军事能力到装备系统的双层规划模型及其求解算法

阐述了基于能力的军事规划新思路,提出了从军事能力到系统项目的两层规划模型。该模型上层以效果和效果-成本比值最大化为目标,通过资本规模来约束下层决策。下层以各种能力最大化为目标,在成本约束下寻求不同系统项目的最佳组合,并将结果返回上层影响最终的决策。应用了多目标遗传算法来求解该规划模型。算例结果表明,所建立的双层规划模型及其求解算法对于国防资源分配问题是有效的。     

一种基于多目标优化的QoS路由交互式算法

为了满足通信网络中一些特定业务对于多个网络指标性能的同时要求 ,研究了一类基于多目标决策的QoS路由算法。通过选取带宽作为约束条件 ,把时延和丢失率作为优化目标 ,建立了QoS路由选择的多目标非线性整数规划模型 ,并给出了一种求解模型的交互式算法。该算法通过逐步调整目标函数的上界 ,压缩目标函数的搜索空间来满足决策者的要求和网络条件。实例计算结果表明了算法的可行性     

用结构自适应前馈网络解算多目标导弹攻击区

多目标导弹攻击区的实时解算是机载多目标攻击武器系统得以技术实现的中心环节。阐述了“多目标导弹攻击区”的概念 ,探索了其解算的技术途径 ,提出了“实时、高精度和低存储”的解算要求。根据上述技术要求 ,设计了基于网络灵敏度统计分析的多层前馈网络结构自适应算法 ,以用于训练合适规模的多层前馈网络逼近器。在此基础上 ,进行了系统仿真研究 ,研究的结果表明了该方案的应用前景。     

陆地车辆导航仪中方位保持温控系统的研究

针对方位保持部件温控系统 ,提出了一种分时分段 PID控制与级间控制相结合的三级温控方案 ,以及用遗传算法进行参数整定的方法。同时 ,介绍了温控系统的软、硬件实现 ,并给出了试验结果。     

匈牙利算法在多目标分配中的应用

在多目标攻击决策中 ,根据 Harold提出的目标优势函数 ,分析了使所有目标机的总优势函数为指派问题 ,运用匈牙利算法对 n对 n的最优目标分配指派问题进行求解 ,并把它推广至 n对 m的多目标分配中。仿真结果表明匈牙利算法对于此类多目标分配指派问题的求解是十分有效的。     

Two-agent scheduling with linear resource-dependent processing times

This paper considers a two-agent scheduling problem with linear resource-dependent processing times, in which each agent has a set of jobs that compete with that of the other agent for the use of a common processing machine, and each agent aims to minimize the weighted number of its tardy jobs. To meet the due date requirements of the jobs of the two agents, additional amounts of a common resource, which may be in discrete or continuous quantities, can be allocated to the processing of the jobs to compress their processing durations. The actual processing time of a job is a linear function of the amount of the resource allocated to it. The objective is to determine the optimal job sequence and resource allocation strategy so as to minimize the weighted number of tardy jobs of one agent, while keeping the weighted number of tardy jobs of the other agent, and the total resource consumption cost within their respective predetermined limits. It is shown that the problem is -hard in the ordinary sense, and there does not exist a polynomial-time approximation algorithm with performance ratio unless ; however it admits a relaxed fully polynomial time approximation scheme. A proximal bundle algorithm based on Lagrangian relaxation is also presented to solve the problem approximately. To speed up convergence and produce sharp bounds, enhancement strategies including the design of a Tabu search algorithm and integration of a Lagrangian recovery heuristic into the algorithm are devised. Extensive numerical studies are conducted to assess the effectiveness and efficiency of the proposed algorithms.     

如何改善路径测试用例生成的搜索算法

软件结构测试数据生成一直是软件测试领域一个较为复杂的问题,方法和手段尚未成熟。基于程序直接执行的测试数据生成方法因其动态性,显示出一定的优越性,本文主要针对该方法的核心部分——搜索算法进行讨论,探讨了有助于改善其功能的若干手段,目的在于提高算法效率,提高其实用化程度,显示出较好的实验效果。     

海战场态势评估问题的研究

对海战场综合态势进行态势评估和威胁分析是信息融合系统的最高层级,态势评估结果将对指挥员的指挥决策起到非常重要的作用。根据海军作战理论分析了海战场态势的表示方法,并基于模板方法设计了一种战场当前态势与模板数据库中态势进行匹配的算法。该算法特别适用于高层推理如态势或威胁评估。     

Algorithms for the multi‐item multi‐vehicles dynamic lot sizing problem

We consider a two‐stage supply chain, in which multi‐items are shipped from a manufacturing facility or a central warehouse to a downstream retailer that faces deterministic external demand for each of the items over a finite planning horizon. The items are shipped through identical capacitated vehicles, each incurring a fixed cost per trip. In addition, there exist item‐dependent variable shipping costs and inventory holding costs at the retailer for items stored at the end of the period; these costs are constant over time. The sum of all costs must be minimized while satisfying the external demand without backlogging. In this paper we develop a search algorithm to solve the problem optimally. Our search algorithm, although exponential in the worst case, is very efficient empirically due to new properties of the optimal solution that we found, which allow us to restrict the number of solutions examined. Second, we perform a computational study that compares the empirical running time of our search methods to other available exact solution methods to the problem. Finally, we characterize the conditions under which each of the solution methods is likely to be faster than the others and suggest efficient heuristic solutions that we recommend using when the problem is large in all dimensions. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

基于改进卡尔曼滤波方法的机动目标跟踪研究

针对在机动目标跟踪中当目标作高度机动飞行时卡尔曼滤波可能会出现严重发散的情况,提出利用BP神经网络校正其滤波结果,并将遗传算法应用于BP网络的训练过程,以解决BP网络训练速度慢的缺陷,提高算法的实时性。仿真表明该方法是可行的、有效的。