Shuffled frog leaping algorithm with non-dominated sorting for dynamic weapon-target assignment

doi:10.23919/JSEE.2023.000102

Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (4): 1007-1019.doi: 10.23919/JSEE.2023.000102

• • 上一篇

收稿日期:2021-03-07 出版日期:2023-08-18 发布日期:2023-08-28

Shuffled frog leaping algorithm with non-dominated sorting for dynamic weapon-target assignment

Yang ZHAO(), Jicheng LIU(), Ju JIANG(), Ziyang ZHEN()

¹ College of Automation Engineering, Nanjing University of Aeronautics and Astronauts, Nanjing 211106, China

Received:2021-03-07 Online:2023-08-18 Published:2023-08-28
Contact: Yang ZHAO E-mail:zy@nuaa.edu.cn;ljc_uav@nuaa.edu.com;jiangju@nuaa.edu.cn;zhenziyang@nuaa.edu.cn
About author:
ZHAO Yang was born in 1987. He received his M.S. degree in the College of Automation Engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2013. He is pursuing his Ph.D. degree in the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. His research interests include advanced aircraft flight control and intelligent decision-making for modern air combat. E-mail: zy@nuaa.edu.cn

LIU Jicheng was born in 1996. He received his B.S. degree in the College of Automation Engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2019. He is pursuing his M.S. degree in the College of Automation Engineering from Nanjing University of Aeronautics and Astronautics. His main research interests include advanced flight control theory and its application to multi-unmanned aerial vehicle flight control systems. E-mail: ljc_uav@nuaa.edu.com

JIANG Ju was born in 1963. He received his M.S. and Ph.D. degrees in navigation, guidance and control from Beijing University of Aeronautics and Astronautics, Beijing, China, in 1988 and 2007. He is a professor at Nanjing University of Aeronautics and Astronautics. His research interest includes navigation and flight control of aircraft systems. E-mail: jiangju@nuaa.edu.cn

ZHEN Ziyang was born in 1981. He received his M.S. and Ph.D. degrees in control theory and control engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2007 and 2010. He is a professor at Nanjing University of Aeronautics and Astronautics. His research interests include advanced aircraft flight control, unmanned aerial vehicle swarm cooperative control, and artificial intelligence. E-mail: zhenziyang@nuaa.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (61673209; 71971115)

摘要/Abstract

Abstract:

The dynamic weapon target assignment (DWTA) problem is of great significance in modern air combat. However, DWTA is a highly complex constrained multi-objective combinatorial optimization problem. An improved elitist non-dominated sorting genetic algorithm-II (NSGA-II) called the non-dominated shuffled frog leaping algorithm (NSFLA) is proposed to maximize damage to enemy targets and minimize the self-threat in air combat constraints. In NSFLA, the shuffled frog leaping algorithm (SFLA) is introduced to NSGA-II to replace the inside evolutionary scheme of the genetic algorithm (GA), displaying low optimization speed and heterogeneous space search defects. Two improvements have also been raised to promote the internal optimization performance of SFLA. Firstly, the local evolution scheme, a novel crossover mechanism, ensures that each individual participates in updating instead of only the worst ones, which can expand the diversity of the population. Secondly, a discrete adaptive mutation algorithm based on the function change rate is applied to balance the global and local search. Finally, the scheme is verified in various air combat scenarios. The results show that the proposed NSFLA has apparent advantages in solution quality and efficiency, especially in many aircraft and the dynamic air combat environment.

Key words: dynamic weapon-target assignment (DWTA) problem, shuffled frog leaping algorithm (SFLA), air combat research

. [J]. Journal of Systems Engineering and Electronics, 2023, 34(4): 1007-1019.

Yang ZHAO, Jicheng LIU, Ju JIANG, Ziyang ZHEN. Shuffled frog leaping algorithm with non-dominated sorting for dynamic weapon-target assignment[J]. Journal of Systems Engineering and Electronics, 2023, 34(4): 1007-1019.

图/表 16

参考文献 33

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Parameter	Value	Type
$ m $	$\{\text{ {4}，\text{6}，\text{12}，\text{18} } \}$	Integer
$ r $	$\{ {2}\times m,2\times m,2\times m,2\times m{} \}$	Integer
$ n $	$\{\text{ {6}，10，\text{20}，\text{36} } \}$	Integer
$ v $	$\{\text{ {2}，\text{2}，\text{3}，\text{3} } \}$	Integer
$ n_k^h $	1	Integer
$ m_j^h $	$\{ \text{ {2}，\text{2}，\text{3}，\text{3} }\}$	Integer
$ {a_k} $	$\{ \text{ {2}，\text{2}，\text{2}，\text{2} }\}$	Integer
$ f_{kj}^h $	$\left\{\begin{aligned}&1,\;\;\rho \lt \theta \\ &0,\;\;\text{otherwise}\end{aligned}\right.$ where $\theta {\text{ = } }0.8 - 0.1 h$	Float

$({\rm{Nmp}},{\rm{Nem}})$	$({F_{{\rm{avg}}} },{E_{{\rm{avg}}} })$	$({F_{{\rm{std}}} },{E_{{\rm{std}}} })$	${T_{{\rm{avg}}} }$	${T_{{\rm{std}}} }$	${N_{{\rm{avg}}} }$	${\rm{Ind}}$
(5,60)	(38.24,10.27)	(0.00531,0.00507)	16.2931	1.4682	63.0241	0.3184
(10,30)	(37.37,11.51)	(0.00406,0.00401)	15.6742	0.9257	58.2852	0.7627
(15,20)	(37.12,12.01)	(0.00352,0.00337)	14.7203	0.5060	52.7503	1.9241
(20,15)	(37.13,11.79)	(0.00347,0.00364)	14.9268	0.7401	58.9511	1.7956
(30,10)	(37.45,11.23)	(0.00509,0.00498)	15.6472	0.8364	60.2047	0.6507
(60,5)	(38.03,11.02)	(0.00646,0.00632)	15.9356	1.2679	62.6059	0.3166

P=150		P=200		P=500
$({\rm{Nmp}},{\rm{Nem}})$	${\rm{Ind}}$	$({\rm{Nmp}},{\rm{Nem}})$	${\rm{Ind}}$	$({\rm{Nmp}},{\rm{Nem}})$	${\rm{Ind}}$
(5,30)	0.2668	(5,40)	1.4502	(10,50)	4.9341
(10,15)	0.2955	(10,20)	1.5884	(20,25)	5.1755
(15,10)	0.3031	(20,10)	1.6032	(25,20)	5.3022
(30,5)	0.2764	(40,5)	1.4794	(50,10)	4.9816

Case	Criteria	$ \varepsilon $
		${p_{{\rm{cross}}} } = 0.2$			${p_{{\rm{cross}}} } = 0.5$			${p_{{\rm{cross}}} } = 0.8$
		2.0	6.0	10.0	2.0	6.0	10.0	2.0	6.0	10.0
II	${F_{{\rm{avg}}} }$	8.2473	8.2472	8.2473	8.2461	8.2458	8.2460	8.2470	8.2472	8.2472
	${E_{{\rm{avg}}} }$	4.8051	4.8050	4.8055	4.8079	4.8082	4.8068	4.8081	4.8112	4.8078
	${T_{{\rm{avg}}} }$	9.6005	9.1317	8.9053	9.5224	9.0127	8.9050	9.6732	9.1260	9.1071
	${N_{{\rm{avg}}} }$	18.5207	15.3214	15.8553	17.0524	13.3285	16.5227	14.0952	13.4100	16.2571
	${\rm{Ind}}$	13.4931	18.4212	19.3138	11.7050	21.5326	16.6947	15.4371	19.0545	18.9267
III	${F_{{\rm{avg}}} }$	37.2723	37.2715	37.2771	37.1365	37.1361	37.1473	37.1642	37.1637	37.1810
	${E_{{\rm{avg}}} }$	12.0548	12.1036	12.0872	12.1429	12.2550	12.2546	12.2510	12.2649	12.2588
	${T_{{\rm{avg}}} }$	14.3106	13.5501	13.1864	13.3601	12.9197	13.0985	14.6062	13.0089	13.4272
	${N_{{\rm{avg}}} }$	65	59	61	62	55	56	66	62	62
	${\rm{Ind}}$	0.4060	0.5009	0.4978	0.5329	0.6220	0.6212	0.4576	0.0538	0.5296

Parameter	Binh1		Fonseca2		Poloni
Parameter	NSFLA	NSGA-II	NSFLA	NSGA-II	NSFLA	NSGA-II
${C_{{\rm{avg}}} }$	0.00015	0.00020	0.00012	0.00077	0.00038	0.00170
${N_{{\rm{avg}}} }$	6.68508	7.00131	5.24771	5.78068	6.52404	7.13399
${C_{{\rm{std}}} }$	0.02091	0.02417	0.00096	0.00154	0.11474	0.13550

Shuffled frog leaping algorithm with non-dominated sorting for dynamic weapon-target assignment

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