TY - GEN
T1 - Hybrid Algorithm Research Based on Improved Genetic Algorithm and Auction Algorithm for AUVs Task Allocation
AU - Ji, Guanfeng
AU - Zhang, Zhuo
AU - Huang, Guan
AU - Cui, Rongxin
AU - Yan, Weisheng
AU - Zhang, Shouxu
AU - Wang, Yintao
AU - Guo, Xinxin
AU - Sun, Qi
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In Autonomous Underwater Vehicles (AUVs) systems, an effective task allocation is crucial for AUVs to complete tasks cooperatively. To address the problems of low solution efficiency in static task allocation algorithms and poor real-time performance in dynamic task allocation algorithms, we present a hybrid algorithm based on the improved genetic algorithm and the auction algorithm. Specifically, the auction algorithm is applied to solve the initial solution of task allocation, then the improved genetic algorithm is applied to solve the problem on this basis. The hybrid algorithm can effectively improve the solution efficiency of static task allocation. In particular, our presented algorithm can meet the demands of dynamic task allocation. Finally, simulation results confirm the effectiveness of the proposed algorithm.
AB - In Autonomous Underwater Vehicles (AUVs) systems, an effective task allocation is crucial for AUVs to complete tasks cooperatively. To address the problems of low solution efficiency in static task allocation algorithms and poor real-time performance in dynamic task allocation algorithms, we present a hybrid algorithm based on the improved genetic algorithm and the auction algorithm. Specifically, the auction algorithm is applied to solve the initial solution of task allocation, then the improved genetic algorithm is applied to solve the problem on this basis. The hybrid algorithm can effectively improve the solution efficiency of static task allocation. In particular, our presented algorithm can meet the demands of dynamic task allocation. Finally, simulation results confirm the effectiveness of the proposed algorithm.
UR - http://www.scopus.com/inward/record.url?scp=85208031090&partnerID=8YFLogxK
U2 - 10.1109/ICARM62033.2024.10715788
DO - 10.1109/ICARM62033.2024.10715788
M3 - 会议稿件
AN - SCOPUS:85208031090
T3 - ICARM 2024 - 2024 9th IEEE International Conference on Advanced Robotics and Mechatronics
SP - 88
EP - 93
BT - ICARM 2024 - 2024 9th IEEE International Conference on Advanced Robotics and Mechatronics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2024
Y2 - 8 July 2024 through 10 July 2024
ER -