基于遗传算法的电子对抗作战实验寻优方法

作战仿真实验是评估电子对抗作战效能的理想方法,但在方案寻优时却面临实验方案"组合爆炸"的困难。对此,提出了将遗传算法引入作战实验寻优过程的求解思路。简要介绍了电子对抗作战仿真系统;分析了电子对抗作战方案拟制一般流程,建立了电子对抗作战方案优化模型,并给出了结合遗传算法和作战实验对其进行求解的原理和步骤;通过空袭作战电子对抗方案寻优的实例验证了方法的有效性。结果显示,本方法能够极大地提高寻优效率。     

Direct ink writing of 3D-Honeycombed CL-20 structures with low critical size

3D-Honeycombed CL-20 structures with low critical size of detonation have been fabricated successfully for intelligent weapon systems using a micro-flow direct ink writing (DIW) technology. The CL-20-based explosive ink for DIW technology was prepared by a two-component adhesive system with waterborne polyurethane (WPU) and ethyl cellulose (EC). Not only the preparation of the explosive ink but also the principle of DIW process have been investigated systematically. The explosive ink displayed strong shear-thinning behavior that permitted layer-by-layer deposition from a fine nozzle onto a substrate to produce complex shapes. The EC content was varied to alter the pore structure distribution and rheological behavior of ink samples after curing. The deposited explosive composite materials are of a honeycombed structure with high porosity, and the pore size distribution increases with the increase of EC content. No phase change was observed during the preparation process. Both WPU and EC show good compatibility with CL-20 particles. Apparently high activation energy was realized in the CL-20-based composite ink compared with that of the refined CL-20 due to the presence of non-energetic but stable WPU. The detonation performance of the composite materials can be precisely controlled by an adjustment in the content of binders. The 3D honeycombed CL-20 structures, which are fabricated by DIW technology, have a very small critical detonation size of less than 69 μm, as demonstrated by wedge shaped charge test. The ink can be used to create 3D structures with complex geometries not possible with traditional manufacturing techniques, which presents a bright future for the development of intelligent weapon systems.     

基于Solidworks二次开发的两栖车辆浮态设计及静稳性分析

建立了描述车辆姿态向量和重力向量的两个坐标系,研究了姿态向量与坐标变换之间的关系,根据Solid-Works提供的函数,利用二分法求解了给定姿态下的浮心位置;以浮心计算为基础,通过对车辆的受力分析和运动分析,确定了车辆浮态的计算方法;利用SolidWorks的API函数进行二次开发,形成了计算静稳性的程序,并进行了实例计算。结果表明：与传统的作图法相比较,该方法计算结果更精确,计算速度更快。     

基于计算机三维建模技术的两栖车辆静水性能计算

为了解决传统静水性能计算中倾斜浮态下浮心计算困难的问题,建立了两栖车辆的三维实体模型,研究了任意浮态下浮心的计算方法。在此基础上,求解了两栖车辆在静水平衡时的浮态,并利用SolidWorks提供的API函数进行二次开发,实现了计算的自动化。经实例验证表明,该算法准确、快速。     

空陆攻防博弈的动态武器目标分配

大规模作战具有高动态、非完全信息和不确定性，在分析归纳目前解决动态武器目标分配问题的一系列方法的基础上，尝试构建基于双方动态博弈的攻防对抗综合数学模型，并利用纳什均衡和帕累托最优算法进行分阶段求解。结果表明，该数学模型和博弈论方法结合能够有效解决武器目标动态分配问题。     

Shortest path interdiction problem with arc improvement recourse: A multiobjective approach

We consider the shortest path interdiction problem involving two agents, a leader and a follower, playing a Stackelberg game. The leader seeks to maximize the follower's minimum costs by interdicting certain arcs, thus increasing the travel time of those arcs. The follower may improve the network after the interdiction by lowering the costs of some arcs, subject to a cardinality budget restriction on arc improvements. The leader and the follower are both aware of all problem data, with the exception that the leader is unaware of the follower's improvement budget. The effectiveness of an interdiction action is given by the length of a shortest path after arc costs are adjusted by both the interdiction and improvement. We propose a multiobjective optimization model for this problem, with each objective corresponding to a different possible improvement budget value. We provide mathematical optimization techniques to generate a complete set of strategies that are Pareto‐optimal. Additionally, for the special case of series‐parallel graphs, we provide a dynamic‐programming algorithm for generating all Pareto‐optimal solutions.     

炮控伺服系统自抗扰控制器优化设计

针对自抗扰控制器参数难于整定的问题,给出了一种基于自适应变异粒子群优化算法的炮控伺服系统自抗扰控制器优化设计方法.该算法结构简单,具有良好的全局收敛性,充分发挥了自抗扰控制器的控制性能.通过对某炮控伺服系统的仿真研究,表明了该设计方法的有效性.     

炮兵火力任务分配的优化模型

现代作战,参战兵种多,炮兵的火力单位和类型更为复杂,不同的火力单位具有不同的毁伤效果,如何用最小的代价取得最大的军事效益,是一种火力任务分配的优化问题.根据不同炮种和目标的特点,建立在一定约束条件下的炮兵火力任务分配模型,并将其转化为指派问题,运用匈牙利算法求解,达到优化分配火力任务的目的.通过仿真计算证明这是辅助指挥员进行射击决策的一种有效手段,为作战指挥理论提供了一种新的数学模型.     

基于对抗演练的坦克单车成绩评定方法

为合理评定坦克分队对抗演练过程中各单车的操作技能,基于各单车在对抗过程中的相关数据特征,运用模糊聚类算法对单车对抗水平进行聚类分析,得出了各单车的等级评定成绩。提出了一种改进的ReliefF算法,将其差异明显、差距较大的属性特征分离,为坦克单车以及分队找出差距、制定日后训练重点提供了重要依据,并通过一实例阐明了此方法的实现步骤,验证了此方法的科学合理性。     

A worst‐case formulation for constrained ranking and selection with input uncertainty

In this research, we consider robust simulation optimization with stochastic constraints. In particular, we focus on the ranking and selection problem in which the computing time is sufficient to evaluate all the designs (solutions) under consideration. Given a fixed simulation budget, we aim at maximizing the probability of correct selection (PCS) for the best feasible design, where the objective and constraint measures are assessed by their worst‐case performances. To simplify the complexity of PCS, we develop an approximated probability measure and derive the asymptotic optimality condition (optimality condition as the simulation budget goes to infinity) of the resulting problem. A sequential selection procedure is then designed within the optimal computing budget allocation framework. The high efficiency of the proposed procedure is tested via a number of numerical examples. In addition, we provide some useful insights into the efficiency of a budget allocation procedure.