基于混合粒子群算法的软硬武器协同反导决策

以单舰使用软硬武器对抗末端飞行的反舰导弹为背景,在对软硬武器抗击反舰导弹存在相互干扰进行分析的基础上,为了最大程度地减小干扰,取得最大的作战效果,建立了单舰协同使用软硬武器分层防御反舰导弹的模型.这是一个多阶段单指标方案优选问题,使用混合粒子群算法进行求解,仿真结果表明:该算法可以找到合理的、满足要求的反导方案,而且计算方便.     

一种通用型舰载防空硬武器火力优化算法?

针对当前武器优化分配算法缺少通用性,难以兼顾效率和时间的问题,提出了一种通用型舰载防空硬武器火力优化算法。该算法首先提取各舰载武器能够攻击的目标集合,然后对各武器的目标集合逐一进行时间分配,并计算对目标的毁伤概率,最终完成所有武器的分配。计算表明,该算法具有很好的通用性和实时性,可适用于较大规模舰载防空硬武器的火力优化分配问题。     

基于排队论的防空兵力部署优化模型

兵力部署优化问题是防空指控系统的重要研究内容之一。针对多型防空武器多层多区段混合部署问题,对异型空袭武器和防空武器基于作战效能标准化处理,基于排队论给出空袭武器的突防概率计算模型,将防空武器系统综合防御效能作为优化目标,建立多型防空武器扇形部署优化模型。仿真实验验证了优化模型的有效性和合理性,可为科学制定兵力部署方案提供参考。     

基于图像处理技术的舰载武器系统对准方法

针对目前舰载武器系统对准方法在实际应用中局限性大的问题,提出了一种基于图像处理技术、利用差分算法的舰载武器系统对准方法,并给出了实现该方法的图像处理算法和程序设计流程以及图像比较基准坐标系的建立方法,使得武器系统的对准工作变得更加方便、快捷和精密.该方法适用于舰载武器系统的对准联调和类似的民用设备.     

舰艇武器布置问题的一种协同优化算法

针对舰艇武器布置问题的特点,提出了一种基于粒子群优化和分类器系统的协同优化算法,以粒子群优化进行优化计算,用分类器系统消除约束.计算实例表明,该算法能较好地实现优化计算,并能节省大量的计算时间.     

A targeting model that minimizes collateral damage

This paper considers the problem of allocating weapons to achieve targeting objectives while simultaneously minimizing aggregate damage to surrounding nonmilitary facilities, each of which has an upper limit to the damage it is permitted to incur. A model is formulated which assumes only that damage to individual targets or associated facilities does not decrease as the number of allocated weapons increases. An implicit enumeration algorithm, based on that of Lawler and Bell is described that yields optimal integer solutions. An example is presented.     

基于支持向量机算法的虚拟脱靶量预测

为了提高防空高炮武器系统的射击精度问题,采用支持向量机(SVM)算法,建立了基于支持向量机的虚拟脱靶量预测模型,提出了预测方法,该算法可以通过对给定样本的学习,获得很好的预测未出现的样本,理论上比较科学,算法简单、易于实现,通过仿真实验验证了该算法对虚拟脱靶量预测的可用性和准确性,为火控系统精度的校正提供了一种有效的方法。     

基于蚁群算法的试验流程优化研究

水中兵器的海上试验涉及许多人员、兵力、被试产品、测量设备等,试验周期长、消耗大,因此如何缩短试验周期是亟待研究解决的问题.文中首先将试验流程优化问题转化为车间调度问题,建立了相应的数学模型,再应用蚁群算法转移规则得到中间结果并进行排队以对各种资源约束进行处理.最后将结果利用局部搜索算法优化后作为蚁群算法信息素更新的基础.实例计算结果表明,该方法优化效果良好.     

基于禁忌退火算法的巡航导弹航迹规划

针对巡航导弹航迹规划这个复杂的优化问题,一个禁忌退火混合优化算法被提出.首先,该算法是以基本模拟退火算法为基础.其次,为了加快该模拟退火算法的收敛速度,在恶化解的接受判断过程中,增加了一定动态的约束条件.最后,为了使最优解能够跳出局部最优的陷阱,使用了一个动态的禁忌表.仿真结果验证了该禁忌退火混合优化算法能够取得目标函数更优的航迹规划路径,从而有效提高巡航导弹的作战效能.     

INCAPACITATING BIOCHEMICAL WEAPONS

Military interest in incapacitating biochemical weapons has grown in recent years as advances in science and technology have appeared to offer the promise of new “non-lethal” weapons useful for a variety of politically and militarily challenging situations. There is, in fact, a long and unfulfilled history of attempts to develop such weapons. It is clear that advances are opening up a range of possibilities for future biological and chemical weapons more generally. The treaties prohibiting biological and chemical weapons make no distinction between lethal and “non-lethal” weapons—all are equally prohibited. Indeed, a sharp and technically meaningful distinction between lethal and “non-lethal” biological and chemical weapons is beyond the capability of science to make. Thus, interest in incapacitating biochemical weapons, and efforts on the part of various states to develop them, pose a significant challenge to the treaty regimes, to the norms against biological and chemical warfare that they embody, and, ultimately, to the essential protections that they provide. Preventing a new generation of biological and chemical weapons from emerging will take concerted efforts and action at the local, national, and international levels.     

蚁群算法及其在火力分配问题中的应用

火力分配问题是指用一定数量的武器对一定数量的目标进行打击,如何根据武器性能和目标特性等一系列的因素,制定打击计划,使打击效果最好,满足打击需求,是我二炮部队火力运用专业的研究课题之一.火力分配问题是NP难题,经典的求解算法存在指数级的时间复杂度.采用蚁群优化算法,对该问题进行了研究.     

非致命武器系统安全性分析

非致命武器在各类防暴和处突任务中发挥着重要作用,为提高非致命武器的系统安全性,给出了系统安全性的定义,明确了非致命武器系统安全性的组成,分析了非致命武器本质(固有)安全性和使用安全性的关系。在建立非致命武器系统安全性评价指标的基础上,建立了适用于非致命武器的安全管理系统模型,为非致命武器的安全管理模式提供了一种新的思路。     

火力分配多目标优化的IBACO算法

应用蚁群优化算法(Ant Colony Optimization)求解多目标优化问题已经引起广泛关注,多目标火力分配问题的目标是求出一个合适的武器目标分配方案,使满足决策需要。建立了多目标火力分配的数学模型,提出一种基于指标的蚁群优化算法Indicator-Based Ant Colony Optimization),给出了算法的具体步骤。IBACO的核心思想是利用二元性能指标来引导人工蚂蚁进行搜索,由于该算法中的信息素是根据指标的值来更新的,通过奖励信息素可以强化最优解。仿真实验证明了该算法的有效性,在解决火力分配问题上,所提算法和蚁群优化算法相比具有较好的收敛性。     

基于遗传模拟退火算法的空袭兵力分配及优化

对遗传模拟退火算法中的交叉、变异操作进行了改进,并实施了最优保留策略,形成了改进遗传模拟退火算法.以突击效果最大化和兵力损失最小化为目标函数,以空袭兵力总量的限制、空袭兵器挂载类型的限制等为约束条件,建立了空袭兵力分配及优化模型.在考虑兵力分配模型特点的基础上,利用改进遗传模拟退火算法求解.通过与多目标数学规划和标准遗传算法优化进行的比较表明,该方法能够有效地解决带约束的多目标优化问题.     

射向保持方案及影响其精度的因素分析

介绍用于压制兵器的射向保持器的工作原理和计算方法,并通过计算机仿真分析了计算机字长,计算步长,仪器安装糟度以及陀螺仪测量精度等因素对射向保持器精度的影响。     

灰色预测模型在非致命武器经济寿命预测中的应用

针对目前非致命武器经济寿命方面的研究相当缺乏的现状,结合非致命武器的自身特点,在全面分析装备全寿命周期费用的基础上,引入灰色理论,运用GM（1,1）模型对非致命武器的经济寿命周期费用进行估算和预测。通过分析,灰色预测模型具有较高的建模精度,预测方法和结果对非致命武器的经济寿命预测具有很强的实用性。     

空对地攻击武器选用方法

空对地攻击中能否正确选用空对地武器,将直接影响空对地攻击的效果.讨论了一般的空对地武器选用原则和依据,并用概率论的方法建立了选用空地武器的效损比模型,最后给出具体算例说明模型在实际作战任务中的应用.     

Weapon acquisition with target uncertainty

This article is concerned with choosing a mix of weapons, subject to constraints, when the targets to be attacked are known imprecisely. It is shown that the correct method for optimizing the mix of weapons involves a pair of nested optimization problems (two-stage optimization). Two methods for optimizing the expected utility of a mix are discussed. The first involves a simultaneous attack model, in which it is implicitly assumed that all weapons are used at once. The second involves a sequential attack model, in which targets appear in random order and are attacked one at a time. Particular attention is given to the question of the appropriate mix of general-purpose and special-purpose weapons.     

Russia and Strategic Conventional Weapons:

ABSTRACT

Russian political leaders and military strategists are growing increasingly concerned about “strategic conventional weapons”—a broad category that appears to include all non-nuclear, high-precision, standoff weapons—and about long-range, hypersonic weapons, in particular. These concerns are complex and multifaceted (and, in some cases, contradictory), but chief among them are the beliefs that strategic conventional weapons could prove decisive in a major conflict and that Russia is lagging behind in their development. US programs to develop and acquire such weapons—namely, the Conventional Prompt Global Strike program—are of great concern to Russian strategists, who argue both that the United States seeks such weapons for potential use against Russia—its nuclear forces, in particular—and because strategic conventional weapons are more “usable” than nuclear weapons. Asymmetric responses by Russia include increased reliance on tactical nuclear weapons, efforts to enhance the survivability of its nuclear forces, and investments in air and missile defenses. There is also strong—but not completely conclusive evidence—that Russia is responding symmetrically by attempting to develop a long-range, conventionally armed boost-glide weapon.     

相依目标群系统火力分配问题分析与解法

本文中讨论由若干个相依目标群组成的平面点目标系统的火力分配问题。对于武器型号相同的情形,得到了“边际毁伤递减原理”和“循序最优方案即全局最优方案”等结论,并在此基础上提出了问题的解算方法。对于武器型号不同的情形,提出了“循序最优枚举法”,并得出有关结论。