Pre-planning method of joint air defense resources for ship formations based on improved genetic algorithm

LYU Xiadong; ZHENG Shuang; CHEN Jie

doi:10.19693/j.issn.1673-3185.02877

Volume 18 Issue 3

Jun. 2023

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Chinese Journal of Ship Research > 2023 > 18(3): 266-276. > DOI: 10.19693/j.issn.1673-3185.02877 CSTR: 32390.14.j.issn.1673-3185.02877

LYU X D, ZHENG S, CHEN J. Pre-planning method of joint air defense resources for ship formations based on improved genetic algorithm[J]. Chinese Journal of Ship Research, 2023, 18(3): 266–276. DOI: 10.19693/j.issn.1673-3185.02877

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Pre-planning method of joint air defense resources for ship formations based on improved genetic algorithm

China Ship Development and Design Center, Wuhan 430064, China

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Received Date: April 25, 2022
Revised Date: January 17, 2023
Available Online: January 30, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Objectives The field of combat resource planning has gradually become the core point of intelligent decision guidance for future combat, and ensuring a better combat resource planning scheme is crucial to the guidance and implementation of actual combat. To this end, a resource planning method for the joint air defense of warship formations based on an improved genetic algorithm is proposed.
Methods First, the resources are serviced to improve their versatility; next, the articulation of multi-population genetic algorithms is used to represent multi-stage combat planning, and multi-dimensional quality of service (QoS) combat performance indicators are designed on the basis of multi-population genetic algorithms, thereby establishing a set of strengths and weaknesses for the evaluation of joint warfare planning programs.
Results After the generalization of resources, the proposed method can be effectively combined with multi-population genetic algorithms to obtain a multi-stage optimal combat resource planning scheme.
Conclusion This study has certain reference value for the design and application of combat resource planning.
- coordinated operations,
- resource scheduling,
- genetic algorithm,
- mission resource planning

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Pre-planning method of joint air defense resources for ship formations based on improved genetic algorithm

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