A hybrid meta-heuristic method for the optimized deployment of the multi-unmanned underwater platforms

Ranzhen Ren; Lichuan Zhang; Lu Liu; Guang Pan; Xiaomeng Zhang; Yi Chen

doi:10.1145/3631726.3631743

A hybrid meta-heuristic method for the optimized deployment of the multi-unmanned underwater platforms

Ranzhen Ren
, Lichuan Zhang
, Lu Liu
, Guang Pan
, Xiaomeng Zhang
, Yi Chen

School of Marine Science and Technology

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	WUWNet 2023 - 17th ACM International Conference on Underwater Networks and Systems
Publisher	Association for Computing Machinery
ISBN (Electronic)	9798400716744
DOIs	https://doi.org/10.1145/3631726.3631743
State	Published - 24 Nov 2023
Event	17th ACM International Conference on Underwater Networks and Systems, WUWNet 2023 - Shenzhen, China Duration: 23 Nov 2023 → 26 Nov 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	17th ACM International Conference on Underwater Networks and Systems, WUWNet 2023
Country/Territory	China
City	Shenzhen
Period	23/11/23 → 26/11/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Hybrid meta-heuristic method
Kriging interpolation
LHS
Multi-unmanned underwater platforms
Optimized deployment

Access to Document

10.1145/3631726.3631743

Cite this

Ren, R., Zhang, L., Liu, L., Pan, G., Zhang, X., & Chen, Y. (2023). A hybrid meta-heuristic method for the optimized deployment of the multi-unmanned underwater platforms. In WUWNet 2023 - 17th ACM International Conference on Underwater Networks and Systems Article 22 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3631726.3631743

@inproceedings{8cb1756bcb7740d0951c4c403c55efba,

title = "A hybrid meta-heuristic method for the optimized deployment of the multi-unmanned underwater platforms",

abstract = "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.",

keywords = "Hybrid meta-heuristic method, Kriging interpolation, LHS, Multi-unmanned underwater platforms, Optimized deployment",

author = "Ranzhen Ren and Lichuan Zhang and Lu Liu and Guang Pan and Xiaomeng Zhang and Yi Chen",

note = "Publisher Copyright: {\textcopyright} 2023 ACM.; 17th ACM International Conference on Underwater Networks and Systems, WUWNet 2023 ; Conference date: 23-11-2023 Through 26-11-2023",

year = "2023",

month = nov,

day = "24",

doi = "10.1145/3631726.3631743",

language = "英语",

series = "ACM International Conference Proceeding Series",

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Ren, R, Zhang, L, Liu, L, Pan, G, Zhang, X & Chen, Y 2023, A hybrid meta-heuristic method for the optimized deployment of the multi-unmanned underwater platforms. in WUWNet 2023 - 17th ACM International Conference on Underwater Networks and Systems., 22, ACM International Conference Proceeding Series, Association for Computing Machinery, 17th ACM International Conference on Underwater Networks and Systems, WUWNet 2023, Shenzhen, China, 23/11/23. https://doi.org/10.1145/3631726.3631743

A hybrid meta-heuristic method for the optimized deployment of the multi-unmanned underwater platforms. / Ren, Ranzhen; Zhang, Lichuan; Liu, Lu et al.
WUWNet 2023 - 17th ACM International Conference on Underwater Networks and Systems. Association for Computing Machinery, 2023. 22 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

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

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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 -

A hybrid meta-heuristic method for the optimized deployment of the multi-unmanned underwater platforms

Abstract

Publication series

Conference

UN SDGs

Keywords

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