Optimization of Missile Path Planning Based on APMO-HV Algorithm

Hu Zhang; Shuai Wang; Tonglin Liu; Aimin Zhou; Yi Zhang

doi:10.1109/ICUS48101.2019.8996084

Optimization of Missile Path Planning Based on APMO-HV Algorithm

Hu Zhang
, Shuai Wang^*
, Tonglin Liu
, Aimin Zhou
, Yi Zhang

^*Corresponding author for this work

School of Computer Science and Technology

Beijing Electro-mechanical Engineering Institute
Changzhou University

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

1 Scopus citations

Abstract

In this paper, with considerations of low efficiency of missile path planning (MPP) by traditional aggregation technology, it uses affinity propagation based multi-objective evolutionary algorithm with hypervolume environment selection (APMO-HV) to solve the problem of MPP after establishing the MPP model. The experimental part compares and analyzes APMO-HV with six state-of-the-art algorithms, and applies it to address the MPP problem. The experimental results show that compared with the other six algorithms, APMO-HV has achieved the best solution performance in both the GLT test suite and MPP problem. This not only validates the effect of the proposed algorithm, but also enriches and improves the research results of MPP.

Original language	English
Title of host publication	Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	495-501
Number of pages	7
ISBN (Electronic)	9781728137926
DOIs	https://doi.org/10.1109/ICUS48101.2019.8996084
State	Published - Oct 2019
Event	2019 IEEE International Conference on Unmanned Systems, ICUS 2019 - Beijing, China Duration: 17 Oct 2019 → 19 Oct 2019

Publication series

Name	Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

Conference

Conference	2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Country/Territory	China
City	Beijing
Period	17/10/19 → 19/10/19

Keywords

evolutionary algorithm
hypervolume environment selection
missile path planning
multi-objective optimization

Access to Document

10.1109/ICUS48101.2019.8996084

Cite this

Zhang, H., Wang, S., Liu, T., Zhou, A., & Zhang, Y. (2019). Optimization of Missile Path Planning Based on APMO-HV Algorithm. In Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019 (pp. 495-501). Article 8996084 (Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICUS48101.2019.8996084

@inproceedings{06852fda3dec45cebb8b57bed42bff20,

title = "Optimization of Missile Path Planning Based on APMO-HV Algorithm",

abstract = "In this paper, with considerations of low efficiency of missile path planning (MPP) by traditional aggregation technology, it uses affinity propagation based multi-objective evolutionary algorithm with hypervolume environment selection (APMO-HV) to solve the problem of MPP after establishing the MPP model. The experimental part compares and analyzes APMO-HV with six state-of-the-art algorithms, and applies it to address the MPP problem. The experimental results show that compared with the other six algorithms, APMO-HV has achieved the best solution performance in both the GLT test suite and MPP problem. This not only validates the effect of the proposed algorithm, but also enriches and improves the research results of MPP.",

keywords = "evolutionary algorithm, hypervolume environment selection, missile path planning, multi-objective optimization",

author = "Hu Zhang and Shuai Wang and Tonglin Liu and Aimin Zhou and Yi Zhang",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Unmanned Systems, ICUS 2019 ; Conference date: 17-10-2019 Through 19-10-2019",

year = "2019",

month = oct,

doi = "10.1109/ICUS48101.2019.8996084",

language = "英语",

series = "Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "495--501",

booktitle = "Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019",

address = "美国",

}

Zhang, H, Wang, S, Liu, T, Zhou, A & Zhang, Y 2019, Optimization of Missile Path Planning Based on APMO-HV Algorithm. in Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019., 8996084, Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019, Institute of Electrical and Electronics Engineers Inc., pp. 495-501, 2019 IEEE International Conference on Unmanned Systems, ICUS 2019, Beijing, China, 17/10/19. https://doi.org/10.1109/ICUS48101.2019.8996084

Optimization of Missile Path Planning Based on APMO-HV Algorithm. / Zhang, Hu; Wang, Shuai; Liu, Tonglin et al.
Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 495-501 8996084 (Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019).

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

TY - GEN

T1 - Optimization of Missile Path Planning Based on APMO-HV Algorithm

AU - Zhang, Hu

AU - Wang, Shuai

AU - Liu, Tonglin

AU - Zhou, Aimin

AU - Zhang, Yi

PY - 2019/10

Y1 - 2019/10

N2 - In this paper, with considerations of low efficiency of missile path planning (MPP) by traditional aggregation technology, it uses affinity propagation based multi-objective evolutionary algorithm with hypervolume environment selection (APMO-HV) to solve the problem of MPP after establishing the MPP model. The experimental part compares and analyzes APMO-HV with six state-of-the-art algorithms, and applies it to address the MPP problem. The experimental results show that compared with the other six algorithms, APMO-HV has achieved the best solution performance in both the GLT test suite and MPP problem. This not only validates the effect of the proposed algorithm, but also enriches and improves the research results of MPP.

AB - In this paper, with considerations of low efficiency of missile path planning (MPP) by traditional aggregation technology, it uses affinity propagation based multi-objective evolutionary algorithm with hypervolume environment selection (APMO-HV) to solve the problem of MPP after establishing the MPP model. The experimental part compares and analyzes APMO-HV with six state-of-the-art algorithms, and applies it to address the MPP problem. The experimental results show that compared with the other six algorithms, APMO-HV has achieved the best solution performance in both the GLT test suite and MPP problem. This not only validates the effect of the proposed algorithm, but also enriches and improves the research results of MPP.

KW - evolutionary algorithm

KW - hypervolume environment selection

KW - missile path planning

KW - multi-objective optimization

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DO - 10.1109/ICUS48101.2019.8996084

M3 - 会议稿件

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T3 - Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

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BT - Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

PB - Institute of Electrical and Electronics Engineers Inc.

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Zhang H, Wang S, Liu T, Zhou A, Zhang Y. Optimization of Missile Path Planning Based on APMO-HV Algorithm. In Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 495-501. 8996084. (Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019). doi: 10.1109/ICUS48101.2019.8996084

Optimization of Missile Path Planning Based on APMO-HV Algorithm

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