摘要
作战任务系统是调度指挥和协同控制的有机结合。系统的整体性、可靠性不仅取决于系统所利用的最优控制算法,还取决于战场资源的合理调度组合。融入相关约束条件及组合搭配方案能更好达到组织的协调控制。传统遗传算法存在早熟收敛、陷入局部最优等问题,对此提出聚类组合方式、关联作战因素的适应度函数及目标模型、二维关联编码方法等改进方法。仿真结果表明,该方法在保证系统稳定性的前提下,能较好地对平台设备进行组合,加快了算法的收敛速度、优化了模型的目标函数,提高了不同作战任务规模下的实效性。
Combat mission system is an organic combination of scheduling command and collaborative control.The integrity and reliability of the system depend not only on the optimal control algorithm used by the system,but also on the reasonable scheduling combination of battlefield resources.Integrating relevant constraints and combination schemes can better achieve the coordination and control of the organization.The traditional genetic algorithm has problems such as premature convergence and local optimization.This paper proposes some improved methods,such as clustering combination mode,combat capability fitness function and target model,two-dimensional correlation coding method and so on.The simulation results show that this method can better combine the platform equipment on the premise of ensuring the system stability,accelerate the convergence speed of the algorithm,optimize the objective function of the model,and improve the effectiveness under different combat mission scales.
作者
李嘉伦
王鹏
吕志刚
李晓艳
付博雯
Li Jialun;Wang Peng;LüZhigang;Li Xiaoyan;Fu Bowen(School of Electronics Information Engineering,Xi’an Technological University,Xi’an 710021,Shaanxi,China)
出处
《计算机应用与软件》
北大核心
2022年第2期55-62,共8页
Computer Applications and Software
基金
国家自然科学基金项目(61671362)
陕西省科技厅重点研发计划项目(2019GY-022,2019GY-066)。
关键词
改进遗传算法
资源调度约束
作战调度模型
作战关联适应度函数
Improved genetic algorithm
Resource scheduling constraint
Operational scheduling mode
Fitness function of combat capability
