Geodesic
Applied routing problem for a fleet of delivery drones using a modified parallel genetic algorithm
Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, Tome 18 (2022) no. 1, pp. 135-148

Voir la notice de l'article provenant de la source Math-Net.Ru

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.
Keywords: drone delivery, scheduling, genetic algorithm, vehicle routing problem, multi-depot, multi-trip, multi-product, split-delivery. 
@article{VSPUI_2022_18_1_a10,
     author = {A. Markelova and A. Allahverdyan and A. Martemyanov and I. Sokolova and O. Petrosian and M. Svirkin},
     title = {Applied routing problem for a fleet of delivery drones using a modified parallel genetic algorithm},
     journal = {Vestnik Sankt-Peterburgskogo universiteta. Prikladna\^a matematika, informatika, processy upravleni\^a},
     pages = {135--148},
     publisher = {mathdoc},
     volume = {18},
     number = {1},
     year = {2022},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/VSPUI_2022_18_1_a10/}
}
TY  - JOUR
AU  - A. Markelova
AU  - A. Allahverdyan
AU  - A. Martemyanov
AU  - I. Sokolova
AU  - O. Petrosian
AU  - M. Svirkin
TI  - Applied routing problem for a fleet of delivery drones using a modified parallel genetic algorithm
JO  - Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ
PY  - 2022
SP  - 135
EP  - 148
VL  - 18
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/VSPUI_2022_18_1_a10/
LA  - en
ID  - VSPUI_2022_18_1_a10
ER  - 
%0 Journal Article
%A A. Markelova
%A A. Allahverdyan
%A A. Martemyanov
%A I. Sokolova
%A O. Petrosian
%A M. Svirkin
%T Applied routing problem for a fleet of delivery drones using a modified parallel genetic algorithm
%J Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ
%D 2022
%P 135-148
%V 18
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/VSPUI_2022_18_1_a10/
%G en
%F VSPUI_2022_18_1_a10
A. Markelova; A. Allahverdyan; A. Martemyanov; I. Sokolova; O. Petrosian; M. Svirkin. Applied routing problem for a fleet of delivery drones using a modified parallel genetic algorithm. Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, Tome 18 (2022) no. 1, pp. 135-148. http://geodesic.mathdoc.fr/item/VSPUI_2022_18_1_a10/