基于马尔柯夫决策过程动态WTA最优化模型分析

在作战过程中,通过把目标群的威胁程度作为目标函数制定决策,可将目标分配决策过程变成马尔柯夫决策过程.即首先对攻防作战态势进行抽象性描述,建立基于马尔柯夫决策过程动态WTA最优化模型,然后提出了有限次迭代求解最优策略的新方法,并进行了算例验证和分析.结果表明该方法可使武器系统获得最大的射击效率,并能有效地减少重点目标突防的概率.     

攻击机靶场效能优化:概念、方法与基本问题

系统阐述了攻击机靶场攻击、靶场效能以及靶场效能优化等基本概念,在此基础上,分析了攻击机靶场效能优化的基本任务和基本问题,并给出了形式化描述。     

Partitioning of biweighted trees

A districting problem is formulated as a network partitioning model where each link has one weight to denote travel time and another weight to denote workload. The objective of the problem is to minimize the maximum diameter of the districts while equalizing the workload among the districts. The case of tree networks is addressed and efficient algorithms are developed when the network is to be partitioned into two or three districts. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 143–158, 2002; DOI 10.1002/nav.10003     

天地测控资源调度的两阶段递进遗传算法

为对天地测控资源调度进行高效求解,设计了两阶段递进遗传算法对其进行优化调度。鉴于问题的目标具有一定的可分性,以时间为依据将被调度弧段划分成两个部分,在对第一部分形成种群并作进化求解的基础上,将其最优解与第二部分弧段组合,并作进一步的进化求解。为了缓解两阶段优化的局部搜索特性,在第一阶段个体适应度计算中,以一定概率设定虚拟弧段,保留具有潜在全局优势的个体。仿真表明该方法能在确保求解质量的前提下明显减少运算时间。     

Adaptive random search for continuous simulation optimization

We present, analyze, and compare three random search methods for solving stochastic optimization problems with uncountable feasible regions. Our adaptive search with resampling (ASR) approach is a framework for designing provably convergent algorithms that are adaptive and may consequently involve local search. The deterministic and stochastic shrinking ball (DSB and SSB) approaches are also convergent, but they are based on pure random search with the only difference being the estimator of the optimal solution [the DSB method was originally proposed and analyzed by Baumert and Smith]. The three methods use different techniques to reduce the effects of noise in the estimated objective function values. Our ASR method achieves this goal through resampling of already sampled points, whereas the DSB and SSB approaches address it by averaging observations in balls that shrink with time. We present conditions under which the three methods are convergent, both in probability and almost surely, and provide a limited computational study aimed at comparing the methods. Although further investigation is needed, our numerical results suggest that the ASR approach is promising, especially for difficult problems where the probability of identifying good solutions using pure random search is small. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

A stochastic gradual cover location problem

Covering models assume that a point is covered if it is within a certain distance from a facility and not covered beyond that distance. In gradual cover models it is assumed that a point is fully covered within a given distance from a facility, then cover gradually declines, and the point is not covered beyond a larger distance. Gradual cover models address the discontinuity in cover which may not be the correct approach in many situations. In the stochastic gradual cover model presented in this article it is assumed that the short and long distances employed in gradual cover models are random variables. This refinement of gradual cover models provides yet a more realistic depiction of actual behavior in many situations. The maximal cover model based on the new concept is analyzed and the single facility location cover problem in the plane is solved. Computational results illustrating the effectiveness of the solution procedures are presented. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

C2组织鲁棒性信息交互结构设计及分析

介绍了C2组织的信息交互结构及其设计约束,讨论了C2组织鲁棒性信息交互结构的设计问题。提出了基于启发式嵌套遗传算法的鲁棒性信息交互结构设计方法:外层遗传算法对信息交互结构的拓扑及链路容量进行优化搜索;内层嵌套遗传算法依据对路由的搜索优化出多个使命邻域下最小延时集合,将其依概率平均化后返回外层来对链路容量的鲁棒性进行评价。案例分析和对比试验表明该方法可以实现鲁棒性较强的组织信息交互结构。     

装备维修资源优化中的模拟退火遗传算法

在对模拟退火遗传算法改进的基础上,结合建立的通信装备维修资源分配模型,给出了该算法的实现过程,并利用此算法对模型进行了最优化求解。实例的计算结果表明该算法对于模型的求解具有较好的收敛性。     

滑翔增程弹滑翔弹道优化设计分析

针对鸭式布局的滑翔增程弹,建立了滑翔增程弹滑翔弹道的模型,采用使滑翔弹道上每一点的升阻比最大的设计思想进行弹道优化设计,导出了俯仰舵偏角与平衡攻角的表达式,并对滑翔飞行弹道特性进行了仿真计算分析.仿真计算表明,滑翔弹道与常规弹道降弧段相比下降趋缓,增程效果显著.     

基于遗传算法的多目标虚拟装配路径规划

针对以往求解路径规划问题中以路径最短为目标的局限性以及随机选取初始路径的缺陷,引入合适的目标函数和遗传算子,提出了一种基于遗传算法的多目标虚拟装配路径规划方法,利用大范围初始化的方式产生具有代表性的初始群体,设计了具有启发作用、适合路径规划的遗传算子,能够同时得到不同特点的多条路径,优化了装配路径.