基于杀伤网评估的装备组合多目标优化

doi:10.12305/j.issn.1001-506X.2021.02.15

Abstract

Abstract:

As a concept involved in many new combat concepts, the kill-web will replace the kill-chain as the main mode for generating combat effectiveness under the novel combat operations. In this paper, we make multiple-objective optimization for the problem of the traditional equipment portfolio based on the evaluation of kill-web. First, we construct the network description method of kill-web based on the multi-layer network model. Second, we constrult three evaluation criteria based on the characteristics of kill-web including redundancy indicator, risk indicator, and agility indicator, and propose the calculation model of three evaluation indicator. Then, we construct an equipment portfolio programming model based on the kill-web evaluation criteria and present a heuristic algorithm-based multi-objective optimization method of equipment portfolio. Finally, we carry out a case study to compare the advantages and disadvantages of two different kill-webs with different equipment composition and network structure, and then optimize the equipment portfolio based on the first kill-web including unmanned equipment to verify the rationality of the evaluation model and the effectiveness of the optimization model, respectively.

Key words: kill-web, equipment portfolio, redundancy, risk, agility, multi-objective optimization

CLC Number:

N945.15

Boyuan XIA, Kewei YANG, Zhiwei YANG, Xiaoke ZHANG, Danling ZHAO. Multi-objective optimization of equipment portfolio based on kill-web evaluation[J]. Systems Engineering and Electronics, 2021, 43(2): 399-409.

Figures/Tables 16

Fig.1

Fig.2

Table 1

Table 2

Table 3

Table 4

Fig.3

Table 5

Table 6

Table 7

Table 8

Table 9

Fig.4

Table 10

Table 11

Fig.5

References 31

1	雷子欣, 李元平. 美国"马赛克战"作战概念解析[J]. 军事文摘, 2019, (2): 6- 10.
	LEI Z X , LI Y P . An analysis of the concept of American "Mosaic War"[J]. Military Digest, 2019, (2): 6- 10.
2	MATTIS J. National defense strategy[EB/OL].[2020-03-03]. https://dod.defense.gov/Portals/1/Documents/pubs/2018-National-Defense-Strategy-Summary.pdf.
3	飞行总动员航天网.诺斯罗普·格鲁曼使用全球鹰无人机解决F-22与F-35战机通信代差问题[EB/OL].[2020-03-03]. https://www.sohu.com/a/169761629_476262, 2017-09-05.
	General aviation aerospace network. Northrop Grumman used the global hawk to solve the communication gap between f-22 and f-35 aircraft[EB/OL].[2020-03-03]. https://www.sohu.com/a/169761629_476262, 2017-09-05.
4	吴勤. 美军分布式作战概念发展分析[J]. 军事文摘, 2016, (7): 44- 47.
	WU Q . Development analysis of distributed combat concept of the US army[J]. Military Digest, 2016, (7): 44- 47.
5	叶秋玲,汪强.美军发布多域作战概念最新1.5版本[EB/OL].[2020-03-04]. http://www.fx361.com/page/2019/0312/4993189.shtml, 2019-03-12.
	YE Q L, WANG Q. U.S. release the latest version 1.5 of the multi-domain operational concepts[EB/OL].[2020-03-04]. http://www.fx361.com/page/2019/0312/4993189.shtml.
6	WILLIAMS D B. DARPA's "mosaic warfare" concept turns complexity into asymmetric advantage[EB/OL].[2020-03-05]. http://tony.9shi.cf/index.php?q=aHR0cHM6Ly93d3cuZmlmdGhkb21haW4uY29tL2RvZC8yMDE3LzA4LzE0L2RhcnBhcy1tb3NhaWMtd2FyZmFyZS1jb25jZXB0LXR1cm5zLWNvbXBsZXhpdHktaW50by1hc3ltbWV0cmljLWFkdmFudGFnZS8.
7	TERVONEN T , LIESIÖ J , SALO A . Modeling project preferences in multi-attribute portfolio decision analysis[J]. European Journal of Operational Research, 2017, 263 (1): 225- 239. doi: 10.1016/j.ejor.2017.04.051
8	SEFAIR J A , MÉNDEZ C Y , BABAT O , et al. Linear solution schemes for mean-semi variance project portfolio selection problems: an application in the oil and gas industry[J]. Omega, 2017, 68, 39- 48. doi: 10.1016/j.omega.2016.05.007
9	MOHAGHEGHI V , MOUSAVI S M , VAHDANI B , et al. R&D project evaluation and project portfolio selection by a new interval type -2 fuzzy optimization approach[J]. Neural Computing and Applications, 2017, 28 (12): 3869- 3888. doi: 10.1007/s00521-016-2262-3
10	LIU Y , LIU Y K . Distributionally robust fuzzy project portfolio optimization problem with interactive returns[J]. Applied Soft Computing, 2017, 56, 655- 668. doi: 10.1016/j.asoc.2016.09.022
11	SILVA C G , MEIDANIS J , MOURA A V , et al. An improved visualization-based approach for project portfolio selection[J]. Computers in Human Behavior, 2017, 73, 685- 696. doi: 10.1016/j.chb.2016.12.083
12	SCHIFFELS S , FLIEDNER T , KOLISCH R . Human behavior in project portfolio selection: insights from an experimental study[J]. Decision Sciences, 2018, 49 (6): 1061- 1087. doi: 10.1111/deci.12310
13	JAFARZADEH H , AKBARI P , ABEDIN B . A methodology for project portfolio selection under criteria prioritisation, uncertainty and projects interdependency-combination of fuzzy QFD and DEA[J]. Expert Systems with Applications, 2018, 110, 237- 249. doi: 10.1016/j.eswa.2018.05.028
14	FIALA P . Project portfolio designing using data envelopment analysis and De Novo optimization[J]. Central European Journal of Operations Research, 2018, 26 (4): 847- 859. doi: 10.1007/s10100-018-0571-6
15	KOROTIN V , POPOV V , TOLOKONSKY A , et al. A multi-criteria approach to selecting an optimal portfolio of refinery upgrade projects under margin and tax regime uncertainty[J]. Omega, 2017, 72 (C): 50- 58.
16	TINOCO M A C , DUTRA C C , RIBEIRO J L D , et al. An integrated model for evaluation and optimisation of business project portfolios[J]. European Journal of Industrial Engineering, 2018, 12 (3): 442- 463. doi: 10.1504/EJIE.2018.092010
17	LI J C , GE B F , JIANG J , et al. High-end weapon equipment portfolio selection based on a heterogeneous network model[J]. Journal of Global Optimization, 2020, 78, 743- 761. doi: 10.1007/s10898-018-0687-1
18	XIONG J , ZHOU Z B , LIAO T J , et al. A multi-objective approach for weapon selection and planning problems in dynamic environments[J]. Journal of Industrial & Management Optimization, 2017, 13 (3): 1189- 1211.
19	XIA B Y , ZHAO Q S , YANG K W , et al. Scenario-based modeling and solving research on robust weapon project planning problems[J]. Journal of Systems Engineering and Electronics, 2019, 30 (1): 85- 99. doi: 10.21629/JSEE.2019.01.09
20	VAHID M , MEYSAM M S , BEHAM V , et al. A mathematical modeling approach for high and new technology-project portfolio selection under uncertain environments[J]. Journal of Intelligent & Fuzzy Systems, 2017, 32 (6): 4069- 4079.
21	张骁雄, 葛冰峰, 姜江, 等. 面向能力需求的武器装备组合规划模型与算法[J]. 国防科技大学学报, 2017, 39 (1): 102- 108.
	ZHANG X X , GE B F , JIANG J , et al. Adapt to the need of the ability of weapon and equipment combination programming model and algorithm[J]. Journal of National University of Defense Technology, 2017, 39 (1): 102- 108.
22	豆亚杰, 徐向前, 周哲轩, 等. 系统组合选择方法及典型军事应用[J]. 系统工程与电子技术, 2019, 41 (12): 2754- 2762.
	DOU Y J , XU X Q , ZHOU Z X , et al. Analysis of system portfolio selection and typical military application[J]. Systems Engineering and Electronics, 2019, 41 (12): 2754- 2762.
23	杨克巍, 杨志伟, 谭跃进, 等. 面向体系贡献率的装备体系评估方法研究综述[J]. 系统工程与电子技术, 2019, 41 (2): 311- 321.
	YANG K W , YANG Z W , TAN Y J , et al. Review of the evaluation methods of equipment system of systems facing the contribution rate[J]. Systems Engineering and Electronics, 2019, 41 (2): 311- 321.
24	夏博远, 赵青松, 张骁雄, 等. 基于动态能力需求的鲁棒性武器系统组合决策[J]. 系统工程与电子技术, 2017, 39 (6): 1280- 1286.
	XIA B Y , ZHAO Q S , ZHANG X X , et al. Robust weapon system portfolio decision based on dynamic capability requirements[J]. Systems Engineering and Electronics, 2017, 39 (6): 1280- 1286.
25	刘鹏, 赵丹玲, 谭跃进, 等. 面向多任务的武器装备体系贡献度评估方法[J]. 系统工程与电子技术, 2019, 41 (8): 1763- 1770.
	LIU P , ZHAO D L , TAN Y J , et al. Multi-task oriented contribution evaluation method of weapon equipment system of systems[J]. Systems Engineering and Electronics, 2019, 41 (8): 1763- 1770.
26	李际超, 吴俊, 谭跃进, 等. 基于有向自然连通度的作战网络抗毁性研究[J]. 复杂系统与复杂性科学, 2015, 12 (4): 25- 31.
	LI J C , WU J , TAN Y J , et al. Robustness of combat networks based on directed natural connectivity[J]. Complex Systems and Complexity Science, 2015, 12 (4): 25- 31.
27	LI J C , ZHAO D L , JAING J , et al. Capability oriented equipment contribution analysis in temporal combat networks[J]. IEEE Trans.on Systems, Man, and Cybernetics: Systems,, 2015, 12 (4): 25- 31.
28	LI J C , JIANG J , YANG K , et al. Research on functional robustness of heterogeneous combat networks[J]. IEEE Systems Journal, 2018, 13 (2): 1487- 1495.
29	ARYO D. Dijkstra algorithm[EB/OL].[2020-02-12]. https://www.mathworks.com/matlabcentral/fileexchange/36140-dijkstra-algorithm.
30	DEB K , PRATAP A , AGARWAL S , et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE Trans.on Evolutionary Computation, 2002, 6 (2): 182- 197. doi: 10.1109/4235.996017
31	SHIH H S , SHYUR H J , LEE E S . An extension of TOPSIS for group decision making[J]. Mathematical & Computer Modelling, 2007, 45 (7): 801- 813.

	r₁	r₂	r₃	r₄	r₅	r₆	r₇	r₈	r₉	r₁₀	r₁₁	r₁₂
r₁	0	0	0	0	0	0	1	0	0	0	0	1
r₂	0	0	0	0	0	0	0	0	0	1	0	0
r₃	0	1	1	0	0	0	1	0	0	0	0	0

	r₁	r₂	r₃	r₄	r₅	r₆	r₇	r₈	r₉	r₁₀	r₁₁	r₁₂
r₁	1	1	1	0	0	0	0	0	0	0	0	0
r₂	1	1	1	0	1	0	0	0	0	0	0	0
r₃	1	1	1	1	0	1	1	0	0	0	0	1
r₄	0	0	1	1	0	1	1	0	0	0	0	0
r₅	0	1	0	0	1	0	1	1	0	0	0	1
r₆	0	0	1	1	0	1	1	0	0	0	0	0
r₇	0	0	1	1	1	1	1	0	0	0	1	1
r₈	0	0	0	0	1	0	0	1	1	1	0	0
r₉	0	0	0	0	0	0	0	1	1	0	0	0
r₁₀	0	0	0	0	0	0	0	1	0	1	0	0
r₁₁	0	0	0	0	0	0	1	0	0	0	1	0
r₁₂	0	0	1	0	1	0	1	0	0	0	0	1

	r₁	r₂	r₃	r₄	r₅	r₆	r₇	r₈	r₉	r₁₀	r₁₁	r₁₂
r₁	0	0	0	0	0	0	0	0	0	0	0	0
r₂	1	1	1	0	1	0	0	0	0	0	0	0
r₃	0	0	1	1	0	1	1	0	0	0	0	0
r₄	0	0	0	0	0	0	0	0	0	0	0	0
r₅	0	0	0	0	1	0	0	1	1	0	1	0
r₆	0	0	0	0	0	0	0	0	0	0	0	0
r₇	0	0	0	0	0	0	1	0	0	0	1	0
r₈	0	0	0	0	0	0	0	1	0	1	0	0
r₉	0	0	0	0	0	0	0	0	0	0	0	0
r₁₀	0	0	0	0	0	0	0	0	0	0	0	0
r₁₁	0	0	0	0	0	0	0	0	0	0	0	0
r₁₂	0	0	0	0	0	0	0	0	0	0	0	0

	b₁	b₂	b₃
r₁	1	0	0
r₂	0	0	0
r₃	0	0	0
r₄	0	0	1
r₅	1	0	0
r₆	0	0	1
r₇	0	0	0
r₈	0	0	0
r₉	0	1	0
r₁₀	0	0	0
r₁₁	1	0	0
r₁₂	0	0	0

	r₁	r₂	r₃	r₄	r₅	r₆	r₇	r₈	r₉
b₁	0	0	0	0	0	0	0	0	1
b₂	0	0	0	0	0	0	1	0	0
b₃	0	0	1	0	0	0	0	0	0

Multi-objective optimization of equipment portfolio based on kill-web evaluation

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 16

References 31

Related Articles 15

Recommended Articles

Metrics

Comments

指标	示例1	示例2	指标解释	优势方
节点数量	12(3)	9(3)	每个杀伤网中己方节点的数量(目标节点数量)	—
冗余性	157.33	3	针对每个目标形成的杀伤链数量平均值	示例1
风险性	0.56	0.29	每个节点失能后损失的杀伤链数量占原有杀伤链数量比值的平均值	示例2
敏捷性	0.77	0.68	每个指控节点指控其他节点的敏捷性的均值	示例1

Pareto解	冗余性	风险性	敏捷性	TOPSIS值
1	157.33	0.56	0.77	0.755 6
2	148.67	0.76	0.78	0.622 3
3	74.67	0.55	0.77	0.465 6
4	23.67	0.38	0.76	0.361 6
5	1.67	0.28	0.65	0.364 0
6	1.33	0.30	0.72	0.359 4

序号	权重值
1	0.1	0.1	0.8
2	0.1	0.2	0.7
3	0.1	0.3	0.6
4	0.1	0.4	0.5
5	0.1	0.5	0.4
6	0.1	0.6	0.3
7	0.1	0.7	0.2
8	0.1	0.8	0.1
9	0.2	0.1	0.7
10	0.2	0.2	0.6
11	0.2	0.3	0.5
12	0.2	0.4	0.4
13	0.2	0.5	0.3
14	0.2	0.6	0.2
15	0.2	0.7	0.1
16	0.3	0.1	0.6
17	0.3	0.2	0.5
18	0.3	0.3	0.4
19	0.3	0.4	0.3
20	0.3	0.5	0.2
21	0.3	0.6	0.1
22	0.4	0.1	0.5
23	0.4	0.2	0.4
24	0.4	0.3	0.3
25	0.4	0.4	0.2
26	0.4	0.5	0.1
27	0.5	0.1	0.4
28	0.5	0.2	0.3
29	0.5	0.3	0.2
30	0.5	0.4	0.1
31	0.6	0.1	0.3
32	0.6	0.2	0.2
33	0.6	0.3	0.1
34	0.7	0.1	0.2
35	0.7	0.2	0.1
36	0.8	0.1	0.1

[1]	Shiying YAN, Kefei YAN, Wei FANG, Hengyang LU. Large-scale multi-objective algorithm based on neighborhood adaptive of differential evolution [J]. Systems Engineering and Electronics, 2022, 44(7): 2112-2124.
[2]	Qian LIU, Yunjun LU, Kebin CHEN, Mengyao HAN, Liang GUO. Combat task decomposition EVA method based on binary constraints of task subject [J]. Systems Engineering and Electronics, 2022, 44(7): 2201-2210.
[3]	Bo LI, Jiahao ZHOU, Minmin LIU, Pinchao ZHU. Feature selection for welding defect assessment based on improved NSGA3 [J]. Systems Engineering and Electronics, 2022, 44(7): 2211-2218.
[4]	Xudong SHI, Boyuan CHENG, Kun HUANG, Zhangang YANG. Risk assessment of aircraft IDG based on fuzzy TOPSIS-FMEA [J]. Systems Engineering and Electronics, 2022, 44(6): 2060-2064.
[5]	Zhiwei YANG, Xuexin XIE, Shuwan LI. Analysis of coherent processing capability of pulse width-FMpolarity agile waveform [J]. Systems Engineering and Electronics, 2022, 44(4): 1139-1147.
[6]	Yao TAN, Qian ZHAO, Wenfeng WANG, Bo GUO, Ping JIANG. Type I censored reliability acceptence test plan for Weibull distributed products by considering expert information [J]. Systems Engineering and Electronics, 2022, 44(4): 1409-1416.
[7]	Siyu DU, Yinghui QUAN, Minghui SHA, Wen FANG, Mengdao XING. Waveform optimization for SFA radar based on evolutionary particle swarm optimization [J]. Systems Engineering and Electronics, 2022, 44(3): 834-840.
[8]	Jinli MENG, Yafeng WANG, Jingbei YANG, Ning WANG. Spatial adaptive filtering of polarization agility jamming [J]. Systems Engineering and Electronics, 2022, 44(11): 3305-3312.
[9]	Shuxian DONG, Yinghui QUAN, Minghui SHA, Wen FANG, Mengdao XING. Frequency agile radar combined with intra-pulse frequency coding to resist intermittent sampling jamming [J]. Systems Engineering and Electronics, 2022, 44(11): 3371-3379.
[10]	Yantao WANG, Zheng YANG. Propagation and control improvement of flight operation risk network [J]. Systems Engineering and Electronics, 2021, 43(9): 2544-2552.
[11]	Liupengcheng YUAN, Zhemei FANG, Jianbo WANG, Xiaozhen QIN. CRC-MATE based method for system-of-systems architecture alternative selection [J]. Systems Engineering and Electronics, 2021, 43(8): 2146-2153.
[12]	Fan ZHU, Kai XIE. Analysis of the characteristic impedance of the transmission line under dual redundancy mechanism [J]. Systems Engineering and Electronics, 2021, 43(8): 2303-2310.
[13]	Rui ZHANG, Yinghui QUAN, Shengqi ZHU, Yachao LI, Mengdao XING. Microwave correlation imaging method based on improved OMP algorithm for sparse targets [J]. Systems Engineering and Electronics, 2021, 43(7): 1756-1765.
[14]	Rongwei CUI, Wei HAN, Xichao SU, Liguo WANG, Yujie LIU. Integrated optimization of carrier-based aircraft flight deck operations scheduling and resource configuration for pre-flight preparation stage [J]. Systems Engineering and Electronics, 2021, 43(7): 1884-1893.
[15]	Wen FANG, Yinghui QUAN, Minghui SHA, Zhixing LIU, Xia GAO, Mengdao XING. Dense false targets jamming suppression algorithm based on frequency agility and waveform entropy [J]. Systems Engineering and Electronics, 2021, 43(6): 1506-1514.