TY - GEN
T1 - A hybrid meta-heuristic method for the optimized deployment of the multi-unmanned underwater platforms
AU - Ren, Ranzhen
AU - Zhang, Lichuan
AU - Liu, Lu
AU - Pan, Guang
AU - Zhang, Xiaomeng
AU - Chen, Yi
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/11/24
Y1 - 2023/11/24
N2 - A novel hybrid meta-heuristic method is proposed in this paper for the optimized deployment problem of cooperative detection of multi-unmanned underwater platforms. First, a detection model considering fault-tolerant radius is employed to accurately describe the detection performance of underwater unmanned platforms. The optimized deployment model of the unmanned system is established by combining the detection coverage and communication energy consumption. Second, the Latin Hypercube Sampling(LHS) method is used to initialize the population to improve the quality of the initial population. Next, a novel hybrid meta-heuristic method is proposed. The optimal parameters are solved by Kriging interpolation method to improve the computational accuracy of the method. Finally, the analysis results of the simulation experiments show that the unmanned platform detection model is effective. Moreover, the hybrid meta-heuristic method is capable of the optimized deployment task of cooperative detection of multi-unmanned underwater platforms, and its comprehensive performance is better than that of comparison algorithms.
AB - A novel hybrid meta-heuristic method is proposed in this paper for the optimized deployment problem of cooperative detection of multi-unmanned underwater platforms. First, a detection model considering fault-tolerant radius is employed to accurately describe the detection performance of underwater unmanned platforms. The optimized deployment model of the unmanned system is established by combining the detection coverage and communication energy consumption. Second, the Latin Hypercube Sampling(LHS) method is used to initialize the population to improve the quality of the initial population. Next, a novel hybrid meta-heuristic method is proposed. The optimal parameters are solved by Kriging interpolation method to improve the computational accuracy of the method. Finally, the analysis results of the simulation experiments show that the unmanned platform detection model is effective. Moreover, the hybrid meta-heuristic method is capable of the optimized deployment task of cooperative detection of multi-unmanned underwater platforms, and its comprehensive performance is better than that of comparison algorithms.
KW - Hybrid meta-heuristic method
KW - Kriging interpolation
KW - LHS
KW - Multi-unmanned underwater platforms
KW - Optimized deployment
UR - http://www.scopus.com/inward/record.url?scp=85197221917&partnerID=8YFLogxK
U2 - 10.1145/3631726.3631743
DO - 10.1145/3631726.3631743
M3 - 会议稿件
AN - SCOPUS:85197221917
T3 - ACM International Conference Proceeding Series
BT - WUWNet 2023 - 17th ACM International Conference on Underwater Networks and Systems
PB - Association for Computing Machinery
T2 - 17th ACM International Conference on Underwater Networks and Systems, WUWNet 2023
Y2 - 23 November 2023 through 26 November 2023
ER -
