Abstract
Drones routing, also known as unmanned aerial vehicles routing, has become a highly active area of research. However, the healthcare domain did not raise enough attention in comparison with other research domain as parcel delivery, or surveillance, and other domains. In this article, we propose to solve a routing problem with drone to deliver medication, using a parallel genetic algorithm to reach an optimal solution in a reduced time execution. The algorithm aims to find the optimal routes of drones. We consider the problem as a multiple depots vehicle routing problem with drone. The approach is to create clusters of patients, as depots are the centroids. Each cluster is optimized with an instance of the genetic algorithm executed using multiple cores of the processor.
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Ouiss, M., Ettaoufik, A., Marzak, A., Tragha, A. (2022). A Parallel Genetic Algorithm for Solving the Vehicle Routing Problem with Drone Medication Delivery. In: Saeed, F., Al-Hadhrami, T., Mohammed, E., Al-Sarem, M. (eds) Advances on Smart and Soft Computing. Advances in Intelligent Systems and Computing, vol 1399. Springer, Singapore. https://doi.org/10.1007/978-981-16-5559-3_19
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DOI: https://doi.org/10.1007/978-981-16-5559-3_19
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