title: Applied routing problem for a fleet of delivery drones using a modified parallel genetic algorithm
metadata.name: dc.contributor.author
metadata.value: Markelova, Anastasia Y.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Allahverdyan, Alexander L.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Martemyanov, Alexey A.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Sokolova, Inga S.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Petrosian, Ovanes L.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Svirkin, Mikhail V.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2022-06-23T14:05:49Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2022-06-23T14:05:49Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2022-03
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Markelova A., Allahverdyan A., Martemyanov A., Sokolova I., Petrosian O., Svirkin M. Applied routing problem for a fleet of delivery drones using a modified parallel genetic algorithm. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2022, vol. 18, iss. 1, pp. 135–148.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/spbu10.2022.111
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/36938
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: More and more experts agree that in the near future, most freight traffic will be carried out
  using automated systems, and of them drone delivery is considered to be the most promising.
  Drone delivery would benefit by independence from the limitations of transport infrastructure
  and road conditions and would ensure cargo delivery with rapid turnaround times, as well as a
  significant reduction of environmental impact. The technical capabilities of unmanned aerial
  vehicles improve year by year, so the task of coordinating drones and effectively planning
  routes is relevant and in great demand. The development of such technologies will help
  reduce transportation costs and improve customer service through faster delivery. This article
  discusses the applied routing problem for a fleet of drones with limited load capacity for the
  delivery of heterogeneous goods with the possibility of loading in multiple warehouses from
  an international optimization competition. The solution includes new approach based on
  a mixed dimensional parallel genetic algorithm (MDPGA) for finding rational routes for
  delivering goods to various customers and an assignment problem to reduce the dimension
  depending on the number of warehouses.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: This work was carried out under the auspices of a grant of the President of the Russian Federation
  for state support of young Russian scientists   candidates of science (project N MK-4674.2021.1.1).
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Applied Mathematics. Computer Science. Control Processes;Volume 18; Issue 1
metadata.lang: -
metadata.name: dc.subject
metadata.value: drone delivery
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: scheduling
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: genetic algorithm
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: vehicle routing problem
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: multidepot
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: multi-trip
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: multi-product
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: split-delivery
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Applied routing problem for a fleet of delivery drones using a modified parallel genetic algorithm
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 135-148.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/36938/1/135-148.pdf
resources.format: Adobe PDF
resources.size: 516,13 kB