Research on Intelligent Optimization Method of Combat SoS Based on GABC Algorithm

doi:10.16182/j.issn1004731x.joss.21-0666

Abstract

Abstract:

In order to solve the problem that exploratory simulation can not traverse the solution space quickly, and provide the auxiliary decision-making scheme in real time, a genetic algorithm based on classifier is proposed. The framework of simulation optimization method based on the algorithm is established. It can find the optimal solution according to the dynamic changes of key factors and decision targets of the system, which is suitable for such as seeking the best efficiency-cost ratio scheme and the optimization of the optimal power deployment and other systems. Based on the simulation bed system of the National Defense University, experiments on fire blocking operations in a sea area are carried out. The power allocation problem is optimized by GABC (genetic algorithm based on classifier). The experiment shows that the method can find the most efficient and cost ratio scheme from the complex system constraints accurately and quickly, and can reduce the number of simulation experiments and meet the needs of quick assistant commander decision.

Key words: classifier, genetic algorithm, combat system, SoS optimization, simulation test bed

CLC Number:

TP391.9

Hucheng Zhang, Jingyu Yang. Research on Intelligent Optimization Method of Combat SoS Based on GABC Algorithm[J]. Journal of System Simulation, 2023, 35(1): 221-227.

Figures/Tables 8

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Table 1

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分类器	测试集准确率/%
决策树^[7]	100
线性SVM^[8]	75
POLY核函数SVM	100
RBF核函数SVM	50

实验编号	输入						输出		效果
实验编号	常导类型	飞机机型	舰艇弹药类型	常导数量(枚)	飞机数量(架)	舰艇数量(艘)	蓝方弹药消耗量(枚)	突防率/%	拦阻效果
1	常导2	飞机1	舰艇1	0	32	16	238	73	1
2	常导2	飞机1	舰艇1	12	0	0	63	70	0
…
35	常导1	飞机2	舰艇2	12	32	20	321	79	1
36	常导1	飞机2	舰艇2	24	0	4	164	59	0

序号	力量限制条件			决策目标		输出最优解(体系力量)			优化目标
序号	常导数量限制(枚)	飞机数量限制(架)	舰艇数量限制(艘)	预测拦阻效果	实际拦阻结果	常导数量(枚)	飞机数量(架)	舰艇数量(艘)	作战费用(无量纲)
1	60	40	20	1	1	8	27	9	568
2	30	40	20	1	1	0	32	9	544
3	60	20	20	1	1	7	20	13	632
4	60	40	10	1	1	15	32	5	538
5	30	20	10	0	0

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