The HSGWO-MPIO algorithm based on improved search capability-Reference-Cited by-同舟云学术

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The HSGWO-MPIO algorithm based on improved search capability

Published:2023-04-24 Issue:14 Volume:79 Page:15997-16016
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Zhou Xinrong,Wang Fang,Zhou Chao,Shan Rui

Funder

Science and Technology Project of of Hebei Education Department

Natural Science Foundation of Hebei Province

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11227-023-05246-8.pdf

Reference34 articles.

1. Jin Z, Shima T, Schumacher CJ (2006) Optimal scheduling for refueling multiple autonomous aerial vehicles. IEEE Trans Robot 22(4):682–693. https://doi.org/10.1109/TRO.2006.878793

2. She R, Ouyang Y (2020) Efficiency of UAV-based last-mile delivery under congestion in low-altitude air. Transp Res C 122:1–13. https://doi.org/10.1016/j.trc.2020.102878

3. Pardo D, Möller L, Neunert M et al (2016) Evaluating direct transcription and nonlinear optimization methods for robot motion planning. IEEE Robot Autom Lett 1(2):946–953. https://doi.org/10.1109/LRA.2016.2527062

4. Han Y, Wang B, Deng Z et al (2016) An improved TERCOM-based algorithm for gravity-aided navigation. IEEE Sens J 16(8):2537–2544. https://doi.org/10.1109/JSEN.2016.2518686

5. Zhu Z, Yin Y, Lyu H (2023) Automatic collision avoidance algorithm based on route-plan-guided artificial potential field method. Ocean Eng 271:1–23. https://doi.org/10.1016/j.oceaneng.2023.113737

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