电子侦察卫星联合侦察的混合调度算法

针对电子侦察卫星的使用约束,及不同任务的调度需求,建立了电子侦察卫星联合侦察的多目标混合整数规划模型.利用进化算法的全局搜索能力和变邻域搜索的局部优化能力,提出了一种多目标进化算法和变邻域搜索相结合两阶段混合调度算法MOEA VNS.针对问题多时间窗组合优化特点,设计了进化算子与邻域移动算子,在确保解多样性的同时使算法...     

神经网络在某交流伺服系统建模中的应用

针对某交流伺服系统的模型辨识问题,提出了基于遗传算法优化的BP神经网络的辨识方法.BP神经网络在非线性系统的辨识中已得到了广泛的使用,但是其存在易陷入局部极小值和对网络结构初值要求高等缺点.根据遗传算法具有全局寻优的特点,先用遗传算法优化得到神经网络权值和阈值的初值,再由BP算法进行局部寻优.辨识结果表明,该算法辨识精度高、收敛速度快.     

兵力编成结构裁剪中指挥关系优化研究

由于决策个体控制战场作战平台资源实体,通过平台资源实体执行作战任务,作战平台资源实体在任务上的聚集导致决策个体间需要复杂的交互协作与交流,兵力编成需要为任务的执行创造良好的交互结构。基于任务执行的兵力编成包括两方面的内容:一是指控决策结点间的协作关系;二是指控决策结点间的指挥关系。本文基于决策个体在任务上的协作关系设计兵力编成的指挥关系,以最小化编成中总的协作工作负载为目标,并描述了编成指挥决策关系的生成过程,对生成过程的求解采用了优化协作树算法。     

改进的粒子群神经网络在飞控中的应用

针对BP神经网络对初始值敏感、容易陷入局部寻优且收敛速度较慢,提出用粒子群对神经网络的参数进行优化,同时设计了衰减的指数函数对惯性权重进行动态调整以提高算法性能.并应用该算法对导弹飞控系统的逆误差进行补偿,仿真结果表明,该方法对逆误差进行了有效的补偿,避免了局部寻优并提高了学习效率.     

基于双向启发式属性约简的战术决策建模研究

从预警机指挥引导的多机协同空战原则分析出发,针对超视距协同空战决策过程中的不确定性和不完备性问题,提出了一种不完备信息系统中的基于双向启发式属性约简的战术粗决策建模方法。首先考虑粗糙集决策过程中条件属性发生缺失或不确定的情况,根据扩展不完备信息概念建立了不完备决策信息系统的最优完备选择;其次基于分辨矩阵的属性约简算法,以属性频度的大小作为启发信息进行决策信息系统约简的双向选择,得出决策信息系统的最佳约简集合;然后依据使决策最有可能发生的原则,给出决策信息系统的最优选择,以该最优选择为代表提取出决策规则;最后根据软、硬杀伤结合使用的CGF实体超视距协同空战作战想定,建立了CGF实体综合战术决策模型,并通过作战决策实例对该方法的正确性和有效性进行了验证。结果表明：该方法能在作战态势信息不完备的情况下正确给出CGF实体综合战术行为。     

防空旅指挥自动化系统Petri网决策组织结构

结合实战,在给出基本决策单元结构模型的基础上,依据战术原则建立了防空旅决策组织结构的Petri网表示模型,在决策单元的结构模型中信息处理分为四级:态势评估级(SA)、信息融合级(IF)、资源分配级(RA)、响应选择级(RS).就决策中同级决策组织结构分三种形式(集中式、分布式和混合式)进行了建模,并对三种形式进行了利弊分析,为防空旅C4ISR系统中决策组织结构的设计和分析提供了依据.     

多无人机协同攻击目标决策

论文针对多架无人机相互协作攻击多个敌对目标的武器目标分配决策问题进行了研究。利用层次分析法（AHP）和灰色关联分析法评估了威胁指标的权重,针对协同攻击空战模型中受威胁大的无人机无需参与攻击,而采用机动躲避策略的特定情况提出了一种启发式遗传模拟退火（HGASA）求解算法,实现了武器目标攻击决策的求解。仿真实验表明,本文提出的HGASA算法对决策方案的求解速度和求解质量与现有的遗传算法(GA)、模拟退火算法(SA)等算法相比均有明显提高。     

基于迭代结构滤波器的SAR图像去噪方法研究

通过比较各种合成孔径雷达 (SAR)图像的滤波方法 ,指出他们存在的不足。然后提出基于模拟退火的迭代滤波器的SAR图像滤波方法。这种方法通过引入相关邻域模型 ,描述图像的局部特性。首先建立一系列反映方向信息的模板 ,每一个模板代表了一种邻域结构。然后在SAR图像的统计性质基础上 ,对于每个邻域结构 ,利用Bayes方法 ,根据图像的观测值 ,获得强度真实值的最大后验概率 (MAP)估计。然后运用模拟退火算法 ,根据每个结构的概率随机选取一个邻域结构作为最适合结构 ,它所对应的估计值作为图像真实强度的估计。模拟退火保证随着温度逐步趋向于 0 ,算法可以获得估计的全局最优解     

基于DoDAF的天基预警系统体系结构模型研究

借鉴美国国防部体系结构框架思想(department of defense architecture framework,DoDAF),从核心体系结构实体、体系结构建模集和建模步骤几方面研究了以数据为中心的体系结建模方法,针对天基预警系统的特点和在反导中的应用,采用体系结构工具system architect(SA)从作战层面建立了典型的天基预警系统体系结构模型,对理解天基预警系统体系结构、开展天基预警系统顶层设计研究具有一定的参考价值。     

稳健局部线性嵌入方法

针对局部线性嵌入方法对于噪声的敏感性,从分析噪声对数据集局部特性的影响入手,提出了稳健局部线性嵌入方法。通过与局部线性嵌入方法的理论分析和实例对比,表明稳健局部线性嵌入方法不仅对噪声影响不敏感,而且对邻域的选择有较好的适应性,可更好地挖掘数据集的本征特性,具有更强的数据可视化能力。     

A New Chaotic Genetic Hybrid Algorithm and Its Applications in Mechanical Optimization Design

A new chaotic genetic hybrid algorithm(CGHA) based on float point coding was put forward in this paper.Firstly,it used chaos optimization to search coarsely and produced a better initial population.Then,a power function carrier was adopted to improve the ergodicity and the sufficiency of the chaos optimization.Secondly,the genetic algorithm(GA) was used to search finely and guaranteed the population's evolution.To avoid the search being trapped in local minimum,a chaos degenerate mutation operator was designed to make the search converge to a global optimum quickly.Finally,CGHA was used to solve a typical mechanical optimization problem of shear stress checking for a cylinder helix spring.Compared with traditional penalty function method,chaos-Powell hybrid algorithm and standard GA,CGHA shows better performance in solution precision and convergence speed than those of the algorithms.Therefore,CGHA is a new effective way to solve the problems in mechanical optimization design.     

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.     

An algorithm for the discrete bilevel programming problem

The bilevel programming problem (BLPP) is an example of a two-stage, noncooperative game in which the first player can influence but not control the actions of the second. This article addresses the linear formulation and presents a new algorithm for solving the zero-one case. We begin by converting the leader's objective function into a parameterized constraint, and then attempt to solve the resultant problem. This produces a candidate solution that is used to find a point in the BLPP feasible reagion. Incremental improvements are sought, which ultimately lead to a global optimum. An example is presented to highlight the computations and to demonstrate some basic characteristics of the solution. Computational experience indicates that the algorithm is capable of solving problems with up to 50 variables in a reasonable amount of time.     

Algorithms for the minimax transportation problem

In this paper, we consider a variant of the classical transportation problem as well as of the bottleneck transportation problem, which we call the minimax transportation problem. The problem considered is to determine a feasible flow x_ij from a set of origins I to a set of destinations J for which max_(i,j)εIxJ{c_ijx_ij} is minimum. In this paper, we develop a parametric algorithm and a primal-dual algorithm to solve this problem. The parametric algorithm solves a transportation problem with parametric upper bounds and the primal-dual algorithm solves a sequence of related maximum flow problems. The primal-dual algorithm is shown to be polynomially bounded. Numerical investigations with both the algorithms are described in detail. The primal-dual algorithm is found to be computationally superior to the parametric algorithm and it can solve problems up to 1000 origins, 1000 destinations and 10,000 arcs in less than 1 minute on a DEC 10 computer system. The optimum solution of the minimax transportation problem may be noninteger. We also suggest a polynomial algorithm to convert this solution into an integer optimum solution.     

A descent approach to solving the complementary programming problem

In recent years, much attention has focused on mathematical programming problems with equilibrium constraints. In this article we consider the case where the constraints are complementarity constraints. Problems of this type arise, for instance, in the design of traffic networks. We develop here a descent algorithm for this problem that will converge to a local optimum in a finite number of iterations. The method involves solving a sequence of subproblems that are linear programs. Computational tests comparing our algorithm with the branch-and-bound algorithm in [7] bear out the efficacy of our method. When solving large problems, there is a definite advantage to coupling both methods. A local optimum incumbent provided by our algorithm can significantly reduce the computational effort required by the branch-and-bound algorithm.     

模糊优选动态规划在稀缺军事资源配置中的应用

在对稀缺军事资源配置问题进行数学描述的基础上,建立起评价指标相对优属度计算模型,实现了局部优选。在此基础上,通过分配目标综合评价模型实现了对局部优选数据的综合处理,最后建立资源分配的动态规划模型实现了对方案的优选。最后通过实例演示了解决该类问题的具体方法和步骤,对部队建设具有一定的参考和应用价值。     

基于改进匈牙利算法的多技能人员调度方法

人员的优化配置对于提高装备制造效率具有重要意义。针对经典匈牙利算法不能解决具有并联环节的人员指派问题的不足,提出利用虚拟工作代替并联环节,将问题转化为典型的指派问题;通过判断虚拟工作的可实现性,迭代搜索得到最优解。以某多技能人员任务指派系统为例,详细介绍了该优化方法的步骤。优化结果很好地验证了改进算法的有效性。     

Local search techniques for the generalized resource constrained project scheduling problem

In this article we address the problem of scheduling a single project network with both precedence and resource constraints through the use of a local search technique. We choose a solution definition which guarantees precedence feasibility, allowing the procedure to focus on overcoming resource infeasibility. We use the 110-problem data set of Patterson to test our procedure. Our results indicate a significant improvement over the best heuristic results reported to date for these problems (Bell and Han [1]). Two major advantages of the local search algorithm are its ability to handle arbitrary objective functions and constraints and its effectiveness over a wide range of problem sizes. We present a problem example with an objective function and resource constraints which include nonlinear and non-continuous components, which are easily considered by the procedure. The results of our algorithm are significantly better than random solutions to the problem. © 1993 John Wiley & Sons, Inc.     

文章编号：基于多目标进化搜索算法的AUV地磁仿生导航方法

针对水下自主航行器(AUV)地磁多参量多目标搜索的问题,提出了一种基于磁趋势敏感的多目标进化搜索算法。在进化算法的结构下,利用地磁场参量与导航路径的约束关系,以磁趋势敏感作为后验评估准则,建立导航模型,使得地磁多分量伴随航行器的运动同时同地收敛至各自目标值,实现导航目的。通过与六边形路径搜索算法的仿真对比,验证了多目标进化搜索算法的有效性和优越性。     

防空监视网络传感器资源分配的最优化

针对防空监视网络的传感器管理问题,讨论了传感器资源分配的最优化方法。提出了把传感器资源分配问题映射为多代理系统分布约束最优化问题的解决策略,设计了基于约束代价下界搜索的异步分枝定界最优化算法,实现了传感器资源分配问题最优解的异步并行搜索,给出的仿真实例说明了传感器资源分配最优化方法的有效性。