TY - GEN
T1 - Improved Mixed Discrete Particle Swarms based Multi-Task Assignment for UAVs
AU - Jia, Zhenshuai
AU - Xiao, Bing
AU - Qian, Hanyu
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Aiming at the problem of multi-Task distribution for Unmanned Aerial Vehicle (UAV) swarm, a new type of multi-Task distribution model for UAVs is established in this paper, various constraints are considered, such as bomb load and damage loss. To solve the multi-Task allocation problem, an improved mixed discrete particle swarm optimization algorithm (IM-DPSO) is proposed, a two-dimensional particle coding matrix with task priority is designed, the genetic variation rules with particle update strategies are combined, and then the inertia weight and learning factors are optimized to enhance the algorithm's ability of solving the problem. Simulation results show that the improved algorithm can better solve the problem of multi-Task allocation for UAVs under the distribution model.
AB - Aiming at the problem of multi-Task distribution for Unmanned Aerial Vehicle (UAV) swarm, a new type of multi-Task distribution model for UAVs is established in this paper, various constraints are considered, such as bomb load and damage loss. To solve the multi-Task allocation problem, an improved mixed discrete particle swarm optimization algorithm (IM-DPSO) is proposed, a two-dimensional particle coding matrix with task priority is designed, the genetic variation rules with particle update strategies are combined, and then the inertia weight and learning factors are optimized to enhance the algorithm's ability of solving the problem. Simulation results show that the improved algorithm can better solve the problem of multi-Task allocation for UAVs under the distribution model.
KW - Discrete Particle Swarm Optimization (DPSO)
KW - Multi-Task Assignment
KW - Unmanned Aerial Vehicle
UR - http://www.scopus.com/inward/record.url?scp=85165997452&partnerID=8YFLogxK
U2 - 10.1109/DDCLS58216.2023.10166130
DO - 10.1109/DDCLS58216.2023.10166130
M3 - 会议稿件
AN - SCOPUS:85165997452
T3 - Proceedings of 2023 IEEE 12th Data Driven Control and Learning Systems Conference, DDCLS 2023
SP - 442
EP - 448
BT - Proceedings of 2023 IEEE 12th Data Driven Control and Learning Systems Conference, DDCLS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2023
Y2 - 12 May 2023 through 14 May 2023
ER -