摘要
综合考虑雷场费效因素、多目标打击、目标撤退等因素,建立非线性作战方案规划模型,利用遗传算法迭代求解最优作战方案。通过Matlab仿真对比不同毁伤次数、毁伤代价、智能雷布设密度条件下智能雷场对坦克的毁伤效能,确定最优方案。仿真结果表明:采用遗传算法进行最优化迭代求解的作战方案可以有效提高雷场作战效能,指导智能雷场对坦克实施准确打击,确定反坦克智能雷场合理布雷密度。
Considering the factors such as minefield cost-effectiveness factor,multi-target strike,target retreat and other factors,the nonlinear warfare plan planning model was established,and the genetic algorithm was used to solve the optimal warfare scheme.Through Matlab simulation,the damage effectiveness of intelligent minefields on tanks under different damage times,damage costs and intelligent mine density was compared,and the optimal scheme was determined.Simulation results show that the operational scheme using genetic algorithm can effectively improve the combat effectiveness of minefields,and the intelligent minefield can be guided to accurately strike the tank.and to guide how to carry out the mine of density in the anti-tank intelligent minefield.
作者
王静
刘立芳
齐小刚
WANG Jing;LIU Lifang;QI Xiaogang(School of Computer Science and Technology,Xidian University, Xi'an 710071, China;School of Mathematics and Statistics,Xidian University, Xi’an 710071, China)
出处
《兵器装备工程学报》
CAS
北大核心
2019年第6期51-56,共6页
Journal of Ordnance Equipment Engineering
基金
国家自然科学基金项目(61877067
61572435)
西安市科技创新项目(201805029YD7CG13-6)
关键词
智能雷场
作战效能
遗传算法
作战方案
intelligent minefield
operational effectiveness
genetic algorithm
operational scheme
