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     

人才结构系统分析的目标规划方法

本文把马尔可夫过程和目标规划结合起来,提出人才结构系统分析的单项控制和多项控制,并在单项控制模型的基础上发展成了多项控制模型,加强了模型的可信度和通用性。     

高效率机动部署航空武器靶场关键技术和应用

为用户设计了一个航空武器试验靶场,具备空空、空地和地空导弹试验能力,可机动部署,具有易于运行和运维代价低的特点。靶场由载机遥测系统、测量雷达、光电跟踪系统、微波和光纤通信系统、靶机遥测站、指挥控制等6个子系统构成;指挥控制子系统之外的5个子系统均使用国产成熟产品。在总体方案和指挥控制子系统设计中,对互联集成方案、机动部署、试验航线设计和发布、自动化领航、自动化指挥决策等5项关键技术进行了着重优化。在实际应用中,全靶场运行仅需20多成员(不含飞行和机场机务人员),3天内完成新试验场部署和联调,对作战部队飞行员进行5架次航线训练后即进行实弹试验,2天内完成多发中程拦截和近距格斗空空导弹试验。     

复杂环境下基于多目标粒子群的DWA路径规划算法

针对机器人在障碍物分布密集的复杂环境中运行时,动态窗口法(dynamic window approach,DWA)易出现避障失败或规划不合理的情况,提出一种基于多目标粒子群优化算法(multi-objective particle swarm optimization,MOPSO)的改进DWA规划算法。在建立多障碍物环境覆盖模型的基础上,提出一种障碍物密集度的判断方法;优化DWA算法中的子评价函数;利用改进的MOPSO算法实现DWA权重系数的动态调整,将权重系数的自适应变化问题转化为多目标优化问题;根据路径规划的要求将安全距离和速度作为优化目标,并使用改进的MOPSO算法对相应的多目标优化模型进行优化求解。仿真结果表明,该算法使机器人有效地通过障碍〖BHDWG8,WK10YQ,DK1*2,WK1*2D〗〖XCLXY.TIF;%129%129〗听语音 聊科研与作者互动 物密集区的同时兼顾了运行的安全性和速度,具有更好的路径规划效果。     

舰载对陆巡航导弹规划航路点间距离的计算分析

针对舰载对陆巡航导弹在实际飞行中,其航迹需要参考近似大地线的航线,在充分考虑导弹由海对陆的航路规划过程基础上,提出了易于编程、精度有所改进的空间两点间大地距离的计算方法.该方法在考虑高程的地球椭球模型参数的求取基础上,利用Bowring反解公式重新推导了顾及高程的空间航路点间的计算公式.相关算例表明,该方法提高了导弹规...     

基于CPN建模的行动方案开发与分析系统设计

协助和支持军事计划人员制订和分析作战计划的建模与仿真能力是军方的现行需求,而行动方案的开发与分析则是作战计划建模与仿真的重点。针对作战计划过程期间开发的军事任务的排序与调度问题,设计了一个行动方案开发与分析系统,系统采用客户机-服务器体系结构,运用基于有色Petri网建模的军事计划领域的概念表示法,并使用状态空间分析技术完成军事任务的自动化排序与调度。军事计划人员通过图形用户界面使用系统,在面对紧急突发事件时,可以快速及时地开发出适当可行的COA,并对COA进行逻辑可行性分析。