions in longer time periods. The learning component, which is the main difference between the suggested heuristic and its simplified version, makes a significant change. The results of the experiments strongly suggest the usage of our metaheuristic method for the introduced problem.

Suggested Citation

  • Oktay Yılmaz & Ertan Yakıcı & Mumtaz Karatas, 2019. "A UAV location and routing problem with spatio-temporal synchronization constraints solved by ant colony optimization," Journal of Heuristics, Springer, vol. 25(4), pages 673-701, October.
    • Handle: RePEc:spr:joheur:v:25:y:2019:i:4:d:10.1007_s10732-018-9389-6
    DOI: 10.1007/s10732-018-9389-6
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    References listed on IDEAS

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    1. Bijun Wang & Zheyong Bian & Mo Mansouri, 2023. "Self-adaptive heuristic algorithms for the dynamic and stochastic orienteering problem in autonomous transportation system," Journal of Heuristics, Springer, vol. 29(1), pages 77-137, February.

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