数据并行程序设计语言中分布数组的地址计算

本文讨论了在大规模并行计算机上实现数据并行程序设计语言的关键问题──分布数组的地址计算问题。文中详细给出了维分布数组的下标地址计算公式,分布数组的内情向量结构以及分布数组映射函数算法,并对有关编译实现技术进行了探讨。     

测试点的选取问题

在故障检测的过程中 ,每个测试点检测需要的时间可能不同。本文研究了如何选取一些测试点 ,使得这些测试点可以检测所有故障 ,而所需时间最少的问题。我们将其转化成整数规划问题 ,并给出一个求解算法 .最后给出一个实例对算法加以说明。     

Heuristics for the multi‐resource generalized assignment problem

The well‐known generalized assignment problem (GAP) involves the identification of a minimum‐cost assignment of tasks to agents when each agent is constrained by a resource in limited supply. The multi‐resource generalized assignment problem (MRGAP) is the generalization of the GAP in which there are a number of different potentially constraining resources associated with each agent. This paper explores heuristic procedures for the MRGAP. We first define a three‐phase heuristic which seeks to construct a feasible solution to MRGAP and then systematically attempts to improve the solution. We then propose a modification of the heuristic for the MRGAP defined previously by Gavish and Pirkul. The third procedure is a hybrid heuristic that combines the first two heuristics, thus capturing their relative strengths. We discuss extensive computational experience with the heuristics. The hybrid procedure is seen to be extremely effective in solving MRGAPs, generating feasible solutions to more than 99% of the test problems and consistently producing near‐optimal solutions. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 468–483, 2001     

An integer programming model for the weekly tour scheduling problem

We study a workforce planning and scheduling problem in which weekly tours of agents must be designed. Our motivation for this study comes from a call center application where agents serve customers in response to incoming phone calls. Similar to many other applications in the services industry, the demand for service in call centers varies significantly within a day and among days of the week. In our model, a weekly tour of an agent consists of five daily shifts and two days off, where daily shifts within a tour may be different from each other. The starting times of any two consecutive shifts, however, may not differ by more than a specified bound. Furthermore, a tour must also satisfy constraints regarding the days off, for example, it may be required that one of the days off is on a weekend day. The objective is to determine a collection of weekly tours that satisfy the demand for agents' services, while minimizing the total labor cost of the workforce. We describe an integer programming model where a weekly tour is obtained by combining seven daily shift scheduling models and days‐off constraints in a network flow framework. The model is flexible and can accommodate different daily models with varying levels of detail. It readily handles different days‐off rules and constraints regarding start time differentials in consecutive days. Computational results are also presented. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 607–624, 2001.     

Applying Lanchester's linear law to model the Ardennes campaign

In modern warfare, many believe the decisive factor in winning a battle is seizing the right moment to shift from defense to attack, or vice versa. This paper attempts to bring that perspective to Lanchester's differential equations of warfare, and continues the application of Lanchester's linear law to the analysis of the World War II battle of Ardennes, as reported in earlier issues of Naval Research Logistics by Bracken and by Fricker. A new variable, shift time, accounting for the timing of the shift between defense and attack is explicitly included in our version of the model, and it helps obtain improved goodness of fit to historical data. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:653–661, 2001     

A risk function for the stochastic modeling of electric capacity expansion

We present a stochastic optimization model for planning capacity expansion under capacity deterioration and demand uncertainty. The paper focuses on the electric sector, although the methodology can be used in other applications. The goals of the model are deciding which energy types must be installed, and when. Another goal is providing an initial generation plan for short periods of the planning horizon that might be adequately modified in real time assuming penalties in the operation cost. Uncertainty is modeled under the assumption that the demand is a random vector. The cost of the risk associated with decisions that may need some tuning in the future is included in the objective function. The proposed scheme to solve the nonlinear stochastic optimization model is Generalized Benders' decomposition. We also exploit the Benders' subproblem structure to solve it efficiently. Computational results for moderate‐size problems are presented along with comparison to a general‐purpose nonlinear optimization package. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:662–683, 2001     

Extending the MAD portfolio optimization model to incorporate downside risk aversion

A mathematical model of portfolio optimization is usually represented as a bicriteria optimization problem where a reasonable tradeoff between expected rate of return and risk is sought. In a classical Markowitz model, the risk is measured by a variance, thus resulting in a quadratic programming model. As an alternative, the MAD model was developed by Konno and Yamazaki, where risk is measured by (mean) absolute deviation instead of a variance. The MAD model is computationally attractive, since it is easily transformed into a linear programming problem. An extension to the MAD model proposed in this paper allows us to measure risk using downside deviations, with the ability to penalize larger downside deviations. Hence, it provides for better modeling of risk averse preferences. The resulting m‐MAD model generates efficient solutions with respect to second degree stochastic dominance, while at the same time preserving the simplicity and linearity of the original MAD model. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 185–200, 2001     

C++ Builder面向对象编程在多路串行通信中的应用

以模拟导航信号源软件开发为例 ,从面向对象分析设计方法、多线程方法、异常处理等几方面介绍了C ++Builder面向对象编程在多通道实时串行通信系统中应用的一种方法     

基于Matlab的线性拟合计算

对于弹道导弹,由于其运动受多种因素的影响,因此描述其运动的微分方程是极其复杂的,而且,方程中的部分参数是通过对试验数据的科学处理获得的.为了建立数学模型,有时用数据拟合的方法对试验数据进行处理.运用单变量、多变量的线性拟和方法,给出了"单输入/单输出"、"多输入/单输出"的线性拟合模型,并针对拟合模型中未知参数的确定问题,给出了基于最小二乘的线性矛盾方程组的求解方法.通过仿真计算,能够得到较高精度的计算结果.最后,给出了Matlab的实现方法,并给出了一段具体的实现程序.     

三点等间隔线列阵目标定位存在唯一解的充要条件

简要介绍了三点等间隔线列阵目标定位的原理,证明了目标定位存在唯一解的充要条件是:τ12≠τ23,并给出了它的等价条件,为战斗使用线列阵提供科学选择.同时,指出了时延的距离表达式在不同文献中形式不一致的原因;给出了m个水听器时,由时延进行目标定向的公式.