基于A~*算法的虚拟士兵城市作战路径规划

针对虚拟士兵在城市作战仿真领域的需求,重点研究了虚拟士兵在城市环境中路径规划问题。通过对三维城市虚拟环境空间进行分层信息处理,生成虚拟士兵能够感知的虚拟信息层。用A*算法求出虚拟士兵从初始位置到达目标位置的最佳路径,并给出算法的具体设计与实现。     

基于二层遗传算法的导弹航路选优问题研究

在多批次多数量的反舰导弹从多个方向对敌舰艇进行饱和攻击的决策过程中,如何选择出最优的航路组合是提高反舰导弹作战效能的关键问题。在综合分析反舰导弹航路选优问题的基础上,建立了导弹航路选择的优化模型,并针对导弹航路选优问题,对基本遗传算法进行了改进,提出了二层遗传算法。仿真分析了多火力单元多目标导弹攻击的航路组合优化问题,得出了有效的导弹攻击航路。通过验证,说明了二层遗传算法在导弹航路规划中的有效性。     

基于Dubins路径的智能车辆路径规划算法

路径规划是车辆智能化的核心问题之一,而所有路径均可分解为简单的Dubins路径。在Dubins路径的思想下对智能车辆的行驶路径进行分段研究,并利用经典PID控制对该算法的执行性能进行检验。研究表明:算法能计算出车辆行驶的最短路径,减少了车辆行驶的路径长度,缩短了行驶时间,减少了控制系统的计算量,提高了车辆执行系统的执行力度,降低了执行误差,对最优路径具有较好的选择性。     

Making defense planning meaningful: the evolution of strategic guidance in the Hungarian Ministry of Defense

Hungary, a former communist state, adapted a Western-style defense planning system during the 1990s and 2000s. Although on the surface the elements of this planning system were similar to the planning programming budgeting system (PPBS) developed by the US Department of Defense, strategic guidance for defense planning has not been properly developed until recently. Thus, albeit PPBS-based defense plans were developed in the Hungarian Ministry of Defense (Hungarian MoD) regularly, they lacked both an expression of clear priorities and strategic focus. This article delineates the evolution of strategic guidance in the Hungarian MoD concentrating on current developments, and introduces the newly elaborated analytical concepts and tools, which helped to create needed strategic guidance in Hungary.     

基于多目标优化的任务计划建模及方法

针对任务计划在进行多目标优化时采用进化算法求解效率较低的问题,设计了一种结合分组策略的非支配排序遗传(NSGA-Ⅱ)算法,可以快速有效地得到合理的分组结果。基于分组结果,调整NSGA-Ⅱ算法的步骤,灵活地进行种群初始化,使最终分配结果各优化的目标有了明显的改善,提高了算法的效率。通过实验分析,验证了所提方法的可行性和有效性。     

隐身飞机突防建模及低可探测性轨迹规划

针对隐身飞机突防飞行规划,分析了隐身飞机对警戒雷达网突防过程问题特性,建立了雷达探测模型与组网警戒雷达信息融合模型;综合考虑隐身飞机的隐身能力、预警时间和燃料消耗将隐身飞机低可探测性轨迹规划问题形式化为一个复杂多目标非线性连续时间最优控制问题;并提出基于伪谱法的低可探测性轨迹规划方法。仿真实验实现了在组网警戒雷达下隐身飞机的低可探测性突防轨迹规划,证明了方法的可用性和有效性。     

机载反辐射导弹和常规反舰导弹协同规划算法

机载反辐射导弹在攻击移动目标时容易受雷达关机影响而丢失目标,和常规主动雷达制导的反舰导弹协同攻击可以有效对抗目标雷达关机。为了达到协同作战目的,载机起飞前已知目标信息情况下,通过计划协同算法确定协同作战方案,方案包括载机和导弹各个航路点位置和到达该位置的时间点,然后按照在机场起飞前就制定好的方案实施具体作战行动。对计划协同算法进行了实例仿真,结果表明算法切实有效。     

Expansion planning for waste‐to‐energy systems using waste forecast prediction sets

We consider an expansion planning problem for Waste‐to‐Energy (WtE) systems facing uncertainty in future waste supplies. The WtE expansion plans are regarded as strategic, long term decisions, while the waste distribution and treatment are medium to short term operational decisions which can adapt to the actual waste collected. We propose a prediction set uncertainty model which integrates a set of waste generation forecasts and is constructed based on user‐specified levels of forecasting errors. Next, we use the prediction sets for WtE expansion scenario analysis. More specifically, for a given WtE expansion plan, the guaranteed net present value (NPV) is evaluated by computing an extreme value forecast trajectory of future waste generation from the prediction set that minimizes the maximum NPV of the WtE project. This problem is essentially a multiple stage min‐max dynamic optimization problem. By exploiting the structure of the WtE problem, we show this is equivalent to a simpler min‐max optimization problem, which can be further transformed into a single mixed‐integer linear program. Furthermore, we extend the model to optimize the guaranteed NPV by searching over the set of all feasible expansion scenarios, and show that this can be solved by an exact cutting plane approach. We also propose a heuristic based on a constant proportion distribution rule for the WtE expansion optimization model, which reduces the problem into a moderate size mixed‐integer program. Finally, our computational studies demonstrate that our proposed expansion model solutions are very stable and competitive in performance compared to scenario tree approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 47–70, 2016     

An exact method for finding shortest routes on a sphere,avoiding obstacles

On the surface of a sphere, we take as inputs two points, neither of them contained in any of a number of spherical polygon obstacles, and quickly find the shortest route connecting these two points while avoiding any obstacle. The WetRoute method presented here has been adopted by the US Navy for several applications. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 374–385, 2016     

Risk‐sensitive sizing of responsive facilities

We develop a risk‐sensitive strategic facility sizing model that makes use of readily obtainable data and addresses both capacity and responsiveness considerations. We focus on facilities whose original size cannot be adjusted over time and limits the total production equipment they can hold, which is added sequentially during a finite planning horizon. The model is parsimonious by design for compatibility with the nature of available data during early planning stages. We model demand via a univariate random variable with arbitrary forecast profiles for equipment expansion, and assume the supporting equipment additions are continuous and decided ex‐post. Under constant absolute risk aversion, operating profits are the closed‐form solution to a nontrivial linear program, thus characterizing the sizing decision via a single first‐order condition. This solution has several desired features, including the optimal facility size being eventually decreasing in forecast uncertainty and decreasing in risk aversion, as well as being generally robust to demand forecast uncertainty and cost errors. We provide structural results and show that ignoring risk considerations can lead to poor facility sizing decisions that deteriorate with increased forecast uncertainty. Existing models ignore risk considerations and assume the facility size can be adjusted over time, effectively shortening the planning horizon. Our main contribution is in addressing the problem that arises when that assumption is relaxed and, as a result, risk sensitivity and the challenges introduced by longer planning horizons and higher uncertainty must be considered. Finally, we derive accurate spreadsheet‐implementable approximations to the optimal solution, which make this model a practical capacity planning tool.© 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008