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作 者:常雪凝 石建迈[1] 陈超[1] 黄金才[1] CHANG Xuening;SHI Jianmai;CHEN Chao;HUANG Jincai(School of Systems Engineering,National University of Defense Technology,Changsha 410003,China)
机构地区:[1]国防科技大学系统工程学院,湖南长沙410003
出 处:《系统工程与电子技术》2023年第11期3507-3514,共8页Systems Engineering and Electronics
基 金:国家自然科学基金面上项目(71771215);军科委基础加强基金(2019-JCJQ-JJ-215)资助课题
摘 要:针对现代化战争中远程精确制导武器成本高昂以及武器发射平台数量有限的问题,研究了多阶段武器目标分配问题,以最小化武器成本为优化目标,建立了混合整数非线性规划模型。设计了一种集成匈牙利和模拟退火的混合智能搜索算法,首先根据待攻击目标的时空状态与毁伤特性确定打击阶段、标记可松弛性。在模拟退火的框架下,基于目标的松弛性调整攻击阶段,再通过匈牙利算法计算每个阶段武器和目标的精确匹配方案。通过启发式算法和精确求解技术的结合,在保证求解质量的前提下,极大减少了计算时间。通过计算实验,与变邻域搜索算法进行了对比分析,验证了该算法在求解多阶段武器目标分配问题的有效性。仿真结果表明,所提算法在计算时间和求解效果上优于变邻域搜索算法。Aimed at the high cost of long-range precision-guided weapons and the limited number of weapon launch platforms in modern warfare,the multi-stage weapon target assignment(MS-WTA)problem is studied,and a mixed-integer nonlinear programming model is established to minimize the cost of weapons.A hybrid intelligent search algorithm integrating Hungarian and simulated annealing(HSA)is designed.Firstly,the hit stage and mark relaxation are determined according to the spatio-temporal state and damage characteristics of the target to be attacked.Under the framework of simulated annealing,the attack stage is adjusted based on the target’s relaxation,and then the accurate matching scheme of weapons and targets in each stage is calculated by Hungarian algorithm.By combining heuristic algorithms and precise solving techniques,the calculation time is greatly reduced while ensuring the quality of the solution.Through computational experiments and comparative analysis with the variable neighborhood search algorithm,the effectiveness of this algorithm in solving MS-WTA problems is verified.The simulation results show that the proposed algorithm outperforms the variable neighborhood search algorithm in terms of computational time and solution performance.
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