MAV-UAV combat organization’s force formation plan generation based on NSGA-III

doi:10.23919/JSEE.2026.000008

Journal of Systems Engineering and Electronics ›› 2026, Vol. 37 ›› Issue (1): 307-317.doi: 10.23919/JSEE.2026.000008

• SYSTEMS ENGINEERING • Previous Articles Next Articles

MAV-UAV combat organization’s force formation plan generation based on NSGA-III

Yun ZHONG¹^,*(), Lujun WAN²(), Jieyong ZHANG¹()

¹Information and Navigation College, Air Force Engineering University, Xi’an 710077, China
²Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710053, China

Received:2023-11-13 Online:2026-02-18 Published:2026-03-09
Contact: Yun ZHONG E-mail:718227697@qq.com;pandawlj@126.com;dumu3110728@126.com
About author:
ZHONG Yun was born in 1990. He received his master’s degree and Ph.D. degree from Air Force Engineering University in 2014 and 2018, respectively. He is currently a lecturer of the Information and Navigation College, Air Force Engineering University. His research interest is manned aerial vehicle-unmanned aerial vehicle combat command and control. E-mail: 718227697@qq.com

WAN Lujun was born in 1986. He received his master’s degree and Ph.D. degree from Air Force Engineering University in 2009 and 2013, respectively. He is currently an associate professor of the Air Traffic Control and Navigation College, Air Force Engineering University. His research interest is airspace control.E-mail: pandawlj@126.com

ZHANG Jieyong was born in 1983. He received his master’s degree and Ph.D. degree from Air Force Engineering University in 2008 and 2012, respectively. He is currently an associate professor of the Information and Navigation College, Air Force Engineering University. His research interest is command and control modeling and simulation.E-mail: dumu3110728@126.com
Supported by:
This work was supported by the Natural Science Foundation of Shaanxi Province (2023-JC-QN-0728) and the China Postdoctoral Science Foundation (2021M693942).

Abstract

Abstract:

Manned aerial vehicle-unmanned aerial vehicle (MAV-UAV) combat organization is a MAV-UAV combat collective formed from the perspective of organization design theory and methodology, and the generation of force formation plan is a key step in the organizational planning. Based on the description of the problem and the definition of organizational elements, the matching model of platform-target attack wave is constructed to minimize the redundancy of command and decision-making capability, resource capability and the number of platforms used. Based on the non-dominated sorting genetic algorithm III (NSGA-III) framework, which includes encoding/decoding method and constraint handling method, the generation model of organizational force formation plan is solved, and the effectiveness and superiority of the algorithm are verified by simulation experiments.

Key words: manned-unmanned aerial vehicle combat organization, force formation plan, command and decision-making capability, resource capability, non-dominated sorting genetic algorithm III (NSGA-III)

Yun ZHONG, Lujun WAN, Jieyong ZHANG. MAV-UAV combat organization’s force formation plan generation based on NSGA-III[J]. Journal of Systems Engineering and Electronics, 2026, 37(1): 307-317.

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References 31

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Wave	Target	Resource requirement
Wave	Target	r₁	r₂	r₃	r₄	r₅	r₆
Wave 1	T₁	3	1	0	0	0	0
	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
	T₂₄	1	2	0	0	0	0
Wave 2	T₂₅	0	3	2	0	0	0
	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
	T₄₈	0	2	2	0	0	0
Wave 3	T₄₉	0	0	2	3	0	0
	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
	T₇₁	0	0	1	3	0	0
Wave 4	T₇₂	0	0	0	0	2	2
	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
	T₁₀₀	0	0	0	0	2	2

UAV	Resource capability
UAV	r₁	r₂	r₃	r₄	r₅	r₆
U₁	4	5	5	3	4	4
$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
U₁₀	3	4	4	6	6	3
$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
U₂₀	6	3	3	5	5	6
$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
U₃₀	5	4	5	2	4	6
$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
U₄₀	4	3	4	3	5	6
$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
U₅₀	3	2	3	4	3	5
$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
U₆₀	2	2	4	4	4	3

Wave	Allocated platform	$ \lambda_{1} $	$ \boldsymbol{\delta}_{l, q} $
Wave 1	U₂, U₄, U₉, U₁₂, U₁₄, U₁₉, U₂₃, U₂₆, U₃₁, U₃₉, U₄₄, U₄₆, U₄₈, U₄₉, U₅₀, U₅₂, U₅₃, M₁, M₄, M₉, M₁₀	0.65	(0.30,0.40)
Wave 2	U₆, U₇, U₁₁, U₁₇, U₂₁, U₂₄, U₂₉, U₃₅, U₃₈, U₄₃, U₄₅, U₄₇, U₅₁, U₅₈, U₅₉, M₅, M₈, M₁₃	0.60	(0.27,0.35)
Wave 3	U₁, U₂, U₃, U₅, U₉, U₁₀, U₁₃, U₁₆, U₁₈, U₁₉, U₂₀, U₂₇, U₃₀, U₃₃, U₃₉, U₅₀, U₅₂, U₅₅, U₅₆, U₅₇, M₁, M₃, M₆, M₇	0.55	(0.89,0.60)
Wave 4	U₄, U₇, U₁₁, U₁₂, U₁₄, U₁₅, U₁₇, U₂₃, U₂₅, U₂₆, U₂₈, U₃₁, U₃₂, U₃₄, U₃₇, U₄₁, U₄₂, U₄₄, U₄₅, U₄₆, U₄₈, U₅₄, M₂, M₄, M₈, M₁₀, M₁₂, M₁₄	0.77	(0.47,0.37)

Allocation	Specific platform
Unallocated	U₈, U₂₂, U₃₆, U₄₀, U₆₀, U₇₁, U₇₅
Allocated to any wave	U₁, U₃, U₅, U₆, U₁₀, U₁₃, U₁₅, U₁₆, U₁₈, U₂₀, U₂₁, U₂₄, U₂₅, U₂₇, U₂₈, U₂₉, U₃₀, U₃₂, U₃₃, U₃₄, U₃₅, U₃₇, U₃₈, U₄₁, U₄₂, U₄₃, U₄₇, U₄₉, U₅₁, U₅₃, U₅₄, U₅₅, U₅₆, U₅₇, U₅₈, U₅₉, U₆₂, U₆₃, U₆₅, U₆₆, U₆₇, U₆₉, U₇₂, U₇₃, U₇₄
Allocated to wave 1 and wave 3	U₂, U₉, U₁₉, U₃₉, U₅₀, U₅₂, U₆₁
Allocated to wave 1 and wave 4	U₄, U₁₂, U₁₄, U₂₃, U₂₆, U₃₁, U₄₄, U₄₆, U₄₈, U₆₄, U₇₀
Allocated to wave 2 and wave 4	U₇, U₁₁, U₁₇, U₄₅, U₆₈

MAV-UAV combat organization’s force formation plan generation based on NSGA-III

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