Modeling and Optimization Method of Kill Chains Based on AGE-MOEA

doi:10.12382/bgxb.2023.0566

Abstract

Abstract:

A modeling and optimization method of kill chains based on adaptive geometry estimation-based multi-objective evolutionary algorithm (AGE-MOEA ) is proposed for the kill-chains design. Based on the idea of kill chain closure, the OODA cycle theory and the traditional weapon target assignment model, a multi-objective optimization mathematical model of kill chains design is constructed to realize the mathematical representation of kill chains design problem. The proposed model comprehensively considers three kinds of equipment, which are used for reconnaissance, command and attack, respectively, and takes the maximum attack efficiency, minimum weapon consumption and minimum damage threat as the objective functions, and takes the equipment use constraints, kill chain relation constraints and damage threshold constraints as constraint conditions. The algorithm flow of kill chains optimization design based on AGE-MOEA is proposed to solve the multi-objective optimization mathematical model of kill chains design. Through the numerical experiments and the kill chain design experiments in air defense and anti-missile combat scenarios, the results show that the proposed method can simultaneously pursue the optimization of attack efficiency, weapon consumption and damage threat on the premise of ensuring that all kill chains of each target are closed, and obtain a kill chain solution, which can form a distributed lethality. The scientificity of multi-objective optimization mathematical model of kill chains design, the effectiveness of AGE-MOEA algorithm in solving kill chains design problems and the feasibility of kill chain design method in practical military operations are verified.

Key words: kill chain, kill web, OODA loop, multi-objective optimization

CLC Number:

E917

WAN Silai, WANG Guoxin, MING Zhenjun, LI Chuanhao, YAN Yan, DING Wei, YUAN Ke, WANG Yuqian. Modeling and Optimization Method of Kill Chains Based on AGE-MOEA[J]. Acta Armamentarii, 2024, 45(8): 2617-2628.

Figures/Tables 13

References 33

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装备阵营	参数	取值
	装备精度	[0.8,0.9]中取随机数
	弹药成本	[100,200]中取随机数
我方	装备成本	[400,600]中取随机数
	多目标能力	侦察:2;指控:8
	通信矩阵	[0,1]中取随机数
	指控矩阵	[0,1]中取随机数
	目标价值	[600,800]中取随机数
敌方	威胁度	[0.8,0.9]中取随机数
	毁伤门限	[0.4,0.6]中取随机数

装备阵营	参数	取值
	装备精度	[0.8,0.9]中取随机数
	弹药成本	[100,200]中取随机数
我方	装备成本	[400,600]中取随机数
	多目标能力	侦察:2;指控:8
	通信矩阵	[0,1]中取随机数
	指控矩阵	[0,1]中取随机数
	目标价值	[600,800]中取随机数
敌方	威胁度	[0.8,0.9]中取随机数
	毁伤门限	[0.4,0.6]中取随机数

算法	打击效能目标	弹药消耗目标	损毁威胁目标
AGE-MOEA	11193	2655	10141
SGA-Ⅱ	11182	2709	10499
NSGA-Ⅲ	11187	2703	10165

算法	打击效能目标	弹药消耗目标	损毁威胁目标
AGE-MOEA	11193	2655	10141
SGA-Ⅱ	11182	2709	10499
NSGA-Ⅲ	11187	2703	10165

装备类型	装备编号	数量	单元编号	装备精度	弹药成本/美元	装备成本/美元	多目标能力
侦察装备	Radar_A(SAM)	2	Radar_A_1、Radar_A_2	0.92		4000	4
	Radar_B(SAM)	2	Radar_B_1、Radar_B_2	0.94		6000	6
指控装备	指控中心(SAM)	2	指控中心_1、指控中心_2	0.95		9000	8
	Missile_A(SAM)	12	Missile_A_1~Missile_A_12	0.88	300
打击装备	Missile_B(SAM)	12	Missile_B_1~Missile_B_12	0.95	500
	Missile_C(Fighter)	8	Missile_B_1~Missile_B_8	0.9	400