Turbo C与Microsoft FORTRAN混合编程的实现

本文通过研究Borland公司的Turbo C与Microsoft公司的FORTRAN混合编程时出现的问题,提出了修改初始化模块及函数库的原理与方法,并利用TLINK的动态连接功能,实现了这两种语言在源程序级的混合编程,最后说明了实现过程与注意事项。     

变量有界线性目标规划的对偶算法

本文讨论了变量有界的线性目标规划问题,给出了求解这类问题的一个对偶算法,此方法与变量有界线性规划问题的对偶算法相类似。文中证明了算法的有效性,并举例说明了计算过程。     

并行程序设计语言在串行机上的编译实现

目前,诸如Fortran 8x 程序设计语言中已经引入了并行运算成份。这给普通串行(标量)机上实现编译器带来了困难。本文提出了数组(矩阵)运算串行化的概念,并给出了串行化的判别准则及算法。     

单片微型计算机的最新开发技术

本文以 MCS-51系列单片微型机为例,讨论了当前单片机最新编程技术 MBASIC 语言编程和在 IBM-PC 机及兼容机中直接进行模拟/调试,文中给出相应的例子。     

1553B 总线仿真系统总线控制软件设计

就仿真系统对１５５３Ｂ单层总线系统和层次总线系统的总线控制软件设计进行了研究,给出了提高系统效率的方案和优化１５５３Ｂ总线数据流的方法。     

C~3Ⅰ战术模拟技术研究与实现

针对Ｃ￣３Ｉ系统战术模拟实用需求,文章重点对战术想定方案提出、软件系统应用软件模块编程设计,以及有关关键技术应用等进行了研究。该文可对Ｃ￣３Ｉ软件系统技术设计提供参考。     

卫星任务调度问题的约束规划模型

卫星任务规划与调度是空间资源管理的重要内容之一,其目的在于为卫星系统的任务计划编制提供科学合理的决策手段与依据。卫星任务调度问题的重要特点在于,调度任务存在可见时间窗口约束。只有在可见时间窗口内,调度任务才可能执行并完成。在进行合理假设的基础上,建立卫星任务调度问题的约束规划模型。对基本禁忌搜索算法进行改进,提出了模型求解的变邻域禁忌搜索算法。应用结果表明,约束规划模型的建立与求解是合理的。     

Integrating decisions with advance supply information in an assemble-to-order system

We study a periodic-review assemble-to-order (ATO) system with multiple components and multiple products, in which the inventory replenishment for each component follows an independent base-stock policy and stochastic product demands are satisfied according to a First-Come-First-Served rule. We assume that the replenishment for various component suffers from lead time uncertainty. However, the decision maker has the so-called advance supply information (ASI) associated with the lead times and thus can take advantage of the information for system optimization. We propose a multistage stochastic integer program that incorporates ASI to address the joint optimization of inventory replenishment and component allocation. The optimal base-stock policy for the inventory replenishment is determined using the sample average approximation algorithm. Also, we provide a modified order-based component allocation (MOBCA) heuristic for the component allocation. We additionally consider a special case of the variable lead times where the resulting two-stage stochastic programming model can be characterized as a single-scenario case of the proposed multistage model. We carry out extensive computational studies to quantify the benefits of integrating ASI into joint optimization and to explore the possibility of employing the two-stage model as a relatively efficient approximation scheme for the multistage model.     

On efficient algorithms for finding efficient salvo policies

We consider the salvo policy problem, in which there are k moments, called salvos, at which we can fire multiple missiles simultaneously at an incoming object. Each salvo is characterized by a probability p_i: the hit probability of a single missile. After each salvo, we can assess whether the incoming object is still active. If it is, we fire the missiles assigned to the next salvo. In the salvo policy problem, the goal is to assign at most n missiles to salvos in order to minimize the expected number of missiles used. We consider three problem versions. In Gould's version, we have to assign all n missiles to salvos. In the Big Bomb version, a cost of B is incurred when all salvo's are unsuccessful. Finally, we consider the Quota version in which the kill probability should exceed some quota Q. We discuss the computational complexity and the approximability of these problem versions. In particular, we show that Gould's version and the Big Bomb version admit pseudopolynomial time exact algorithms and fully polynomial time approximation schemes. We also present an iterative approximation algorithm for the Quota version, and show that a related problem is NP-complete.     

Application of Markov renewal theory and semi-Markov decision processes in maintenance modeling and optimization of multi-unit systems

In this paper, a condition-based maintenance model for a multi-unit production system is proposed and analyzed using Markov renewal theory. The units of the system are subject to gradual deterioration, and the gradual deterioration process of each unit is described by a three-state continuous time homogeneous Markov chain with two working states and a failure state. The production rate of the system is influenced by the deterioration process and the demand is constant. The states of the units are observable through regular inspections and the decision to perform maintenance depends on the number of units in each state. The objective is to obtain the steady-state characteristics and the formula for the long-run average cost for the controlled system. The optimal policy is obtained using a dynamic programming algorithm. The result is validated using a semi-Markov decision process formulation and the policy iteration algorithm. Moreover, an analytical expression is obtained for the calculation of the mean time to initiate maintenance using the first passage time theory.