IIR数字滤波器联立优化CAD

文中介绍了多目标联立最佳逼近CAD方法,对各种设计方法的性能作了分析比较,提出了改善途径。程序在IBM-PC/XT微机上运行通过,文中给出了应用线性相位IIR数字滤波器线性规划逼近法设计的低通实例。     

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     

Sequential and systematic sampling plans for the Markov‐dependent production process

Acceptance sampling plans are used to assess the quality of an ongoing production process, in addition to the lot acceptance. In this paper, we consider sampling inspection plans for monitoring the Markov‐dependent production process. We construct sequential plans that satisfy the usual probability requirements at acceptable quality level and rejectable quality level and, in addition, possess the minimum average sample number under semicurtailed inspection. As these plans result in large sample sizes, especially when the serial correlation is high, we suggest new plans called “systematic sampling plans.” The minimum average sample number systematic plans that satisfy the probability requirements are constructed. Our algorithm uses some simple recurrence relations to compute the required acceptance probabilities. The optimal systematic plans require much smaller sample sizes and acceptance numbers, compared to the sequential plans. However, they need larger production runs to make a decision. Tables for choosing appropriate sequential and systematic plans are provided. The problem of selecting the best systematic sampling plan is also addressed. The operating characteristic curves of some of the sequential and the systematic plans are compared, and are observed to be almost identical. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 451–467, 2001     

一类对固定目标的集群搜寻对策问题及求解

利用集群搜索对策的理论与方法 ,建立了集群对固定目标的一类搜索对策模型 ,给出了集群的ε -最优搜寻策略 ,并考虑了其在搜索过程中的应用     

一类多目标模糊系数线性规划问题

讨论了一类所有系数均为模糊数的多目标线性规划问题 .通过对模糊数的比较 ,将模糊多目标线性规划模型转化为清晰的多目标模型 ,并应用一种基于线性隶属函数的模糊规划算法求其协调解 .最后给出了一个数值例子 .     

The selection allocation problem

The Selection Allocation Problem (SAP) is a single period decision problem which involves selecting profit‐maximizing (or cost‐minimizing) activities from various distinct groups, and determining the volume of those activities. The activities in each group are selected subject to the availability of that group's resource, which is provided by either pooling or blending raw inputs from several potential sources. Imbedded in the decision process is the additional task of determining how much raw input is to be allocated to each group to form the resource for that group. Instances of this problem can be found in many different areas, such as in tool selection for flexible manufacturing systems, facility location, and funding for social services. Our goal in this paper is to identify and exploit special structures in the (SAP) and use those structures to develop an efficient solution procedure. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 707–725, 1999     

Response surface analysis of two‐stage stochastic linear programming with recourse

We apply the techniques of response surface methodology (RSM) to approximate the objective function of a two‐stage stochastic linear program with recourse. In particular, the objective function is estimated, in the region of optimality, by a quadratic function of the first‐stage decision variables. The resulting response surface can provide valuable modeling insight, such as directions of minimum and maximum sensitivity to changes in the first‐stage variables. Latin hypercube (LH) sampling is applied to reduce the variance of the recourse function point estimates that are used to construct the response surface. Empirical results show the value of the LH method by comparing it with strategies based on independent random numbers, common random numbers, and the Schruben‐Margolin assignment rule. In addition, variance reduction with LH sampling can be guaranteed for an important class of two‐stage problems which includes the classical capacity expansion model. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 753–776, 1999     

SEA的侦察与监测系统效能分析

侦察与监测系统已成为现代C3I系统的重要组成部分,其效能评估既有C3I系统的一般性又有自身的特殊性。首先在一般系统效能含义上定义了侦察与监测系统的系统效能,比较了几种典型的C3I系统评估方法。在此基础上,将SEA方法应用于分析侦察与监测系统效能,并将情报信息量作为效能度量的指标。最后给出了分析计算过程和仿真结果。     

专题式Web信息检索系统的设计与实现

主要介绍WIRSOS (Webinformationretrievalsystemforordnancesupport)系统设计与实现的关键技术。本系统采用搜索引擎技术 ,利用网络机器人 (WebRobot)采集WWW上信息 ,通过对整篇文档的分词处理和相似性计算 ,针对某一专题信息进行收集 ,从而提高检索效率和精度     

非高斯噪声下的滤波方法

干扰条件下的机动目标跟踪在一些文献[1][2]中已有讨论,但利用多传感器,尤其是被动传感器进行非高斯观测噪声条件下的目标跟踪仍需要研究。本文讨论了被动传感器在随机干扰条件下进行机动目标跟踪的方法,其观测量包含非高斯噪声,也可能包含影响观测值的随机干扰。与基于卡尔曼滤波的常见方法不同,采用动态规划算法进行多假设检验,从而估计目标的状态。仿真试验表明,本文方法能有效地处理非高斯噪声情况下的目标跟踪问题,而基于卡尔曼滤波的跟踪方法,比如EKF,则效果较差。