[an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive]
[an error occurred while processing this directive]

弹箭与制导学报 >

2025 , Vol. 45 >Issue 3: 330 - 335

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2025.03.009

综述、总体、动力、毁伤、测试及其他

规则约束的双种群协同进化联合火力打击任务规划

  • 刘建男 ,
  • 赵书圆 ,
  • 李冬
展开
  • 91550部队,辽宁 大连 116023
李冬(1983—),男,工程师,博士研究生。E-mail:

刘建男(1991—),男,助工,硕士。E-mail:

收稿日期: 2024-01-30

  网络出版日期: 2025-07-09

基金资助

国家自然科学基金(61703408)

收起

Rule Constrained Dual Population Co-evolutionary Joint Firepower Strike Mission Planning

  • LIU Jiannan ,
  • ZHAO Shuyuan ,
  • LI Dong
Expand
  • No.91550 Unit, Dalian 116023, Liaoning, China

Received date: 2024-01-30

  Online published: 2025-07-09

Fold

摘要

针对联合作战火力打击任务规划中存在求解空间大、约束复杂和易陷入局部最优的问题,提出了一种规则约束的双种群协同进化遗传算法。以四类战场作战规则为约束条件,设计具有规则约束的联合火力打击任务分配方案,增强了对复杂约束条件的适应性,构建基于目标排序和火力分配排序的双种群协同进化求解,提升了算法的性能和收敛速度。实验分析表明:该方法能够获取更高性能的可行解,具有较强的适用性和寻优能力,可以有效的降低作战成本。

关键词： 联合火力打击; 任务规划; 规则约束; 遗传算法

本文引用格式

刘建男 , 赵书圆 , 李冬 . 规则约束的双种群协同进化联合火力打击任务规划[J]. 弹箭与制导学报, 2025 , 45(3) : 330 -335 . DOI: 10.15892/j.cnki.djzdxb.2025.03.009

Abstract

A rule constrained dual population co-evolutionary genetic algorithm is proposed to address the problems of large solution space, complex constraints, and easy falling into local optima in joint combat firepower strike task planning. Design a joint firepower strike task allocation scheme with rule constraints based on four types of battlefield combat rules, enhance adaptability to complex constraint conditions, construct a dual population co evolutionary solution based on target sorting and firepower allocation sorting, and improve the performance and convergence speed of the algorithm. Experimental analysis shows that this method can obtain feasible solutions with higher performance, has strong applicability and optimization ability, and can effectively reduce fight cost.

Key words： joint firepower strike; task planning; rule constraints; genetic algorithm

[an error occurred while processing this directive]

参考文献

原文顺序 | 文献年度倒序 | 文中引用次数倒序
[1]
向勇. 联合火力打击中目标分配问题优化模型及算法研究[D]. 西安: 西安电子科技大学, 2019.

XIANG Y. Optimization model and algorithm research on target allocation in joint firepower strike[D]. Xi'an: Xi'an University of Electronic Science and Technology, 2019.

[2]
梁荣晓, 王春光, 纪秀美, 等. 联合火力打击智能化规划流程[J]. 指挥与控制学报, 2023, 9(4): 478-486.

LIANG R X, WANG C G, JI X M, et al. Intelligent planning process of joint fire strike[J]. Journal of Command and Control, 2023, 9(4): 478-486.

[3]
马悦, 吴琳, 郭圣明. 基于改进差分进化算法的作战目标分配[J]. 指挥控制与仿真, 2022, 44(4): 31-41.

DOI

MA Y, WU L, GUO S M. Operational targets assignment based on improved DE algorithm[J]. Command Control and Simulation, 2022, 44(4): 31-41.

[4]
MATLIN S. A review of the literature on the missile-allocation problem[J]. Operations Research, 1970, 18(2): 334-373.

[5]
KWON O, LEE K, KANG D H. A branch-and-price algorithm for a targeting problem[J]. Naval Research Logistics, 2007, 6(11): 32-41.

[6]
KARASAKAL O. Air defense missile-target allocation models for a naval task group[J]. Computers and Operations Research, 2008, 35(6): 1759-1770.

[7]
SCHMAEDEKE W. Information based sensor management[C]// Proceeding of SPIE Signal Processing, Sensor Fusion, and Target Recognition, Orlando: SPIE, 1993: 156-164.

[8]
柳毅, 佟明安. 匈牙利算法在多目标分配中的应用[J]. 火力与指挥控制, 2002, 27(4): 34-37.

LIU Y, TONG M A. Application of Hungarian algorithm in multi-objective allocation[J]. Fire and Command Control, 2002, 27(4): 34-37.

[9]
邢岩, 刘昊, 李保硕. 联合火力打击战法策略的智能进化方法研究[J]. 兵器装备工程学报, 2021, 42(9): 189-195.

XING Y, LIU H, LI B S. Research on intelligent evolution method of joint fire strike strategy[J]. Journal of Ordnance Equipment Engineering, 2021, 42(9): 189-195.

[10]
于博文, 吕明. 基于D-NSGA-GKM算法的多阶段武器协同火力分配方法[J]. 控制与决策, 2022, 37(3): 605-615.

YU B W, LYU M. Optimization method for multi-stage collaborative weapon firepower distribution based on D-NSGA-GKM algorithm[J]. Control and Decision, 2022, 37(3): 605-615.

[11]
王赞程, 贺筱媛. 基于CE-QPSO算法的联合火力打击方案智能优化方法[J]. 指挥控制与仿真, 2023, 45(5): 110-115.

DOI

WANG Z C, HE X Y. Intelligent optimization method of joint firepower strike plan based on CE-QPSO algorithm[J]. Command Control and Simulation, 2023, 45(5): 110-115.

[12]
伍国华, 李冰洁, 袁于斐, 等. 基于任务分解与强化学习的多平台协同火力分配方法[J]. 控制与决策, 2024, 39(5): 1727-1735.

WU G H, LI B J, YUAN Y F, et al. Multi platform collaborative firepower allocation method based on task decomposition and reinforcement learning[J]. Control and Decision, 2024, 39(5): 1727-1735.

[13]
刘昊, 谢鹏, 李玥. 联合火力打击中的多目标组合排序算法[J]. 兵工学报, 2020, 41(12): 2570-2578.

DOI

LIU H, XIE P, LI Y. Combined sorting algorithm for multi-target sorting in joint firepower strike[J]. Acta Armamentarii, 2020, 41 (12): 2570-2578.

DOI

[14]
王海峰, 高小军, 刘昊. 基于竞争蛙跳算法的联合火力打击任务规划方法[J]. 指挥控制与仿真, 2019, 41(4): 65-71.

DOI

WANG H F, GAO X J, LIU H. Joint firepower mission planning method based on competitive leapfrog algorithm[J]. Command Control and Simulation, 2019, 41(4): 65-71.

[15]
刘昊, 宋敬峰, 陈超. 基于进化粒子群算法的联合火力打击任务规划方法[J]. 舰船电子工程, 2020, 40(4): 21-26.

LIU H, SONG J F, CHEN C. Joint fire strike task planning method based on evolutionary particle swarm optimization algorithm[J]. Ship Electronics Engineering, 2020, 40(4): 21-26.

[16]
王光源, 李浩民, 陈永展, 等. 基于灰狼算法的多平台火力分配优化模型[J]. 科学技术与工程, 2023, 23(23): 10133-10138.

WANG G Y, LI H M, CHEN Y Z, et al. Multi-platform fire allocation optimization modelbased on gray wolf algorithm[J]. Science Technology and Engineering, 2023, 23(23): 10133-10138.

Options
文章导航

/

〈 〉

[an error occurred while processing this directive]