基于多资源点的装备应急器材调度决策模型

针对装备应急器材调度决策问题,从调度路径优化和调度计划分配2个方面,研究了其多目标优化模型的构建。将资源点划分为若干级别来确定资源点选取的优先次序,通过先求解资源点与需求点之间的最优路径,后求解器材资源分配量的思路,建立了装备应急器材调度决策的广义最优路径模型和运输模型,采用改进的Dijkstra算法对模型进行求解,仿真结果表明:所构建的决策模型及算法是有效的。     

黄葛增压站噪声治理工艺措施

为解决黄葛增压站内4台室外整体式天然气压缩机组造成的噪声污染问题,结合生产运行要求、周边环境状况、噪声源分布及噪声特性,综合吸声、隔声、消声、阻尼减振、通风和泄压等技术,采用半密闭式降噪厂房和阻抗复合排气消声器等治理措施。治理后厂界噪声从64.2～72.1 dB(A)降至49.7～55.0 dB(A),距厂房最近厂界25 Hz声压值从97.9 dB降至84.2 dB,排气消声器出口噪声从84.3 dB(A)降至72.6 dB(A)且25Hz声压值从124.7 dB降至97 dB。厂界噪声达到GB 12348—2008《工业企业厂界环境噪声排放标准》3类要求,中、低频噪声强度减弱,解决了厂界噪声超标和噪声扰民问题。同时,为整体式天然气压缩机组噪声治理开辟了一条新途径,为日后降噪厂房和阻抗复合排气消声器广泛应用奠定了实践基础,为压缩机组噪声治理设计积累了宝贵经验。     

基于协同学的编队协同空战任务决策

基于协同学理论给出了编队协同空战系统的协同学框架;提出了编队协同作战方案的五元组定义,明确了影响系统进程的序参量;基于系统有序度与协同度的概念,构建了协同效能优化模型;以任务冲突检测与消解为依据给出了任务决策的约束条件;最后以二进制粒子群优化算法对此约束优化问题进行了求解.仿真结果表明,以协同学理论描述编队协同任务决策问题是可行的,构建的协同效能模型与任务决策方法在处理编队时序任务决策问题时是有效的.     

一种新的多属性决策方法

针对模糊多属性决策问题,提出了一种新的属性值以三角模糊数形式给出的模糊多属性决策方法。首先定义了两三角模糊数的中心决策矩阵;其次通过引入方案间优势度和优势度比较矩阵概念及其计算公式,从而给出了方案的排序,实例分析说明了所提出的决策方法的合理性及其算法的有效性。     

舰艇编队对潜水声警戒主/被动探测转换区的决策指挥

从大型舰艇编队反潜战术及水声装备作战使用的角度出发,提出了水声警戒主/被动转换区的概念,分析了各种影响因素及其相互关系,研究了水声警戒主/被动转换区的计算方法,建立了转换区的数学模型,得出了多潜艇突防编队警戒幕的概率和水面舰艇编队的对潜警戒探测能力,提出了水声警戒主/被动转换区决策与指挥的方法。     

大区域防空作战条件下防空兵作战方案的优选

大区域防空作战条件下防空作战指挥决策往往面临的是多目的(指标)决策,在分析作战指标的基础上对所选作战方案的益损值进行标准化处理和贴近度排序,并求出各方案的排序频数,将其转化为最优线性分派模型进行优化,从而使所有方案得到总体最优排序。     

基于．NET的装备保障辅助决策系统（ESADS）的设计与实现

介绍了一种基于.NET框架的异构数据库应用系统的集成方法,并设计开发了战时装备保障辅助决策系统。该方法利用XML的特点和.NET技术,将原有的应用系统数据源与系统分离,并能在各异构数据库之间快速交互数据,从而共享原有的装备管理信息,为战时装备保障决策提供数据资源。     

一种动态门限群签名方案的安全性分析

门限群签名是群签名的推广,其中只有授权子集才能代表整个群体进行签名。一旦发生纠纷,签名成员的身份可以被追查出来。指出一种动态门限群签名方案有冗余,提出了针对该签名三种攻击。分析结果证明该门限群签名方案不具有防冒充性,不能抵抗合谋攻击,门限的动态更新、群成员注销和系统密钥更新也不安全。     

Efficient sequential decision‐making algorithms for container inspection operations

Following work of Stroud and Saeger (Proceedings of ISI, Springer Verlag, New York, 2006) and Anand et al. (Proceedings of Computer, Communication and Control Technologies, 2003), we formulate a port of entry inspection sequencing task as a problem of finding an optimal binary decision tree for an appropriate Boolean decision function. We report on new algorithms for finding such optimal trees that are more efficient computationally than those presented by Stroud and Saeger and Anand et al. We achieve these efficiencies through a combination of specific numerical methods for finding optimal thresholds for sensor functions and two novel binary decision tree search algorithms that operate on a space of potentially acceptable binary decision trees. The improvements enable us to analyze substantially larger applications than was previously possible. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Production‐inventory systems with imperfect advance demand information and updating

We consider a supplier with finite production capacity and stochastic production times. Customers provide advance demand information (ADI) to the supplier by announcing orders ahead of their due dates. However, this information is not perfect, and customers may request an order be fulfilled prior to or later than the expected due date. Customers update the status of their orders, but the time between consecutive updates is random. We formulate the production‐control problem as a continuous‐time Markov decision process and prove there is an optimal state‐dependent base‐stock policy, where the base‐stock levels depend upon the numbers of orders at various stages of update. In addition, we derive results on the sensitivity of the state‐dependent base‐stock levels to the number of orders in each stage of update. In a numerical study, we examine the benefit of ADI, and find that it is most valuable to the supplier when the time between updates is moderate. We also consider the impact of holding and backorder costs, numbers of updates, and the fraction of customers that provide ADI. In addition, we find that while ADI is always beneficial to the supplier, this may not be the case for the customers who provide the ADI. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011