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Drone Placement for Optimal Barrier Coverage. / Erzin, A. I.; Shadrina, A. V.

In: Journal of Applied and Industrial Mathematics, Vol. 19, No. 2, 06.2025, p. 230-239.

Research output: Contribution to journal › Article › peer-review

Harvard

Erzin, AI & Shadrina, AV 2025, 'Drone Placement for Optimal Barrier Coverage', Journal of Applied and Industrial Mathematics, vol. 19, no. 2, pp. 230-239. https://doi.org/10.1134/S1990478925020036

APA

Erzin, A. I., & Shadrina, A. V. (2025). Drone Placement for Optimal Barrier Coverage. Journal of Applied and Industrial Mathematics, 19(2), 230-239. https://doi.org/10.1134/S1990478925020036

Vancouver

Erzin AI, Shadrina AV. Drone Placement for Optimal Barrier Coverage. Journal of Applied and Industrial Mathematics. 2025 Jun;19(2):230-239. doi: 10.1134/S1990478925020036

Author

Erzin, A. I. ; Shadrina, A. V. / Drone Placement for Optimal Barrier Coverage. In: Journal of Applied and Industrial Mathematics. 2025 ; Vol. 19, No. 2. pp. 230-239.

BibTeX

@article{74746d5be40d47b7b432df6fc0b3561c,
title = "Drone Placement for Optimal Barrier Coverage",
abstract = "A line segment (barrier) is specified on the plane, as well as the location of depots. Eachsensor is able to travel a limited-length path, starting and ending at its depot. The part of thebarrier along which the sensor moves is covered by thissensor. It is necessary to place some number of mobile sensors (drones) in each depot in order tocover the entire barrier with a minimum number of drones (MinNum), or to minimize the total length ofpaths traveled by drones (MinSum),or to minimize the maximum distance traveled by a drone (MinMax). Previously, the authors investigated a similar problem with an unlimited numberof drones and, for its solution, proposed a pseudopolynomial algorithm depending on the length ofthe barrier L. In this paper, a generalized problem with a limited number of drones is consideredand, to construct an optimal solution, we propose an algorithm with the same complexity.However, in the case of an unlimited number of drones, the new algorithm has complexity times less than the previous one.",
keywords = "barrier coverage, limited energy, linear routing, mobile device (drone), optimization",
author = "Erzin, {A. I.} and Shadrina, {A. V.}",
note = "Erzin, A.I., Shadrina, A.V. Drone Placement for Optimal Barrier Coverage. J. Appl. Ind. Math. 19, 230–239 (2025). The study was carried out within the framework of the state contract of the Sobolev Institute of Mathematics, project no. FWNF–2022–0019.",
year = "2025",
month = jun,
doi = "10.1134/S1990478925020036",
language = "English",
volume = "19",
pages = "230--239",
journal = "Journal of Applied and Industrial Mathematics",
issn = "1990-4789",
publisher = "Pleiades Publishing",
number = "2",

}

RIS

TY - JOUR

T1 - Drone Placement for Optimal Barrier Coverage

AU - Erzin, A. I.

AU - Shadrina, A. V.

N1 - Erzin, A.I., Shadrina, A.V. Drone Placement for Optimal Barrier Coverage. J. Appl. Ind. Math. 19, 230–239 (2025). The study was carried out within the framework of the state contract of the Sobolev Institute of Mathematics, project no. FWNF–2022–0019.

PY - 2025/6

Y1 - 2025/6

N2 - A line segment (barrier) is specified on the plane, as well as the location of depots. Eachsensor is able to travel a limited-length path, starting and ending at its depot. The part of thebarrier along which the sensor moves is covered by thissensor. It is necessary to place some number of mobile sensors (drones) in each depot in order tocover the entire barrier with a minimum number of drones (MinNum), or to minimize the total length ofpaths traveled by drones (MinSum),or to minimize the maximum distance traveled by a drone (MinMax). Previously, the authors investigated a similar problem with an unlimited numberof drones and, for its solution, proposed a pseudopolynomial algorithm depending on the length ofthe barrier L. In this paper, a generalized problem with a limited number of drones is consideredand, to construct an optimal solution, we propose an algorithm with the same complexity.However, in the case of an unlimited number of drones, the new algorithm has complexity times less than the previous one.

AB - A line segment (barrier) is specified on the plane, as well as the location of depots. Eachsensor is able to travel a limited-length path, starting and ending at its depot. The part of thebarrier along which the sensor moves is covered by thissensor. It is necessary to place some number of mobile sensors (drones) in each depot in order tocover the entire barrier with a minimum number of drones (MinNum), or to minimize the total length ofpaths traveled by drones (MinSum),or to minimize the maximum distance traveled by a drone (MinMax). Previously, the authors investigated a similar problem with an unlimited numberof drones and, for its solution, proposed a pseudopolynomial algorithm depending on the length ofthe barrier L. In this paper, a generalized problem with a limited number of drones is consideredand, to construct an optimal solution, we propose an algorithm with the same complexity.However, in the case of an unlimited number of drones, the new algorithm has complexity times less than the previous one.

KW - barrier coverage

KW - limited energy

KW - linear routing

KW - mobile device (drone)

KW - optimization

UR - https://www.scopus.com/pages/publications/105035394893

UR - https://www.mendeley.com/catalogue/3871fc39-f8c1-370f-a00b-2d3a422a5eb1/

U2 - 10.1134/S1990478925020036

DO - 10.1134/S1990478925020036

M3 - Article

VL - 19

SP - 230

EP - 239

JO - Journal of Applied and Industrial Mathematics

JF - Journal of Applied and Industrial Mathematics

SN - 1990-4789

IS - 2

ER -

ID: 76212688