时序电路测试中敏化路径选择研究

时序电路测试产生过程中,在进行敏化路径选择时会遇到失败问题.本文针对迭代组合阵列模型测试中产生的这些问题进行了有益的探讨,并提出了改进的时序电路测试产生算法,使之更加完善.     

卫星数传调度模型研究

卫星数传调度问题是一个具有多时间窗口、多资源约束的优化问题。针对该问题,建立了卫星数传需求模型、任务模型和调度模型。在建模过程中,采用了框架模型形式,把问题中的主要约束封闭于每个数传任务中,这在降低调度模型复杂度的同时,也降低了调度算法设计难度。还提出了调度算法设计思想,并设计了一基于灵活度的调度算法。仿真表明,所建立的模型及算法对解决卫星数传调度问题是可行的。     

战时交通运输路径优化研究

以战时交通运输路径优化问题为研究对象,分析问题特点,考虑多式联运,以运输时间代价、运输费用代价、路段和运输节点的危险性代价为优化目标,建立起广义运输代价最小的运输路径优化模型,并设计了蚁群算法来求解问题模型。给出的算例表明,文中模型符合战时交通运输的特点和实际需要,可为确定战时运输路径提供决策支持,而采用的蚁群算法是求解该问题的一种有效方法。     

Single- and multiple-processor models for minimizing completion time variance

This article concerns the scheduling of n jobs around a common due date, so as to minimize the average total earliness plus total lateness of the jobs. Optimality conditions for the problem are developed, based on its equivalence to an easy scheduling problem. It seems that this problem inherently has a huge number of optimal solutions and an algorithm is developed to find many of them. The model is extended to allow for the availability of multiple parallel processors and an efficient algorithm is developed for that problem. In this more general case also, the algorithm permits great flexibility in finding an optimal schedule.     

一种面向公共服务的跨域授权模型的研究及实现

文章提出一种基于策略的RBAC的跨域统一授权模型,在基于策略的RBAC单域授权模型的研究基础上,扩展单域模型为多域模型,通过授权控制中心之间建立跨域级联机制,构成广域授权网络,实现面向多应用系统、大型公共服务域的跨域统一自动授权机制.     

基于动量BP神经网络的确定掩护重点问题研究

确定掩护重点是地面防空作战的一个重点和难点问题。通过分析影响确定掩护重点问题的主要因素,建立评价指标体系,利用动量BP神经网络解决了确定掩护重点的评价模型,并采用MATLAB6.5的神经网络工具箱进行仿真实现。方法较好地降低主观误差,为确定被掩护目标重要性排序和兵力分配提供了依据。通过对BP算法的改进,减少了误差,提高了学习速度。模型思路清晰,算法简单实用,较好地解决了防空兵辅助决策系统智能确定掩护重点目标的问题。     

基于熵权灰关联法的基地防空作战方案优选

海军基地防空作战方案优选问题是海军基地防空作战指挥决策的重要内容,其实质是一个多目标(指标)决策问题。尝试将熵值理论与灰色关联分析法结合,建立基于熵权的灰色关联分析模型,有效地解决了权重分配偏差问题,并在分析作战指标的基础上对待选方案进行加权关联度排序,从而得到总体方案最优排序结果。     

基于灰色关联分析的防空兵力编组方案优选

要地防空中需要研究的问题很多，其中要地防空兵力编组方案优选是研究的重点问题之一，首先对灰关联分析方法和要地防空兵力编组的关联性进行了分析，然后在兵力部署要求的基础上，建立了评价指标体系及其量化分析，最后采用灰关联分析方法建立了方案优选模型，具体的实例验证了基于灰关联分析的兵力编组优选模型的可行性和有效性，为要地防空兵力编组方案的优选问题提供了一种量化的新思路。     

改进博弈论的舰载无人机编队协同对海突击目标分配

目标分配问题是UAV自主控制的重要问题。针对舰载无人机编队协同对海突击目标分配问题,首先建立了基于离散动态贝叶斯网络的目标价值评估模型,在此基础上构建了舰载无人机编队的益损值矩阵,设计了舰载无人机编队协同对海突击目标分配的决策函数,提出了一种基于改进博弈论的目标分配方法,为4种不同约束条件下的目标分配问题分别设计了算法。最后对所建立的目标价值评估模型和改进博弈论的目标分配算法进行了实例仿真,仿真结果表明了模型和算法的可行性和有效性。     

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     

基于改进的混合高斯模型的背景建模方法

提出了一种基于改进的混合高斯模型的背景建模方法,克服了经典混合高斯模型方法计算量大和对长时间静止物体转为运动及光照突变较为敏感的缺点。首先,在经典混合高斯模型方法的基础上,引入了一种新的高斯分布个数的自适应选择策略,提高了建模效率。其次,分析了经典混合高斯模型方法对长时间静止物体转为运动及光照突变较为敏感的原因,采用了一种不同区域更新率的自适应选择策略,能够迅速响应场景的变化,有效地解决了大面积误检问题。通过在典型的场景下与经典混合高斯模型方法进行比较,验证了本文算法的有效性。     

考虑战损件回收再造的战场军需备件供应优化研究

在考虑军需备件需求和战损件修复不确定性的条件下,研究了战场上军需备件供应优化问题,建立了优化问题的数学模型,证明了模型的凸函数特性,给出了模型的最优解析解计算方法.     

具有战时随机延误与损耗的多配送中心路径优化

建立了具有战时随机延误与损耗的多配送中心配送路径安排模型,给出了基于随机模拟的蚁群算法。算法通过给定残存率、用时与置信度阈值,把多目标问题作为单目标来处理。用随机模拟的方法来求路径的置信度,并以此为基础搜索转移策略的临域与判断未遍历点的插入位置。算法设计了符合问题特点的从虚拟点出发的转移策略与对两类路段不同的信息素更新策略,确保算法的实现。最后,通过算例说明了该方法的可行性与有效性。     

A combination of Lagrangian relaxation and column generation for order batching in steelmaking and continuous‐casting production

This article considers the order batching problem in steelmaking and continuous‐casting production. The problem is to jointly specify the slabs needed to satisfy each customer order and group all the slabs of different customer orders into production batches. A novel mixed integer programming model is formulated for the problem. Through relaxing the order assignment constraints, a Lagrangian relaxation model is then obtained. By exploiting the relationship between Lagrangian relaxation and column generation, we develop a combined algorithm that contains nested double loops. At the inner loop, the subgradient method is applied for approximating the Lagrangian dual problem and pricing out columns of the master problem corresponding to the linear dual form of the Lagrangian dual problem. At the outer loop, column generation is employed to solve the master problem exactly and adjust Lagrangian multipliers. Computational experiments are carried out using real data collected from a large steel company, as well as on large‐scaled problem instances randomly generated. The results demonstrate that the combined algorithm can obtain tighter lower bound and higher quality solution within an acceptable computation time as compared to the conventional Lagrangian relaxation algorithm. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

反舰导弹仿真中的目标命中判断问题

阐述了模型校核的意义和作用。对属于模型校核范畴的仿真中的系统状态不连贯问题的基本概念通过乒乓球的下落和反舰导弹攻击目标舰艇的例子进行了说明。介绍了已有的解决系统状态不连贯问题的三种方法,并进行了优、缺点分析。给出了反舰导弹仿真中的目标命中判断模型。指出,反舰导弹仿真中的目标命中判断问题是一个系统状态不连贯问题。为解决该问题,提出并应用了一种新方法预测法。利用预测法,最多进行两步最小步长仿真,就能够以要求的精确度检测到任何一个系统状态不连贯。相对于以前的三种方法,在提高仿真效率的同时,预测法还能够避免对系统状态不连贯问题的漏检。     

Managing components for assemble‐to‐order products with lead‐time‐dependent pricing: The full‐shipment model

We study a component inventory planning problem in an assemble‐to‐order environment faced by many contract manufacturers in which both quick delivery and efficient management of component inventory are crucial for the manufacturers to achieve profitability in a highly competitive market. Extending a recent study in a similar problem setting by the same authors, we analyze an optimization model for determining the optimal component stocking decision for a contract manufacturer facing an uncertain future demand, where product price depends on the delivery times. In contrast to our earlier work, this paper considers the situation where the contract manufacturer needs to deliver the full order quantity in one single shipment. This delivery requirement is appropriate for many industries, such as the garment and toy industries, where the economies of scale in transportation is essential. We develop efficient solution procedures for solving this optimization problem. We use our model results to illustrate how the different model parameters affect the optimal solution. We also compare the results under this full‐shipment model with those from our earlier work that allows for multiple partial shipments. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Balancing and optimizing a portfolio of R&D projects

A mathematical formulation of an optimization model designed to select projects for inclusion in an R&D portfolio, subject to a wide variety of constraints (e.g., capital, headcount, strategic intent, etc.), is presented. The model is similar to others that have previously appeared in the literature and is in the form of a mixed integer programming (MIP) problem known as the multidimensional knapsack problem. Exact solution of such problems is generally difficult, but can be accomplished in reasonable time using specialized algorithms. The main contribution of this paper is an examination of two important issues related to formulation of project selection models such as the one presented here. If partial funding and implementation of projects is allowed, the resulting formulation is a linear programming (LP) problem which can be solved quite easily. Several plausible assumptions about how partial funding impacts project value are presented. In general, our examples suggest that the problem might best be formulated as a nonlinear programming (NLP) problem, but that there is a need for further research to determine an appropriate expression for the value of a partially funded project. In light of that gap in the current body of knowledge and for practical reasons, the LP relaxation of this model is preferred. The LP relaxation can be implemented in a spreadsheet (even for relatively large problems) and gives reasonable results when applied to a test problem based on GM's R&D project selection process. There has been much discussion in the literature on the topic of assigning a quantitative measure of value to each project. Although many alternatives are suggested, no one way is universally accepted as the preferred way. There does seem to be general agreement that all of the proposed methods are subject to considerable uncertainty. A systematic way to examine the sensitivity of project selection decisions to variations in the measure of value is developed. It is shown that the solution for the illustrative problem is reasonably robust to rather large variations in the measure of value. We cannot, however, conclude that this would be the case in general. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 18–40, 2001     

基于RCS的三维低可探测性轨迹优化方法

针对基于雷达散射截面(RCS)规避雷达威胁的飞行轨迹优化问题,提出了低可探测性三维轨迹优化的求解方法.通过B样条拟合构建连续可微的RCS数据模型,结合三维飞行动力学模型,建立规避雷达威胁下的飞行运动控制模型.将轨迹优化问题描述成为最优控制问题,其中飞行姿态控制、轨迹约束、边界条件作为约束条件,以降低雷达探测概率和减少飞行时间为目标函数.运用高斯伪谱法( GPM)将连续的最优控制问题转换为离散的非线性规划问题进行求解.仿真结果证明本文方法实现了求解单基地雷达和双基地雷达探测环境中低可探测性三维轨迹优化问题,有效降低了飞行过程中的雷达探测概率和暴露时间.     

基于遗传算法的应急物流多设施选址模型研究

在现有研究的基础上,建立了应急物流多设施选址模型。在模型建立过程中除了考虑距离这一基本要素,还考虑了流量与安全性等道路特性,并将其转换为道路的综合权值,使模型更具现实意义。采用遗传算法求解,使该问题的求解过程得到简化。最后用实例对模型进行了验证分析,说明该模型的合理性。     

基于跟踪精度控制的多传感器管理方法

针对地面机动目标跟踪过程中的多传感器管理问题展开了研究，设计了一种基于跟踪精度控制的多传感器多目标分配方法。首先，在考虑目标与目标之间、目标与传感器之间和传感器与传感器之间等的多种约束条件下运用基于协方差控制的思想建立了多传感器多目标分配问题的优化模型；接着将等价伪量测的异步融合算法与IMM算法结合，计算各目标在不同融合周期的跟踪精度估计值；最后，以目标的跟踪精度需求为出发点，结合蚁群算法的思想，设计了一种求解所建立的多传感器多目标分配问题的优化模型的算法。仿真结果表明：该管理方法能在确保跟踪精度需求的前提下，根据对各目标跟踪任务的重要程度，合理地调度传感器资源。