关于最优箭线网络图的定义及其唯一性的讨论

近年来,关于最优箭线网络图的绘制规则已有许多种方法。然而,最优箭线图是否是唯一的,有关文献都没有讨论这个问题。本文通过一个反例,指出目前常用的最优箭线网络图的定义是不完整的,符合这一定义的最优图也不是唯一的,文中给出了一个新的定义,并证明有了这一新的定义,就可根据作业分析表唯一地确定最优箭线网络图。     

基于退火惩罚混合遗传算法求解生产批量计划问题

针对以获得最低生产成本为目的的批量生产计划问题，提出了该问题的混合整数规划模型，首先，根据单级多资源批量计划问题的特点提出了问题的数学描述，；然后根据该数学问题的复合性，利用遗传算法的随机搜索和进行化过程寻找问题的全局最优解，为了防止适应度函数的过早收敛，引入退火惩罚因子对适应度函数进行处理，使得获得全局优解的可能性加大，实验结果表明，该方法能获得比传统遗传算法更为理想的近似最优解。     

海上无人机多机协同巡检航迹规划方法

随着无人机技术应用的不断深入,如何提高无人机编队的协同能力及在复杂动态环境的自适应性,已成为“集群智能”的 1个重要研究方向。文章对海上无人机多机协同航迹规划整体流程进行了分析,分别阐释了静态和动态场景下的多机协同规划方法。静态场景下主要采用分支定界法建立静态问题模型,为每架无人机划分作业区域、生成作业路径,使得整个巡检作业的航迹长度代价与作业时间代价最小;动态场景下主要针对气象变化、连续跟监、海域变化 3种突发场景,侧重于协同决策和路径规划设计对应的目标函数,采用启发式算法为整个巡检作业进行自适应航迹规划,以确保安全性和效率性。实验结果显示,无人机协同路径规划能够根据环境变化和任务需求动态调整多无人机的巡检路径,快速给出不同突发情况下的最佳动态调整方案,以应对复杂的海上环境并动态规避障碍物。     

裂缝区域优化随机扩展航路规划方法

针对密集障碍代价空间中存在的局部裂缝区域,基于采样的路径规划方法随机生成的节点无法进行有效扩展,形成可行路径的概率极低的问题,采用电势原理建立环境威胁模型,提出局部区域启发模式转换机制及节点一步检测方法.采用路径代价改进Transition-based RRT算法的节点选择机制,实现节点扩展的双启发.仿真结果表明,该算法能够有效地解决上述问题,其算法性能和路径生成优于同类算法.     

基于网络图的飞机大修进度模拟分析

飞机大修进度控制是一项复杂、随机性强,却有规律性可循的管理项目。通过对以往若干批次飞机大修进度数据的统计分析,结合专家评估,得到飞机大修中各工艺作业的进度规律,并以此作为大修网络图中的各项作业的基础参数,建立网络图计算模型,借助于计算机大数据模拟来分析大修网络图的内在规律,为实际飞机大修进度 制定和网络图优化提供参考依据。     

一种三维航迹快速搜索方法

本文提出了基于SAS的自动三维航迹规划方法。该方法通过把约束条件结合到搜索算法中去，有效地减小了搜索空间，缩短了搜索时间，从而使三维规划能够用于实时航迹规划。在搜索过程中地形信息得到了充分利用，使算法生成的航迹能够自动回避地形和威胁。实验证明，该方法能够快速有效地完成规划任务，获得满意的三维航迹。     

多个自由飞行空间机器人协调操作运动规划

本文提出了在空间微重力环境下多个自由飞行空间机器人协调操作运动规划算法，首先推导出多个自由飞行空间机器人协调操作的广义雅可比矩阵，其次给出了基于该矩阵的多个自由飞行空间机器人协调操作分解运动速度控制算法，最后用计算机仿真验证了该算法的正确性。     

基于ANP数据库的飞机起飞仿真研究

以可视化的方式全面直观的反应其航迹,来检验或者分析飞机起飞过程,为解决飞机噪声问题提供技术理论支持,利用ANP数据库,从中获取各种机型的飞行程序和性能参数,计算飞机起飞航迹及航迹上各点的推力、速度、姿态等,实现了飞机起飞过程及其航迹的三维可视化仿真。     

A multi-objective multi-memetic algorithm for network-wide conflict-free 4D flight trajectories planning

Under the demand of strategic air traffic flow management and the concept of trajectory based operations (TBO),the network-wide 4D flight trajectories planning (N4DFTP) problem has been investigated with the purpose of safely and efficiently allocating 4D trajectories (4DTs) (3D position and time) for all the flights in the whole airway network.Considering that the introduction of large-scale 4DTs inevitably increases the problem complexity,an efficient model for strategic level conflict management is developed in this paper.Specifically,a bi-objective N4DFTP problem that aims to minimize both potential conflicts and the trajectory cost is formulated.In consideration of the large-scale,high-complexity,and multi-objective characteristics of the N4DFTP problem,a multi-objective multi-memetic algorithm (MOMMA) that incorporates an evolutionary global search framework together with three problem-specific local search operators is implemented.It is capable of rapidly and effectively allocating 4DTs via rerouting,target time controlling,and flight level changing.Additionally,to balance the ability of exploitation and exploration of the algorithm,a special hybridization scheme is adopted for the integration of local and global search.Empirical studies using real air traffic data in China with different network complexities show that the pro posed MOMMA is effective to solve the N4DFTP problem.The solutions achieved are competitive for elaborate decision support under a TBO environment.     

Real-time trajectory planning for UCAV air-to-surface attack using inverse dynamics optimization method and receding horizon control

This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle (UCAV) performing autonomous air-to-surface (A/S) attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem (RHC-OCP). In particular, an approximate elliptic launch acceptable region (LAR) model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom (2-DOF) receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.