Confrontation-based Cooperative Fire Strike Decision-making Method of Assault Weapons and Support Weapons

被引：0
|
作者：
Kong D. [1 ]
Chang T. [1 ]
Hao N. [1 ]
Zhang L. [1 ]
Guo L. [1 ]
机构：
[1] Department of Weaponry and Control, Army Academy of Armored Forces, Beijing
来源：
Binggong Xuebao/Acta Armamentarii | 2019年 / 40卷 / 03期
关键词：
Artificial bee colony algorithm; Assault weapon; Cooperative fire strike; Decision-making; Support weapon; Weapon-target assignment;
D O I：
10.3969/j.issn.1000-1093.2019.03.023
中图分类号：
学科分类号：
摘要：
A decision-making method for the cooperative fire strike (CFS) of assault weapons and support weapons in confrontation is proposed. And a decision-making model for CFS is established based on the ratio of friend or foe's residual values by studying the "point to point" strike of assault weapons and the "area damage" of long-range firepower support weapons, and the optimization process of decision-making of fire strike is considered. The decision of the assault weapons attacking the targets, the decision of the targets attacking the assault weapons and the drop points of projectiles launched from supporting weapons are taken as the optimization variables in decision-making model. A two-level iterative optimization method based on artificial bee colony (ABC) algorithm is proposed to solve the CFS decision-making optimization model. The integer is used to encode the decision variables, and the penalty function method is used to deal with the constraints. The decision-making model is transformed into an unconstrained mixed integer optimization problem. In view of the implementation process of the proposed algorithm, the computational complexity of the two-level iterative ABC algorithm is analyzed. A CFS example is used to verify the rationality and effectiveness of the collaborative fire strike decision-making model and the solving algorithm. © 2019, Editorial Board of Acta Armamentarii. All right reserved.
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页码：629 / 640
页数：11
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