具有多次拦截时机的防空火力分配建模及其优化方法研究  

Modeling and Optimization on Antiaircraft Weapon-target Assignment at Multiple Interception Opportunity

作　　者：张蛟[1,2] 王中许[2] 陈黎[2] 武兆斌[2] 陆建锋[1] 

机构地区：[1]南京理工大学计算机科学与工程学院 [2]中国人民解放军63961部队

出　　处：《兵工学报》2014年第10期1644-1650,共7页Acta Armamentarii

基　　金：中国博士后科学基金项目(2012M521833)

摘　　要：防空火力分配采用一次性完全分配原则容易造成火力资源浪费,针对该问题,以来袭目标到火力单元的飞临时间为依据,筛选出具有多次拦截时机的火力单元组,并按照拦截时机的先后顺序逐步释放火力单元,以毁伤概率为优化目标,同时兼顾火力资源消耗,建立了一种具有多次拦截时机的防空火力分配模型。在此基础上,采用混沌离散粒子群混合优化(CDPSO)算法对模型进行求解,以提高算法的全局搜索能力,避免陷入局部极值。通过仿真验证了模型及算法的合理性和有效性,为防空火力分配问题的求解提供了一条新思路。In antiaircraft weapon-target assignment,the weapon resources could be wasted if all weapons are fully assigned at a time. In view of this situation,a weapon-target assignment model of multiple interception opportunity is proposed. The model is used to screen the weapon groups for multiple interception based on flying time of target approaching to a weapon unit,and the weapon units in the weapon group intercept the target according to the time order. The model not only optimizes the target damage probability,but also considers the consumption of weapon resources. Based on the model,a mixed chaos and discrete particle swarm optimization algorithm is presented to solve the weapon-target assignment problem. The proposed algorithm improves the seeking ability for the global optimal solution so that the local extremum is avoided. Simulation results show the rationality of the weapon-target assignment model and the effectiveness of the proposed mixed optimization algorithm,which is a new thought for antiaircraft weapon-target assignment.

关 键 词：兵器科学与技术 整数规划 火力分配 多次拦截时机 混沌优化 离散粒子群优化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]