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.     

一种基于蚁群算法的准动态防空武器分配算法

武器目标分配问题是一个典型的限制组合优化问题,旨在得到在整个防御阶段中针对目标函数的最优武器分配方案。分配算法主要分为静态和动态两大类。针对传统静态分配模型中存在的几点问题,提出了基于时间窗的准动态武器目标分配算法,该算法综合考虑拦截概率、拦截时间和武器耗费多个优化指标,并将该算法推广至多类防空武器的优化分配中。通过大量实验验证,该算法在性能、时间复杂度等方面均有较大优势,并且能较好地适应战场态势的变化,及时调整分配方案,具有很好的实用性。     

某型末制导炮弹偏流的分析与计算

针对某型激光半主动式末制导炮弹偏流问题，基于考虑末制导炮弹各个典型弹道飞行阶段的刚体弹道模型，通过仿真计算，分析该末制导炮弹偏流的基本特点；探讨偏流形成的原因，确定影响其大小的关键因素，并对计算偏流所需要的数值积分时间步长进行了探讨。有关结论对准确编拟末制导炮弹射表所需要的偏流有直接应用价值，对新型末制导炮弹的弹道设计有积极的指导意义。     

船艇发动机虚拟维修中的场景优化技术研究

针对船艇发动机虚拟维修场景构建过程中模型的高逼真度和实时交互之间的矛盾,提出了降低场景复杂度的初期建模优化技术,以及模型合成后的全景优化技术。通过在发动机虚拟维修训练系统中的综合应用,有效地简化了模型的多边形网格,降低了场景的复杂度,提高了场景的生成速度。     

What you should know about approximate dynamic programming

Approximate dynamic programming (ADP) is a broad umbrella for a modeling and algorithmic strategy for solving problems that are sometimes large and complex, and are usually (but not always) stochastic. It is most often presented as a method for overcoming the classic curse of dimensionality that is well‐known to plague the use of Bellman's equation. For many problems, there are actually up to three curses of dimensionality. But the richer message of approximate dynamic programming is learning what to learn, and how to learn it, to make better decisions over time. This article provides a brief review of approximate dynamic programming, without intending to be a complete tutorial. Instead, our goal is to provide a broader perspective of ADP and how it should be approached from the perspective of different problem classes. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

隐身飞机突防建模及低可探测性轨迹规划

针对隐身飞机突防飞行规划,分析了隐身飞机对警戒雷达网突防过程问题特性,建立了雷达探测模型与组网警戒雷达信息融合模型;综合考虑隐身飞机的隐身能力、预警时间和燃料消耗将隐身飞机低可探测性轨迹规划问题形式化为一个复杂多目标非线性连续时间最优控制问题;并提出基于伪谱法的低可探测性轨迹规划方法。仿真实验实现了在组网警戒雷达下隐身飞机的低可探测性突防轨迹规划,证明了方法的可用性和有效性。     

Optimization of reluctance accelerator efficiency by an improved discharging circuit

In this paper, an improved discharging circuit was proposed to quicken the decay of the current in the drive coil in a reluctance accelerator when the armature reaches the center of the coil. The aim of this is to prevent the suck-back effect caused by the residual current in drive coil. The method is adding a reverse charging branch with a small capacitor in the traditional pulsed discharging circuit. The results under the traditional circuit and the improved circuit were compared in a simulation. The experiment then verified the simulations and they had good agreement. Simulation and experiment both demonstrated the improved circuit can effectively prevent the suck-back effect and increase the efficiency. At the voltage of 800 V, an efficiency increase of 36.34% was obtained.     

非奇异快速终端滑模及动态面控制的轨迹跟踪制导律

针对飞行器跟踪预设轨迹的问题,提出非奇异快速终端滑模和角度约束的轨迹跟踪制导律。通过引入虚拟目标点,提出参考轨迹曲率半径的期望视线角约束条件,建立带有视线角约束并考虑自动驾驶仪动态特性的轨迹跟踪数学模型。为了保证在有限时间内跟踪预设轨迹并避免出现奇异问题,采用快速非奇异终端滑模和动态面控制方法进行制导律设计。推导出视线角误差和轨迹跟踪误差之间的数学关系,并利用Lyapunov稳定性准则证明轨迹跟踪误差最终有界任意小。与弹道成型轨迹跟踪制导律进行仿真对比,仿真结果表明所提出的制导律具有良好的跟踪性能及鲁棒性。     

舰炮身管的模态分析与多目标优化

舰炮的炮口扰动是影响舰炮射击精度的重要因素。为了减少舰炮的炮口扰动,优化身管结构,建立了柔性身管的ABAQUS有限元模型,将有限元模型的模态计算值与模态试验值进行比较,发现建立的柔性身管有限元模型是合理可行的。提出了混沌量子粒子群算法与动力学联合优化的方法,进行身管和炮口的多目标优化。优化结果表明,优化后炮口中心的线速度、角速度和角位移与优化前相比显著减小,身管质量有所降低,结构更加合理,该优化方法有效可行,为下一步全炮总体优化设计提供了一定的借鉴。     

求解不确定型车辆路径问题的弱鲁棒优化方法

为降低鲁棒优化模型最优解的保守性,以最小化违约车辆数和总惩罚成本为目标,建立针对旅行时间不确定的开放式车辆路径问题的弱鲁棒优化模型。对于不确定数据集的每个取值,该模型的最优解可以使其目标函数值始终不超过某数值,进而改善最优解的保守性。为提高启发式算法发现最优解的概率,提出一种自设计遗传算法对模型进行求解,其主要思想是利用粒子群算法搜索出可使遗传算法预期产生最好解的算法要素,并将其进行组合,从而产生新的遗传算法。采用新产生的遗传算法对模型继续求解,输出最好解。计算结果表明:与以往的鲁棒优化方法相比,弱鲁棒优化方法的最优解的保守性显著降低。