Weapon-target Assignment Based on Adaptable Hungarian Algorithm

doi:10.3969/j.issn.1000-1093.2021.06.025

Abstract

Abstract: When various intelligent optimization algorithms are used to solve the weapon-target assignment problem, they have the disadvantages of long time-consuming and non-unique optimization results. Hungary algorithm has the advantages of short time-consuming and stable optimization results, but its adaptability is poor. Currently, the comparison and analysis of intelligent optimization algorithms and Hungarian algorithm has not been reported. For this phenomenon, the time-consuming and stability of traditional Hungarian algorithm and intelligent optimization algorithms are compared, which shows the advantages of Hungarian algorithm. An adaptable Hungarian algorithm that can be applied to all types of weapon-target assignment problems is established by proposing a unified efficiency matrix. And then some examples are used to verify the correctness of the adaptable Hungarian algorithm.

Key words: weapon-targetassignment, Hungarianalgorithm, integerprogramming, intelligentoptimizationalgorithm

CLC Number:

E911

ZHANG Jin， GUO Hao， CHEN Tong. Weapon-target Assignment Based on Adaptable Hungarian Algorithm[J]. Acta Armamentarii, 2021, 42(6): 1339-1344.

References

［1］陈曼, 周凤星. 改进粒子群算法的舰载武器目标分配[J]. 火力与指挥控制, 2018, 43(11):72-76.
CHEN M, ZHOU F X. Shipborne weapon-target assignment based on improved particle swarm optimization[J]. Fire Control & Command Control, 2018, 43(11):72-76. (in Chinese)
[2］黄大山, 徐克虎, 王天召. 求解WTA问题的智能算法评价准则[J]. 火力与指挥控制, 2013, 38(8):43-46.
HUANG D S, XU K H, WANG T Z. An evaluation criteria for intelligent algorithm in solving weapon target assignment problem [J]. Fire Control & Command Control, 2013, 38(8):43-46. (in Chinese)
[3］杨飞, 王青, 侯砚泽. 基于整数域改进粒子群优化算法的多平台武器目标分配[J]. 兵工学报, 2011, 32(7):906-912.
YANG F, WANG Q, HOU Y Z. Weapon-target assignment in multi-launcher system based on improved integer field particle swarm optimization algorithm[J]. Acta Armamentarii, 2011, 32(7): 906-912. (in Chinese)
[4］董朝阳, 路遥, 王青. 改进的遗传算法求解火力分配优化问题[J]. 兵工学报, 2016, 37(1):97-102.
DONG C Y, LU Y, WANG Q. Improved genetic algorithm for solving firepower distribution[J]. Acta Armamentarii, 2016, 37(1): 97-102. (in Chinese)
[5］刘家义, 王刚, 张杰, 等. 基于改进AGD-分布式多智能体系统的目标优化分配模型[J]. 系统工程与电子技术, 2020, 42(4): 863-870.
LIU J Y, WANG G, ZHANG J, et al. Target optimal assignment model based on improved AGD-distributed multi-agent system[J]. Systems Engineering and Electronics, 2020, 42(4):863-870. (in Chinese)
[6］杨进帅, 李进, 王毅. 武器-目标分配问题研究[J]. 火力与指挥控制, 2019, 44(5):6-11.
YANG J S, LI J, WANG Y. Study of weapon target assignment problem[J]. Fire Control & Command Control, 2019, 44(5):6-11. (in Chinese)
[7］李廷鹏, 钱彦岭, 李岳. 基于改进匈牙利算法的多技能人员调度方法[J]. 国防科技大学学报, 2016, 38(2):144-149.
LI T P, QIAN Y L, LI Y. Multi-skilled labor allocating method based on improved Hungary algorithm[J]. Journal of National University of Defense Technology, 2016, 38(2):144-149. (in Chinese)
[8］ ZHU H B, LIU D N, ZHANG S Q, et al. Solving the many to many assignment problem by improving the Kuhn-Munkres algorithm with backtracking[J]. Theoretical Computer Science, 2016, 618:30-41.
[9］ CHOPRA S, NOTARSTEFANO G, RICE M, et al. A distributed version of the Hungarian method for multirobot assignment[J]. IEEE Transactions on Robotics, 2017, 33(4):932-947.
[10］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. An application of Hungarian algorithm to the multi-target assignment[J]. Fire Control & Command Control, 2002, 27(4):34-37. (in Chinese)
[11］谷稳. 基于进化匈牙利算法的目标分配问题研究及应用[D]. 西安：西安电子科技大学, 2013.
GU W. Study and application of target allocation based on evolution Hungarian algorithm[J]. Xi'an: Xi'an University of Electronic Science and Technology, 2013. (in Chinese)
[12］李元左, 杨晓段. 炮兵火力分配建模及优化方法[J]. 指挥控制与仿真, 2015, 37(2):48-52.
LI Y Z, YANG X D. Optimal assignment model of artillery firepower[J]. Command Control & Simulation, 2015, 37(2):48-52. (in Chinese)
[13］ KUHN H W. The Hungarian method for the assignment problem[J]. Naval Research Logistics Quarterly, 1955, 2(1):83-97.
[14］ BOURGEOIS F, LASSALLE J. An extension of the Munkres algorithm for the assignment problem to rectangular matrices[J]. Communications of the ACM, 1971, 14(12):802-804.
[15］陈彬, 韩林, 余旺盛, 等. 基于改进遗传算法的装备调配[J]. 系统工程, 2010, 28(9):98-102.
CHEN B, HAN L, YU W S, et al. Equipment distribution based on modified genetic algorithm[J]. Systems Engineering, 2010, 28(9):98-102. (in Chinese)
[16］孙晓雅, 林焰. 一种新的离散粒子群算法在指派问题中的应用[J]. 计算机应用研究, 2009, 26(11):4091-4093,4097.
SUN X Y, LIN Y. Using new DPSO algorithm to solve assignment problem[J]. Application Research of Computers, 2019, 26(11): 4091-4093,4097. (in Chinese)

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