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Optimal Placement of Mobile Sensors for the Distance-Constrained Line Routing Problem Full article

Conference XXIII International Conference Mathematical Optimization Theory and Operations Research
30 Jun - 6 Jul 2024 , Омск
Source Mathematical Optimization Theory and Operations Research: Recent Trends
Compilation, Springer. 2024. 388 c. ISBN 978-3-031-73364-2.
Journal Communications in Computer and Information Science
ISSN: 1865-0929
Output data Year: 2024, Volume: 2239, Pages: 172-184 Pages count : 13 DOI: 10.1007/978-3-031-73365-9_12
Tags Barrier covering · Drones · Limited energy · Optimization
Authors Erzin A 1,2,3 , Shadrina A 2
Affiliations
1 Sobolev Institute of Mathematics, SB RAS, Novosibirsk 630090, Russia
2 Novosibirsk State University, Novosibirsk 630090, Russia
3 St. Petersburg State University, St. Petersburg 199034, Russia

Funding (1)

1 Russian Science Foundation 22-71-10063

Abstract: A line segment (barrier) is specified on the plane, as well as the location of the depots. Each sensor can travel a limited-length path, starting and ending at its depot. The part of the barrier along which the sensor moved is covered by this sensor. It is necessary to determine the number of sensors (drones) in each depot in order to cover the entire barrier using a minimal number of drones (problem MinNum), or to minimize the maximum distance traveled by each drone (problem MinMax), or to minimize the total length of paths traveled by all drones (problem MinSum). Previously, the problem MinNum of covering a barrier using minimal number of drones (one drone in each depot) was considered. In the problem considered in this paper, the solution is the number of drones in each depot, as well as the trajectory of each drone. We propose algorithms for solving the problem for all three criteria mentioned above.
Cite: Erzin A. , Shadrina A.
Optimal Placement of Mobile Sensors for the Distance-Constrained Line Routing Problem
In compilation Mathematical Optimization Theory and Operations Research: Recent Trends. – Springer., 2024. – Т.2239. – C.172-184. – ISBN 978-3-031-73364-2. DOI: 10.1007/978-3-031-73365-9_12 Scopus OpenAlex
Dates:
Published print: Dec 20, 2024
Published online: Dec 20, 2024
Identifiers:
Scopus: 2-s2.0-85214278891
OpenAlex: W4405597993
Citing: Пока нет цитирований
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