基于熵值法的坦克动力舱热工况的综合评价

坦克动力舱的结构和布置有多种型式,为了对不同结构的动力舱热工况的优劣进行对比、评价,必须用量化的指标加以衡量.提出了一种坦克动力舱热工况的评价指标体系,运用熵值法原理科学地确定各评价指标权重,建立了综合评价模型,并对某型主战坦克动力舱的不同布置方案进行了热工况综合评价.     

对流层散射无源监视系统最优布局方法

为提高对流层散射无源监视系统对辐射源的定位精度,利用改进粒子群优化算法对分布式监视节点进行最优布局设计。推导了基于电磁波方位到达角定位机制下的几何精度因子。在改进粒子群优化算法中,采用混沌理论初始化所有粒子的初始参数;通过自适应变化的惯性权重和学习因子来提高算法寻优能力;为防止粒子陷入局部最优,利用双子群机制进行寻优,并在两子群之间进行交叉变异操作,以增加粒子的多样性。仿真结果表明:相对于几种常规的布站方式,所提算法能够明显提高监视系统对辐射源的定位精度,运行时间较遍历寻优算法有所减少。     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.     

动态威胁环境下单无人机测向定位航迹优化算法

为解决单架无人机在动态战场环境下的测向定位问题,提出了一种基于动态窗口法的单机测向定位航迹优化算法。以最大化Fisher信息矩阵行列式为测向定位评价准则,在由动态探测雷达和静/动障碍构成的动态战场环境中,基于动态窗口法思想,将测向定位航迹优化评价准则由传统的单步最优原则扩展到对多步预测航迹的评价,同时考虑雷达探测和静/动障碍环境对预测航迹的影响,通过滚动时域方法控制无人机最优航向。仿真结果表明,所提方法能够使无人机在有效逃避雷达探测威胁以及规避环境中静/动障碍的条件下保证对目标的高精度测向定位,为解决动态战场环境下的单架无人机测向定位问题提供了新思路。     

九年一贯制学校综合实践活动课程实施现状分析及价值挖掘

综合实践活动课程作为现代教育的重要内容,是国家新一轮课改的亮点和难点。调研发现,九年一贯制学校开设综合实践活动课程推动了学校重构教育教学层级与体系,能有效提升学生核心素养,促进教师职业成长与转型,帮助学校竖立校本特色与教育品牌影响力。九年一贯制学校开设综合实践活动是人才强国背景下的学生需求与文化适应的统一,是教师的使命和责任的体现,是传统教育与新型教育的融合与创新。     

军队会计流程存在的问题及优化策略

在新军事变革的背景下,军队会计流程存在不适应新管理体制需要、信息技术应用对会计流程再造力度不够、军队会计科目设置影响流程等问题。本文从界定军队会计流程的含义入手,提出了优化军队会计流程、建立智能化军队会计信息系统的四项策略,即重塑军队会计流程体系、重构军队会计信息系统、调整军队会计科目体系以及完善各流程会计处理方法。优化军队会计流程、建设智能化军队会计信息系统,不仅能够反映军事经济活动的历史信息,还能为不同类型的信息使用者提供预测、决策等支持,并有利于改善军队会计核算质量,准确反映各类资产负债的价值信息和单位的真实财务状况,对于提高军队会计信息质量具有一定的借鉴意义。     

Optimization of buckling load for laminated composite plates using adaptive Kriging-improved PSO: A novel hybrid intelligent method

An effective hybrid optimization method is proposed by integrating an adaptive Kriging (A-Kriging) into an improved partial swarm optimization algorithm (IPSO) to give a so-called A-Kriging-IPSO for maxi-mizing the buckling load of laminated composite plates (LCPs) under uniaxial and biaxial compressions. In this method, a novel iterative adaptive Kriging model, which is structured using two training sample sets as active and adaptive points, is utilized to directly predict the buckling load of the LCPs and to improve the efficiency of the optimization process. The active points are selected from the initial data set while the adaptive points are generated using the radial random-based convex samples. The cell-based smoothed discrete shear gap method (CS-DSG3) is employed to analyze the buckling behavior of the LCPs to provide the response of adaptive and input data sets. The buckling load of the LCPs is maximized by utilizing the IPSO algorithm. To demonstrate the efficiency and accuracy of the proposed methodology, the LCPs with different layers (2, 3, 4, and 10 layers), boundary conditions, aspect ratios and load patterns (biaxial and uniaxial loads) are investigated. The results obtained by proposed method are in good agreement with the literature results, but with less computational burden. By applying adaptive radial Kriging model, the accurate optimal results-based predictions of the buckling load are obtained for the studied LCPs.     

Discrete stochastic optimization using variants of the stochastic ruler method

We present two random search methods for solving discrete stochastic optimization problems. Both of these methods are variants of the stochastic ruler algorithm. They differ from our earlier modification of the stochastic ruler algorithm in that they use different approaches for estimating the optimal solution. Our new methods are guaranteed to converge almost surely to the set of global optimal solutions under mild conditions. We discuss under what conditions these new methods are expected to converge faster than the modified stochastic ruler algorithm. We also discuss how these methods can be used for solving discrete optimization problems when the values of the objective function are estimated using either transient or steady‐state simulation. Finally, we present numerical results that compare the performance of our new methods with that of the modified stochastic ruler algorithm when applied to solve buffer allocation problems. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

汽油调合优化模型

为了提高炼油厂制订成品油调合方案的科学性,研究了汽油调合优化的非线性规划模型,给出了目标函数和约束条件的具体形式。根据模型特征,选用模拟退火算法对模型求解。最后,通过某炼油厂的一个应用实例验证了上述成品油调合优化模型的有效性。     

一种关于~pc(0≤c<1)的快精算法

求pc(p>1,正整数)的值时,若c较小,通常会存在收敛速度较慢以及数值字长有限所致精度变差的问题。提出了一种关于pc(0≤c<1)的快精算法,该方法按照定点二进制数特点,通过适当扩大c值,利用牛顿迭代法求取近似值,在采用选值法确定初值时,将对应值域分为若干等间隔子区间,初值精度取决于间隔h的大小,而h的大小则根据迭代精度和预定迭代次数确定,由此可获得高精度初值,从而在理论上使pc的迭代计算达到快速、高精度的目的。