基于改进AGD-分布式多智能体系统的目标优化分配模型  

Target optimal assignment model based on improved AGD-distributed multi-Agent system

作　　者：刘家义 王刚[1] 张杰 王闯 宋喜团 LIU Jiayi;WANG Gang;ZHANG Jie;WANG Chuang;SONG Xituan(Air and Missile Defense College,Air Force Engineering University,Xi'an 710051,China;Graduate College,Air Force Engineering University,Xi'an 710051,China;Unit 93453 of the PLA,Shuozhou 038300,China)

机构地区：[1]空军工程大学防空反导学院,陕西西安710051 [2]空军工程大学研究生院,陕西西安710051 [3]中国人民解放军93453部队,山西朔州038300

出　　处：《系统工程与电子技术》2020年第4期863-870,共8页Systems Engineering and Electronics

基　　金：国家自然科学基金青年科学基金项目（61703412）;中国博士后科学基金资助（2016M602996）资助课题

摘　　要：由于现代化战场环境动态多变、作战实时性高,针对当前防空作战中武器目标分配(weapon target assignment,WTA)约束多且复杂、传统建模无法真实反映战争过程、模型可信度不高等问题,提出一种在分布式约束优化问题(distributed constraint optimization problem,DCOP)背景下,基于多智能体系统(multi-Agent system,MAS)理论的武器目标优化分配模型,并利用改进的加速梯度下降(accelerated gradient descent,AGD)算法进行求解。通过实验证明了该算法具有良好的收敛性和低复杂度,能够适应现代化防空作战的需求,满足大规模寻优问题的需求,高效解决多智能体目标优化分配问题。Because the modern battlefield environment is dynamic and the tasks are fulfilled in real-time,in view of the fact that the target allocation of weapons targets in current air defense operations is complex,traditional modeling cannot truly reflect the war process,with low confidence in the model,a weapon target assignment(WTA)model based on multi-Agent system(MAS)theory and distributed constrained optimization problem(DCOP)is proposed,and the improved accelerated gradient descent(AGD)algorithm is used to solve the model.The experiment proves that the algorithm has good convergence and low complexity,can adapt to the needs of modern air defense operations,meet the needs of large-scale optimization problems,and efficiently solve the problem of optimal allocation of multi-Agent targets.

关 键 词：多智能体系统 分布式约束优化问题 武器目标分配 加速梯度下降 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]