基于滚动优化结构的行动过程实时决策方法

doi:10.12305/j.issn.1001-506X.2025.03.22

系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (3): 904-911.doi: 10.12305/j.issn.1001-506X.2025.03.22

• 系统工程 • 上一篇

基于滚动优化结构的行动过程实时决策方法

黄冬¹, 刘钢¹, 江雪云², 刘立志¹, 郭金林³^,*

1. 湖南理工学院信息科学与工程学院, 湖南岳阳 414006
2. 武汉船舶通信研究所, 湖北武汉 430010
3. 国防科技大学系统工程学院, 湖南长沙 410003

收稿日期:2024-04-07 出版日期:2025-03-28 发布日期:2025-04-18
通讯作者: 郭金林
作者简介:黄冬 (1990—), 男, 讲师, 博士, 主要研究方向为复杂系统建模、优化与决策
刘钢 (1983—), 男, 副教授, 博士, 主要研究方向为智能信息处理、协同航路规划
江雪云 (1989—), 女, 工程师, 硕士, 主要研究方向为船舶通信总体设计
刘立志 (1994—), 男, 讲师, 博士, 主要研究方向为非线性系统、复杂动态网络分析与控制
郭金林 (1983—), 男, 教授, 博士, 主要研究方向为复杂系统建模、机器学习和多媒体信息处理
基金资助:
湖南省自然科学基金青年项目(2023JJ40306);湖南省自然科学基金面上项目(2024JJ5173);湖南省自然科学基金面上项目(2024JJ7223);湖南省教育厅科学研究优秀青年项目(20B260);湖南省教育厅科学研究优秀青年项目(23B0646);湖南省教育厅科学研究重点项目(23A0494)

Method of real-time decision for course of action based on recursive optimization structure

Dong HUANG¹, Gang LIU¹, Xueyun JIANG², Lizhi LIU¹, Jinlin GUO³^,*

1. School of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang 414006, China
2. Wuhan Institute of Ship Communication, Wuhan 430010, China
3. College of Systems Engineering, National University of Defense Technology, Changsha 410003, China

Received:2024-04-07 Online:2025-03-28 Published:2025-04-18
Contact: Jinlin GUO

摘要/Abstract

摘要：

为应对现代战争中作战环境的不确定性问题, 指挥员需具备实时优化作战行动过程(course of action, COA)的能力和手段, 保证态势变化条件下的作战效能。本文考虑作战持续过程中战场态势变化、指挥员意图介入等因素, 采用基于贝叶斯网络的行动过程建模, 研究反馈机制下的COA实时滚动优化策略, 有效提升行动方案的适用性。通过仿真案例分析可知, 滚动优化结构所生成的COA方案评价得分能够在单次优化的基础上提高15%以上, 表明滚动优化结构的COA实时决策方法, 能够克服复杂作战环境下战场态势和指挥员意图的实时变化影响, 保证行动方案的全过程持续最优。

关键词: 实时决策, 行动过程, 滚动优化, 态势反馈

Abstract:

Because of the uncertainty for the battlefield environment in modern warfare, it is necessary for commanders to obtain the optimal course of action (COA) in real-time and ensure the combat effectiveness under the condition of situation changes. Considering the factors such as the battlefield situation changes and the command intention intervention during the warfare process, by employing Bayesian network model of COA, this paper studies the real-time recursive optimization method of COA under feedback system, which effectively improves the applicability of action scheme. Through the simulation case analysis, it can be seen that the evaluation score of COA scheme generated by recursive optimization structure can be increased by more than 15% on the basis of normal optimization. The result indicates that the influences of battlefield situation changes and the command intention intervention have been overcome by the recursive optimization of COA under complex combat environment, and the optimality has been ensured in the whole combat process.

Key words: real-time decision, course of action (COA), recursive optimization, situation feedback

中图分类号:

E917

黄冬, 刘钢, 江雪云, 刘立志, 郭金林. 基于滚动优化结构的行动过程实时决策方法[J]. 系统工程与电子技术, 2025, 47(3): 904-911.

Dong HUANG, Gang LIU, Xueyun JIANG, Lizhi LIU, Jinlin GUO. Method of real-time decision for course of action based on recursive optimization structure[J]. Systems Engineering and Electronics, 2025, 47(3): 904-911.

图/表 9

图1

图2

图3

图4

表1

基于因果关系模型生成的可行COA"

序号	COA序列
1	$\left\|\left.\begin{aligned}& t_0 \\& a_4^3 \vee a_5^3 \vee a_6^3\end{aligned} \Rightarrow\left\|\begin{array}{l}t_1 \\a_2^3 \vee a_3^3\end{array} \Rightarrow\right\| \begin{aligned}& t_2 \\& a_1^3\end{aligned} \Rightarrow\left\|\begin{array}{l}t_3 \\a_7^1\end{array} \Rightarrow\right\| \begin{aligned}& t_4 \\& a_4^1 \vee a_5^1\end{aligned} \Rightarrow \right\rvert\, \begin{aligned}& t_5 \\& a_8^1 \vee a_9^1\end{aligned}\right.$
2	$\left\|\begin{array}{l\|l\|l\|l}t_0 \\a_4^3\end{array} \Rightarrow\right\| \begin{aligned}& t_1 \\& a_2^3 \vee a_5^2\end{aligned} \Rightarrow\left\|\begin{array}{l}t_2 \\a_1^3 \vee a_6^1\end{array} \Rightarrow\right\| \begin{aligned}& t_3 \\& a_7^1\end{aligned} \Rightarrow\left\|\begin{array}{l}t_4 \\a_4^1 \vee a_5^1\end{array} \Rightarrow\right\| \begin{aligned}& t_5 \\& a_8^1 \vee a_9^1\end{aligned}$
3	$\left.\left\|\begin{array}{l}t_0 \\a_4^3 \vee a_5^2 \vee a_6^2\end{array} \Rightarrow\right\| \begin{aligned}& t_1 \\& a_2^3\end{aligned} \Rightarrow\left\|\begin{array}{l}t_2 \\a_1^3\end{array} \Rightarrow \left\|\begin{array}{l}t_3 \\a_7^1\end{array}\right. \Rightarrow\right\| \begin{aligned}& t_4 \\& a_5^1 \vee a_6^1\end{aligned} \Rightarrow \right\rvert\, \begin{aligned}& t_5 \\& a_8^1 \vee a_9^1\end{aligned}$
4	$\left.\left\|\begin{array}{l\|l\|l\|l\|l}t_0 \\a_5^4\end{array} \Rightarrow\right\| \begin{aligned}& t_1 \\& a_4^2 \vee a_6^2\end{aligned} \Rightarrow\left\|\begin{array}{l}t_2 \\a_2^3 \vee a_1^3\end{array} \Rightarrow\right\| \begin{aligned}& t_3 \\& a_7^1\end{aligned} \Rightarrow \right\rvert\, \begin{aligned}& t_4 \\& a_5^1 \vee a_8^2\end{aligned} \Rightarrow \left\|\begin{aligned}& t_5 \\& a_9^1\end{aligned}\right.$
5	$\left.\left\|\begin{array}{l\|l\|l\|l\|l}t_0 \\a_5^4 \vee a_6^3\end{array} \Rightarrow\right\| \begin{aligned}& t_1 \\& a_4^1\end{aligned} \Rightarrow\left\|\begin{array}{l}t_2 \\a_2^3 \vee a_1^2\end{array} \Rightarrow\right\| \begin{aligned}& t_3 \\& a_7^1 \vee a_4^1\end{aligned} \Rightarrow \right\rvert\, \begin{aligned}& t_4 \\& a_5^1 \vee a_8^2\end{aligned} \Rightarrow \left\|\begin{aligned}& t_5 \\& a_9^1\end{aligned}\right.$

表1

表2

表3

表4

图5

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序号	COA序列
1	$\left\|\left.\begin{aligned}& t_0 \\& a_4^3 \vee a_5^3 \vee a_6^3\end{aligned} \Rightarrow\left\|\begin{array}{l}t_1 \\a_2^3 \vee a_3^3\end{array} \Rightarrow\right\| \begin{aligned}& t_2 \\& a_1^3\end{aligned} \Rightarrow\left\|\begin{array}{l}t_3 \\a_7^1\end{array} \Rightarrow\right\| \begin{aligned}& t_4 \\& a_4^1 \vee a_5^1\end{aligned} \Rightarrow \right\rvert\, \begin{aligned}& t_5 \\& a_8^1 \vee a_9^1\end{aligned}\right.$
2	$\left\|\begin{array}{l\|l\|l\|l}t_0 \\a_4^3\end{array} \Rightarrow\right\| \begin{aligned}& t_1 \\& a_2^3 \vee a_5^2\end{aligned} \Rightarrow\left\|\begin{array}{l}t_2 \\a_1^3 \vee a_6^1\end{array} \Rightarrow\right\| \begin{aligned}& t_3 \\& a_7^1\end{aligned} \Rightarrow\left\|\begin{array}{l}t_4 \\a_4^1 \vee a_5^1\end{array} \Rightarrow\right\| \begin{aligned}& t_5 \\& a_8^1 \vee a_9^1\end{aligned}$
3	$\left.\left\|\begin{array}{l}t_0 \\a_4^3 \vee a_5^2 \vee a_6^2\end{array} \Rightarrow\right\| \begin{aligned}& t_1 \\& a_2^3\end{aligned} \Rightarrow\left\|\begin{array}{l}t_2 \\a_1^3\end{array} \Rightarrow \left\|\begin{array}{l}t_3 \\a_7^1\end{array}\right. \Rightarrow\right\| \begin{aligned}& t_4 \\& a_5^1 \vee a_6^1\end{aligned} \Rightarrow \right\rvert\, \begin{aligned}& t_5 \\& a_8^1 \vee a_9^1\end{aligned}$
4	$\left.\left\|\begin{array}{l\|l\|l\|l\|l}t_0 \\a_5^4\end{array} \Rightarrow\right\| \begin{aligned}& t_1 \\& a_4^2 \vee a_6^2\end{aligned} \Rightarrow\left\|\begin{array}{l}t_2 \\a_2^3 \vee a_1^3\end{array} \Rightarrow\right\| \begin{aligned}& t_3 \\& a_7^1\end{aligned} \Rightarrow \right\rvert\, \begin{aligned}& t_4 \\& a_5^1 \vee a_8^2\end{aligned} \Rightarrow \left\|\begin{aligned}& t_5 \\& a_9^1\end{aligned}\right.$
5	$\left.\left\|\begin{array}{l\|l\|l\|l\|l}t_0 \\a_5^4 \vee a_6^3\end{array} \Rightarrow\right\| \begin{aligned}& t_1 \\& a_4^1\end{aligned} \Rightarrow\left\|\begin{array}{l}t_2 \\a_2^3 \vee a_1^2\end{array} \Rightarrow\right\| \begin{aligned}& t_3 \\& a_7^1 \vee a_4^1\end{aligned} \Rightarrow \right\rvert\, \begin{aligned}& t_4 \\& a_5^1 \vee a_8^2\end{aligned} \Rightarrow \left\|\begin{aligned}& t_5 \\& a_9^1\end{aligned}\right.$

方案序号	评价得分
1	92.08
2	89.23
3	92.67
4	93.50
5	88.92

时间点	态势/意图变化	最优COA
时间点	态势/意图变化	一次优化	滚动优化
t₀	-	a₅⁴	a₅⁴
t₁	蓝方岸防部队增援	a₄⁴	a₄⁴∨a₆³
t₂	蓝方空中火力增援	a₂³∨a₁²	a₂³∨a₁³
t₃	红方指挥员作战效能优先	a₇¹	a₇¹∨a₆⁰
t₄	红方舰艇增援	a₈²	a₅¹
t₅	-	a₉¹	a₈¹∨a₉¹

时间点	态势/意图变化	COA评价
时间点	态势/意图变化	一次优化	滚动优化
t₀~t₁	-	94.8	94.8
t₁~t₂	蓝方岸防部队增援	80.3	93.0
t₂~t₃	蓝方空中火力增援	73.2	91.9
t₃~t₄	红方指挥员作战效能优先	70.5	92.6
t₄~t₅	红方舰艇增援	84.0	94.6
平均评价得分		80.5	93.4

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基于滚动优化结构的行动过程实时决策方法

Method of real-time decision for course of action based on recursive optimization structure

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