Robust shortest path planning and semicontractive dynamic programming

In this article, we consider shortest path problems in a directed graph where the transitions between nodes are subject to uncertainty. We use a minimax formulation, where the objective is to guarantee that a special destination state is reached with a minimum cost path under the worst possible instance of the uncertainty. Problems of this type arise, among others, in planning and pursuit‐evasion contexts, and in model predictive control. Our analysis makes use of the recently developed theory of abstract semicontractive dynamic programming models. We investigate questions of existence and uniqueness of solution of the optimality equation, existence of optimal paths, and the validity of various algorithms patterned after the classical methods of value and policy iteration, as well as a Dijkstra‐like algorithm for problems with nonnegative arc lengths.© 2016 Wiley Periodicals, Inc. Naval Research Logistics 66:15–37, 2019     

基于运输问题的国防动员任务规划模型研究

国防动员任务规划为执行动员保障任务提供明确的方案计划,是高效有序开展国防动员协同保障的重要前提和关键环节,既要综合考虑各类影响因素,又要确保对接结果适时、适量、适地、适度.本文分析了动员任务规划的现实问题,通过梳理实际开展动员任务规划的阶段步骤,明确了动员任务规划模型的研究内涵和边界;在此基础上,建立了国防动员任务规划...     

不确定环境下无人机区域目标搜索及载荷参数影响

针对不确定环境下无人机区域搜索问题,建立了实时探测更新的搜索方法,提出了机载光电载荷参数优化配置策略。建立了基于二维离散网格的无人机区域搜索模型,采用概率地图描述目标信息的实时获取与更新;引入不确定度指标、目标网格的重访和网格探测次数控制,建立搜索目标函数;建立了基于粒子群算法的搜索路径滚动优化方法;通过对任务区域平均探测时间步数和误判概率的估计分析,建立了机载光电载荷参数优化配置策略。使用蒙特卡洛方法验证了区域搜索方法的有效性和光电载荷参数配置对搜索效率、误判概率的影响。     

深度神经网络指导下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。     

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     

一种基于知识的作战计划系统设计

作战计划系统是复杂的问题求解系统,在军事领域的各个方面发挥着重要的作用。介绍了当前一些主要的作战计划辅助生成系统及其特点,分析比较和归纳整理了当前军用计划系统所采用的一些常见规划技术和优缺点,重点分析了作战计划系统中的智能规划技术。在此基础上,提出了一种基于知识的作战计划辅助生成系统的开发设想,构建了系统知识库,系统采用层级任务网络规划技术,给出了这种规划技术的理论框架和算法过程,并且把这种技术与多主体规划技术相结合,辅助实现军事作战任务的逐层分解与规划优化,进而生成完整的行动序列,较好地解决了作战计划辅助生成问题。     

基于Multi-Agent的武器装备虚拟维修训练系统

提出了一种基于Multi-Agent的虚拟维修训练系统(VMTS)结构框架,整个系统分别由主控Agent、仿真Agent、和接口Agent3个具有交互作用的Agent组成,从而将虚拟维修训练系统的开发转化为一个多Agent系统的设计与开发.基于多Agent的框架结构可实现受训者的智能模型及虚拟训练场景中虚拟物体的行为模型,从而可以提高VMTS的健壮性和可重用性.基于Agent的概念模型实现了Agent之间的交互和协作,并介绍了主控Agent和仿真Agent的具体实现方法.     

蚁群算法在无人机航路规划中的应用

蚂蚁算法是一种新的源于大自然生物界的仿生随机优化方法。吸收了昆虫中蚂蚁的行为特征,通过其内在的搜索机制,在一系列组合优化问题求解中取得了成效。将蚁群算法应用于无人机(UAV)航路规划,提出了一种适用于航路规划的优化方法,可以为在敌方防御区域内执行攻击任务的无人机规划设计出高效的飞行航路,保证无人机以最小的被发现概率及可接受航程到达目标点,提高了无人机作战任务的成功率。仿真结果初步表明该方法是一种有效的航路规划方法。     

空间站零燃料大角度姿态机动路径存在性分析

零燃料大角度姿态机动技术是新近应用在国际空间站的新概念姿态控制技术。构造了以控制力矩陀螺为执行机构的空间站姿态控制动力学模型,在此基础上,建立了空间站本体与控制力矩陀螺之间的角动量守恒关系。针对各类大角度姿态机动任务,通过分析空间站惯量参数与控制力矩陀螺性能参数之间的解析关系,得到了零燃料大角度姿态机动路径的存在性条件。通过规划算例验证了存在性分析的正确性。所提出的零燃料大角度姿态机动存在性条件,为姿态机动路径的存在性判断提供了便捷可行的方法,为零燃料大角度姿态机动技术未来在我国空间站实施的可行性论证提供重要的理论依据。     

Modeling and solution for the ship stowage planning problem of coils in the steel industry

We consider a ship stowage planning problem where steel coils with known destination ports are to be loaded onto a ship. The coils are to be stowed on the ship in rows. Due to their heavy weight and cylindrical shape, coils can be stowed in at most two levels. Different from stowage problems in previous studies, in this problem there are no fixed positions on the ship for the coils due to their different sizes. At a destination port, if a coil to be unloaded is not at a top position, those blocking it need to be shuffled. In addition, the stability of ship has to be maintained after unloading at each destination port. The objective for the stowage planning problem is to minimize a combination of ship instability throughout the entire voyage, the shuffles needed for unloading at the destination ports, and the dispersion of coils to be unloaded at the same destination port. We formulate the problem as a novel mixed integer linear programming model. Several valid inequalities are derived to help reducing solution time. A tabu search (TS) algorithm is developed for the problem with the initial solution generated using a construction heuristic. To evaluate the proposed TS algorithm, numerical experiments are carried out on problem instances of three different scales by comparing it with a model‐based decomposition heuristic, the classic TS algorithm, the particle swarm optimization algorithm, and the manual method used in practice. The results show that for small problems, the proposed algorithm can generate optimal solutions. For medium and large practical problems, the proposed algorithm outperforms other methods. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 564–581, 2015