基于多目标优化模型的武器装备体系能力规划

武器装备体系能力规划是武器装备体系研究的重要内容.在武器装备体系能力空间描述的基础上,将规划时间和规划成本作为优化目标,建立了武器装备体系能力规划的多目标优化模型,提供了基于武器装备体系能力空间描述到能力规划模型的建模方法,采用多目标遗传算法对优化模型进行求解.在此基础上,提供了武器装备体系能力差距定量分析的方法,为武...     

基于Floyd算法的常规导弹连续波次作战运输规划

为提高常规导弹连续波次作战效能,对常规导弹连续波次作战运输规划问题进行研究。以Floyd算法为基础,首先生成了作战机动区域的交通网络最短路径、距离矩阵;其次将常规导弹连续波次作战运输过程分解为不同阶段,以运输过程中的整体暴露时间最短为目标,构建了初始规划方案0-1整数规划模型;然后考虑道路通行量及地域容量限制,对初始规划方案中存在的地域容量超过限制及单行道路中会车、超车情况进行逐步循环优化,以得到最佳运输规划方案;最后选择了一个作战案例想定,通过Matlab编程对案例进行了求解,得到了针对此案例的最佳运输规划方案,验证了模型的正确性和算法的有效性。     

Optimal motion planning in rapid‐fire combat situations with attacker uncertainty

This article provides a modeling framework for quantifying cost and optimizing motion plans in combat situations with rapid weapon fire, multiple agents, and attacker uncertainty characterized by uncertain parameters. Recent developments in numerical optimal control enable the efficient computation of numerical solutions for optimization problems with multiple agents, nonlinear dynamics, and a broad class of objectives. This facilitates the application of more realistic, equipment‐based combat models, which track both more realistic models, which track both agent motion and dynamic equipment capabilities. We present such a framework, along with a described algorithm for finding numerical solutions, and a numerical example.     

翼伞系统线目标归航方法

针对运载火箭助推器或子级无控坠落地面落点散布较大的情况,提出一种翼伞系统的线目标归航方法。建立了矩形边界下的归航计算模型,对点目标归航和线目标归航两种方法进行了收缩区域分析;对翼伞归航能力、落区散布边界特征对归航性能的影响进行对比分析,得到了相应的归航策略,并提出在较大散布区域下设置多个着陆区域的工程解决方案;建立动力学和操纵控制模型,对线目标归航过程进行了仿真。结果表明,所提方法对工程有一定的参考价值。     

The Serbian defence institution: the need for clear policy guidance to improve the Serbian defence planning,management, and command processes

ABSTRACT

The uncritical layering of western liberal defence governance norms and concepts on top of existing legacy concepts has impeded achieving coherent military capabilities and capacities when Serbia’s political and military leadership tried to reform the defence system using Western benchmarking principles and Western countries’ best practices. The process of this change has been more valuable than its actual output, as defined by increased capabilities. Such outcomes should be reflective of policy guidance, and can be thought of as closing the trinity loop of a defence planning system: plans, money and execution. This article addresses two key functional areas of the Serbian defence institution. First, it assesses the current state of defence planning to discern its strengths and weaknesses to ascertain if plans are tied to financial decision-making. Second, a full examination of current Serbian defence management is conducted to discern whether weaknesses exist that distract from producing operational capabilities. Both areas are analyzed thoroughly and some solutions for change are proposed. Also, the article analyzes the appearance of two negative phenomena in the planning process – economization and managerialism.     

排课中合班问题的探讨

基于排课的实际需要,分析了合班对排课的影响,结合遗传算法在排课中的应用,建立了针对班级上课时间分布均匀性以及课程上课时间分布均匀性的适配值函数.在对课程表进行编码后,把合班问题的解决方案应用于排课算法,使用合班信息与课表编码信息的双表操作,从而能在遗传基因中判断出非法个体,并能进行合理化调整.算例结果表明本算法能有效解决排课中的合班问题.     

多架无人机协同作战的路径规划

提出了一种协调多架无人机的编队同时到达目标的航路规划方法.首先根据敌方防御区域内雷达、导弹等威胁阵地的具体分布情况,采用划分Voronoi多边形的方法制定初始航路,然后通过叠加定长线段到初始航路上对初始航路进行离散化,最后采用动态链类比法调整航路并对航路进行光顺优化处理,使航路安全可飞.并用数字仿真技术对该方法进行了验证,结果表明该方法是可行的.     

An eikonal equation based path planning method using polygon decomposition and curve evolution

Path planning is a key technique of autonomous navigation for robots, and the velocity field is an important part. Constructing velocity field in a complex workspace is still challenging. In this paper, an inner normal guided segmentation algorithm in a complex polygon is proposed to decompose the complex workspace in this paper. The artificial potential field model based on probability theory is then used to calculate the potential field of the decomposed workspace, and the velocity field is obtained by utilizing the potential field of this workspace. Path optimization is implemented by curve evolution, during which the internal force generated in the smoothing process of the initial path by a mean filter and the external force is obtained from the gradient of the workspace potential field. The parameter selection principle is deduced by analyzing the influence of several parameters on the path length and smoothness. Simulation results show that the designed polygon decomposition algorithm can effectively segment complex workspace and that the path optimization algorithm can shorten and smoothen paths.     

Reliability of a two-dimensional demand-based networked system with multistate components

Existing research on multistate system reliability has mainly focused on one-dimensional systems such as parallel systems, linear sliding window systems, and linearly consecutively connected systems. However, two-dimensional networked systems widely exist in real-world applications such as lighting systems, monitoring systems, and computer network systems. This research considers a two-dimensional networked system consisting of multistate components. The system fails if the cumulative performance of any row or any column cannot meet a predetermined demand. A novel reliability evaluation algorithm is proposed for the considered two-dimensional networked system by extending the universal generating function technique. Furthermore, the proposed model and reliability evaluation algorithm are extended to a two-dimensional networked system with phased missions. The proposed models and algorithms are illustrated by a matrix heating system in a thermoforming machine.     

基于深度神经网络的无线覆盖预测算法*

为保证新一代移动无线网络能够根据实时覆盖情况动态地调节小区天线参数,需要实现高效且准确的无线覆盖预测。传统的求解方法通过精确的场强预测来判断天线参数的优劣,虽然精度很高但需要大量的计算资源,无法满足5G和后5G移动网络通过实时覆盖预测进行射频参数动态调整的实际需求。现采用基于深度神经网络的算法对给定天线参数的覆盖效果进行预测,以取代对目标区域的精确场强预测。数值结果表明,该方法能够在保持计算准确性的同时显著减少计算量,为5G动态网络规划提供基础性参考数据。