翼伞精确空投系统归航轨迹规划与控制

翼伞归航轨迹规划与控制问题是翼伞系统在一定初始状态下,利用自身可操作性,完成从初始位置到目标位置的转移问题。针对翼伞空投系统不同归航要求,规划出满足精度要求为圆径概率误差（ CEP ）小于40m的归航轨迹并经过一定量的控制完成翼伞空投系统精确空投任务。首先建立翼伞系统状态空间六自由度模型,并在此基础上提出系统简化稳态模型,通过最优控制方法,规划出满足空投要求的最优归航轨迹后对翼伞进行不断控制直至目标点。最后通过Matlab仿真试验,绘出翼伞系统归航轨迹图与控制变化图。     

弹药物资储备布局规划仿真模型＊

介绍了当前弹药物资储备布局规划的现状,对其涉及的要素进行分析,构建了弹药物资储备布局规划网络模型。在此基础上提出了分析模型,将弹药物资布局规划求解问题描述为有约束条件的多目标优化数学模型,解决了各仓库弹药存储量难以预测的问题,并通过实验进行了验证分析。     

舰载预警直升机线式搜索模型

针对舰载预警直升机在遂行编队预警任务时的战术需求,建立了基于一定接触概率、基于给定累积发现概率和基于给定建航概率的舰载预警直升机线式搜索模型,通过仿真计算,得出了不同威胁情况下最大搜索地段长度和最大巡逻线长度的变化规律,给出了在不同威胁情况下应采用的巡逻搜索方式,为舰载预警直升机有效预警角研究奠定了基础,为最终确定舰载预警直升机的阵位配置提供了基本依据。     

复杂海战场环境下AUV全局路径规划方法

针对无人自主水下航行器(Autonomous Underwater Vehicle,AUV)在复杂海战场环境中路径规划时环境模型复杂、约束条件多的情况,建立了包括战场地形、敌方威胁、障碍物和海流场等在内的比较完善的海战场环境模型.以AUV航行时间、威胁时间最短为优化目标,给出了一种基于振荡型入侵野草优化(Invasiv...     

复杂约束下的导弹作战任务规划模型和算法研究*

导弹作战任务规划是一个涉及时间、资源、质量和其他关系约束的复杂问题.首先通过定叉约束满足效用对基本约束满足模型进行了扩展,建立了导弹任务规划的约束满足优化模型.在此基础上,研究了任务规划模型求解的时间和效用传播算法,提出了基于综合效用的优化求解框架.该模型和求解框架易于解决具有多种约束因素的复杂问题,具有较好的通用性.通过定义软、硬约束效用,使得实际任务规划问题求解具有更好的灵活性.     

Disaster management in case of CBRNe events: an innovative methodology to improve the safety knowledge of advisors and first responders

Nowadays, Chemical-Biological-Radiological-Nuclear-explosive (CBRNe) risks are one of the world's main safety concerns. The radiological disasters of Fukushima and Chernobyl, the chemical events of Seveso or the release of Sarin in the Tokyo Subway, the biological emergencies such as the H1N1 flu or the recent Ebola outbreak, and recent news about the availability of non-conventional weapons acquired by fundamentalist organisations represent evidence of potential future threats. CBRNe risks are a real and global threat. The University of Rome, Tor Vergata, in collaboration with the most important Italian and international bodies working in the field of CBRNe safety and security, and supported by the North Atlantic Treaty Organisation and the Organisation for the Prohibition of Chemical Weapons, organises International Masters Courses on the Protection against CBRNe events. Within this framework, a Table-Top Exercise was planned, in collaboration with the Italian Ministry of Interior and Ministry of Defence. The scenario, the logistic organisation, on-going adjustments during the exercise and the outcomes are presented here and analysed.     

Column generation for stochastic green telecommunication network planning with switchable base stations

We present the green telecommunication network planning problem with switchable base stations, where the location and configuration of the base stations are optimized, while taking into account uncertainty and variability of demand. The problem is formulated as a two‐stage stochastic program under demand uncertainty with integers in both stages. Since solving the presented problem is computationally challenging, we develop the corresponding Dantzig‐Wolfe reformulation and propose a solution approach based on column generation. Comprehensive computational results are provided for instances of varying characteristics. The results show that the joint location and dynamic switching of base stations leads to significant savings in terms of energy cost. Up to 30% reduction in power consumption cost is achieved while still serving all users. In certain cases, allowing dynamic configurations leads to more installed base stations and higher user coverage, while having lower total energy consumption. The Dantzig‐Wolfe reformulation provides solutions with a tight LP‐gap eliminating the need for a full branch‐and‐price scheme. Furthermore, the proposed column generation solution approach is computationally efficient and outperforms CPLEX on the majority of the tested instances. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 351–366, 2016     

A bidirectional heuristic for maximizing the net present value of large‐scale projects subject to limited resources

We consider the scheduling of large‐scale projects to maximize the project net present value given temporal and resource constraints. The net present value objective emphasizes the financial aspects of project management. Temporal constraints between the start times of activities make it possible to handle practical problem assumptions. Scarce resources are an expression of rising cost. Since optimization techniques are not expedient to solve such problems and most heuristic methods known from literature cannot deal with general temporal constraints, we propose a new bidirectional priority‐rule based method. Scheduling activities with positive cash flows as early and activities with negative cash flows as late as possible results in a method which is completed by unscheduling techniques to cope with scarce resources. In a computational experiment, we compare the well‐known serial generation scheme where all activities are scheduled as early as possible with the proposed bidirectional approach. On the basis of a comprehensive data set known from literature containing instances with up to 1002 activities, the efficiency of the new approach is demonstrated. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

基于算子空间的公式发现算法研究

在FDD提出的人工智能技术与曲线拟合技术结合的公式发现系统的基础上 ,提出了新的基于算子空间的公式发现算法 ,并在算法研究的基础上设计实现基于算子空间的可视化公式发现系统 ,该系统通过算子空间概念的引入 ,简化了算子空间的规则 ,同时引入导数规则、误差规则以及终止规则 ,丰富了知识库内容。通过以上改进 ,和BACON和FDD相比 ,公式发现的形式更广 ,复杂度更高。文章最后给出了应用实例以及公式发现的结果。     

自适应光学波前实时处理机结构设计

本文介绍的波前处理机是１．２ｍ望远镜自适应光学系统的关键部件之一,吞吐率高,延时小,是具有高速数据处理能力的实时处理系统。为满足系统的高速度性能,系统设计在实时性、并发性的基础上,将图象数据采集加入流水线,并对波前处理中自然存在的子任务作“去相关”’处理,建立了图象采集、斜率计算、波前复原间流水线操作。图象读出时间的利用及流水线的建立,大大减少了时延,降低了系统实时性要求。流水线处理与高度并行处理相结合,也是本处理机设计的一大特色。