一种结构化的编译型 PROLOG数据库及其管理策略

PROLOG数据库存放着构成PROLOG程序的子句以及表示成子句的全局数据,它的组织与管理是实用PROLOG系统的关键,这一点在提高执行效率的编译型PROLOG系统中尤为如此。本文以YH-SIM——一个扩充了的WAM模型为基础,提出一种新颖的编译型PROLOG数据库结构形式,其中·过程中的子句索引与子句彼此分离; ·子句索引块分成多个专门的子索引块; ·一个子句按两种形式存放,子句代码和子句项(源子句形式)。二者分离且共享同一索引,因此代码库和项库的管理是一体化的。这些结构化的特征,有力地支持PROLOG数据库的操作及管理(子句的插入删除,以及空间分配与回收)。文中还介绍了一种简明有效的管理方法。     

向量巨型机高效程序设计技术

本文着重研究适应向量巨型机体系结构的高效程序设计技术。围绕减少指令流水线阻塞,提高多功能部件并行度,数据调度与局部化技术三个方面进行了深入的讨论,给出了一系列设计高效程序的方法和技巧。     

程序进化器

研究用模拟进化方法进行程序设计的途径。构造了以形式文法为遗传表示的程序进化器,提出了这个进化器使用的有关算法。本文用程序进化器解决了人工蚁问题。     

专用字符集译码逻辑的程序优化设计

提出了一种组合逻辑译码电路优化设计的基本原则 ,给出了基于该优化设计原则的程序设计所涉及的关键数据结构和算法 ,并利用现有中小规模译码驱动电路 744 8系列芯片和门电路等实现了工程实践中需要的特殊字符集译码优化设计的参考电路 .     

数字化部队战斗力优化组合模型

数字化部队在战场上的出现,是信息战争产生的重要标志之一.随着信息技术的兴起,一些西方国家组建了数字化部队并加深了对其编成和结构理论的研究.首先介绍了模块理论,通过对数字化部队战斗力原理的分析,讨论了数字化部(分)队战斗力构成要素.在此基础上,使用线性规划理论试探性的构建出数字化部(分)队战斗力模块组合模型,并对模型的不同组合方式进行了论证和分析,得出数字化部(分)队战斗力模块的一种优化组合.最后展望了本课题下一步工作的研究重点.     

助推-滑翔式导弹中段弹道方案的初步分析

建立了助推—滑翔式弹道中段的无量纲运动方程。采用非线性规划方法实现弹道优化。首先求解不同初始速度、速度倾角和最大升阻比的最大射程弹道,然后考虑驻点热流、过载约束,求解总气动加热最小和射程最大的最优弹道。基于前者的计算结果分析了初始条件对最大射程弹道的影响。将考虑约束的再入滑翔弹道与弹道式再入的特征参数比较,表明再入滑翔弹道的峰值热流较小,而总气动加热增加,但再入滑翔飞行时间在一般锥形体再入机动飞行器的热防护系统可承受的时间范围内。     

分布式流体系结构及其编程模型与资源管理

利用互联网资源提供大数据计算服务面临着资源异构性、动态性与通信长延迟等方面的挑战,现有分布式计算模型仍存在一些不足。运用流计算模型提出分布式流体系结构,包括分布式流编程模型与资源管理等,能够高效支持多种并行执行模式。在10个CPU-GPU异构结点上实现了原型系统,仿真实验验证了7个不同的测试用例。实验结果表明,与本地串行计算相比,分布式流体系结构可以平均提高39倍计算性能,具有较大的应用潜力。     

电力市场环境下发电厂机组检修计划

分析了传统的统一调度下和电力市场环境下发电厂机组检修计划的不同,在此基础上提出不同于以往的检修计划方法。以检修费用、电价收益损失和违约金之和最小为目标函数,然后采用0-1整数规划的直接枚举法求解。最后通过算例论证了该方法的可行性。     

Scheduling maintenance and semiresumable jobs on a single machine

The majority of scheduling literature assumes that the machines are available at all times. In this paper, we study single machine scheduling problems where the machine maintenance must be performed within certain intervals and hence the machine is not available during the maintenance periods. We also assume that if a job is not processed to completion before the machine is stopped for maintenance, an additional setup is necessary when the processing is resumed. Our purpose is to schedule the maintenance and jobs to minimize some performance measures. The objective functions that we consider are minimizing the total weighted job completion times and minimizing the maximum lateness. In both cases, maintenance must be performed within a fixed period T, and the time for the maintenance is a decision variable. In this paper, we study two scenarios concerning the planning horizon. First, we show that, when the planning horizon is long in relation to T, the problem with either objective function is NP-complete, and we present pseudopolynomial time dynamic programming algorithms for both objective functions. In the second scenario, the planning horizon is short in relation to T. However, part of the period T may have elapsed before we schedule any jobs in this planning horizon, and the remaining time before the maintenance is shorter than the current planning horizon. Hence we must schedule one maintenance in this planning horizon. We show that the problem of minimizing the total weighted completion times in this scenario is NP-complete, while the shortest processing time (SPT) rule and the earliest due date (EDD) rule are optimal for the total completion time problem and the maximum lateness problem respectively. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 845–863, 1999     

A comparative study of three tool replacement/operation sequencing strategies in a flexible manufacturing system

This paper studies three tool replacement/operation sequencing strategies for a flexible manufacturing system over a finite time horizon: (1) failure replacement—replace the tool only upon failure, (2) optimal preventive tool replacement for a fixed sequence of operations, and (3) joint scheduling of the optimal preventive tool replacement times and the optimal sequence of operations. Stochastic dynamic decision models are used for strategies 2 and 3. The optimization criterion for strategies 2 and 3 is the minimization of the total expected cost over the finite time horizon. We will show through numerical studies that, with the same amount of information, the total expected costs can be reduced considerably by choosing an optimal strategy. Our conclusion is that in flexible manufacturing, optimal tool replacement and optimal operations sequencing are not separate issues. They should be considered jointly to minimize the expected total cost. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 479–499, 2000