支持社会技术系统构造的程序设计模型和语言

互联网上越来越多软件系统呈现出社会与技术交融、环境多样和开放、系统动态和演化等特点,如何支持这类复杂软件系统的构造是软件工程面临的一项重要挑战。通过将社会技术系统视为多Agent组织,把社会组织学的概念和思想引入到面向Agent程序设计范畴,提出了以Agent、组织、角色和职位为核心的基于组织程序模型来支持社会技术系统的开发;通过对多Agent组织不同层次动态性的识别和分析,设计了一组程序设计机制来实现社会技术系统的动态演化;包括角色绑定和组合机制、基于角色的交互机制以及组织的自我管理机制。基于上述模型和机制,提出了社会技术系统程序设计语言OragentL,给出了OragentL程序在组织、角色和组合三个层次的语法形式定义,介绍了OragentL的编译器及其运行支撑环境OragentBurg,并通过案例分析和演示展示了研究成果的有效性。     

军用飞机燃油消耗多元线性回归模型

为了解决军用飞机非标准动作燃油消耗建模问题,利用实际飞参数据,采用多元线性回归方法进行建模分析。建立了燃油消耗量与飞行时间、油箱平均油量、平均高度、平均速度、T1温度、T4温度、N2转速、高度变化量、飞机外挂的多元线性回归模型,并对回归模型进行统计性检验和验证。结论显示:模型拟合度较好,符合军用飞机飞行耗油规律,对军用飞机非标准动作燃油消耗规律研究具有重要意义。     

Dynamic inventory control with limited capital and short‐term financing

For most firms, especially the small‐ and medium‐sized ones, the operational decisions are affected by their internal capital and ability to obtain external capital. However, the majority of the literature on dynamic inventory control ignores the firm's financial status and financing issues. An important question that arises is: what are the optimal inventory and financing policies for firms with limited internal capital and limited access to external capital? In this article, we study a dynamic inventory control problem where a capital‐constrained firm periodically purchases a product from a supplier and sells it to a market with random demands. In each period, the firm can use its own capital and/or borrow a short‐term loan to purchase the product, with the interest rate being nondecreasing in the loan size. The objective is to maximize the firm's expected terminal wealth at the end of the planning horizon. We show that the optimal inventory policy in each period is an equity‐level‐dependent base‐stock policy, where the equity level is the sum of the firm's capital level and the value of its on‐hand inventory evaluated at the purchasing cost; and the structure of the optimal policy can be characterized by four intervals of the equity level. Our results shed light on the dynamic inventory control for firms with limited capital and short‐term financing capabilities.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 184–201, 2014     

Sequential learning versus no learning in Bayesian regression models

We consider two regression models: linear and logistic. The dependent variable is observed periodically and in each period a Bayesian formulation is used to generate updated forecasts of the dependent variable as new data is observed. One would expect that including new data in the Bayesian updates results in improved forecasts over not including the new data. Our findings indicate that this is not always true. We show there exists a subset of the independent variable space that we call the “region of no learning.” If the independent variable values for a given period in the future are in this region, then the forecast does not change with any new data. Moreover, if the independent variable values are in a neighborhood of the region of no learning, then there may be little benefit to wait for the new data and update the forecast. We propose a statistical approach to characterize this neighborhood which we call the “region of little learning.” Our results provide insights into the trade‐offs that exist in situations when the decision maker has an incentive to make an early decision based on an early forecast versus waiting to make a later decision based on an updated forecast. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 532–548, 2014     

基于渐进性的线性方程组教学设计的研究

针对线性方程组传统教学中的一些问题,给出了引入线性方程组、解线性方程组、分析解结构的渐进性三步教学设计,同时给出了maple求解线性方程组的两种方法,将理论与实践初步结合了起来,丰富了教学手段,激发了学生的学习兴趣。     

非均匀线阵天线阵因子综合方法的研究

非均匀线阵的阵因子综合与均匀线阵有很大不同,使得天线阵因子的综合无法利用经典的方法进行,副瓣电平降低困难。提出了一种针对线阵阵元空缺情况下的阵因子综合方法。从理论推导到Matlab仿真,对非均匀线阵天线阵因子综合方法进行了研究,得到一种适用于非均匀线阵天线阵因子的综合方法。     

目标规划的求解

目标规划的求解可采用图示法、单纯形法、分级法等,文中用Excel演示单纯形法和分级法。     

新型装备维修任务分配与保障资源规划分析方法研究

新型装备列装部队,对部队维修保障能力建设提出了更高更新的要求。为加速新型装备战斗力形成,急需一套科学、合理的方法用以确定装备维修任务和规划维修保障资源配置。针对这一问题,本文紧密结合我军实际,构建了新型装备维修任务分配与保障资源规划分析方法体系,规范了新型装备维修分析流程,并对分析过程中的关键技术进行了研究,最后开发了计算机辅助决策分析系统。     

线性规划问题新解——改进大M法

借鉴两阶段法的求解思路,在用单纯形法求解线性规划问题时,对大M法进行改进,提出一种新的算法.这种改进后的算法可以有效克服原来两种算法的不足,既能降低理解难度,又能提高算法的效率,保证算法的全局收敛性.     

军队人力资源培训问题的整数线性规划模型

文章研究了军队人力资源培训问题,并基于时间和费用两个指标,建立了一个满足培训时间约束且费用最省的0-1整数线性规划模型,给出了基于Lagrange松驰分解的模型求解算法。在算法中,采用一种简单可行的Lagrange乘子更新方法代替传统的次梯度法。另外,文章证明了算法获得最优解的两个充分条件,计算实例初步表明给出的算法是行之有效的。