An analytical evaluation of optimal solution value estimation procedures

The estimation of optimal solution values for large-scale optimization problems is studied. Optimal solution value estimators provide information about the deviation between the optimal solution and the heuristic solution. Some estimation techniques combine heuristic solutions with randomly generated solutions. In particular, we examine a class of jacknife-based estimators which incorporate any heuristic solution value with the two best randomly generated solution values. The primary contribution of this article is that we provide a framework to analytically evaluate a class of optimal solution value estimators. We present closed-form results on the relationship of heuristic performance, sample size, and the estimation errors for the case where the feasible solutions are uniformly distributed. In addition, we show how to compute the estimation errors for distributions other than uniform given a specific sample size. We use a triangular and an exponential distribution as examples of other distributions. A second major contribution of this article is that, to a large extent, our analytical results confirm previous computational results. In particular, the best estimator depends on how good the heuristic is, but seems to be independent of the underlying distribution of solution values. Furthermore, there is essentially an inverse relationship between the heuristic performance and the performance of any estimator. © 1994 John Wiley & Sons, Inc.     

The frequency assignment problem: A solution via nonlinear programming

This paper gives a mathematical programming model for the problem of assigning frequencies to nodes in a communications network. The objective is to select a frequency assignment which minimizes both cochannel and adjacent-channel interference. In addition, a design engineer has the option to designate key links in which the avoidance of jamming due to self interference is given a higher priority. The model has a nonconvex quadratic objective function, generalized upper-bounding constraints, and binary decision variables. We developed a special heuristic algorithm and software for this model and tested it on five test problems which were modifications of a real-world problem. Even though most of the test problems had over 600 binary variables, we were able to obtain a near optimum in less than 12 seconds of CPU time on a CDC Cyber-875.     

A new surrogate dual multiplier search procedure

Efficient computation of tight bounds is of primary concern in any branch-and-bound procedure for solving integer programming problems. Many successful branch-and-bound approaches use the linear programming relaxation for bounding purposes. Significant interest has been reported in Lagrangian and surrogate duals as alternative sources of bounds. The existence of efficient techniques such as subgradient search for solving Lagrangian duals has led to some very successful applications of Lagrangian duality in solving specially structured problems. While surrogate duals have been theoretically shown to provide stronger bounds, the difficulty of surrogate dual-multiplier search has discouraged their employment in solving integer programs. Based on the development of a new relationship between surrogate and Lagrangian duality, we suggest a new strategy for computing surrogate dual values. The proposed approach allows us to directly use established Lagrangian search methods for exploring surrogate dual multipliers. Computational experience with randomly generated capital budgeting problems validates the economic feasibility of the proposed ideas.     

Optimal Bayesian single-sampling attribute plans with modified beta prior distribution

In this article we study the properties of the optimal Bayesian single-sampling plans when the prior distribution of the lot fraction defective is modified Beta, which has been found useful in the analysis of inspection schemes for complex production systems. These properties are used to devise an improved and more efficient algorithm for the determination of the optimal sampling plans. Numerical examples are presented to illustrate the potential computational savings of the algorithm.     

基于核主成分分析的铁谱磨粒特征提取方法研究

针对铁谱分析的磨粒识别过程中存在原始磨粒特征描述指标参数多、非线性突出的问题,提出基于核主成分分析的磨粒特征提取方法,介绍该方法的原理与算法。结合某柴油发动机故障检测与分析系统中铁谱磨粒自动识别的应用实例,并与传统主成份分析方法进行对比分析,结果表明该方法在进行样本非线性特征参数指标综合以及特征维数压缩方面具有可行性和有效性。     

Challenging the Hegemon: Al Qaeda's Elevation of Asymmetric Insurgent Warfare Onto the Global Arena

This chapter examines how Al Qaeda, an asymmetric power, was able to become a global challenger to the existing international structure. Neither regional insurgency theories nor grand-scale global theories alone are adequate to explain Al Qaeda's ability. Rather, a modification of the seven dimensions of the Manwaring paradigm for successful insurgency combined with key concepts of global revolutionary or imperial powers formerly applied to states gives insight to this fundamental question. Al Qaeda's asymmetric global challenge is unique, and understanding the nature of the threat is key to finally defeating it.     

体外天线气动加热下三维瞬态温度场建模与仿真

利用工程上常用的突起物干扰系数法,建立了体外天线气动加热工程计算方法,结合成熟的商业软件,采用二次开发技术,建立了突起物三维瞬态温度场计算模型.讨论了飞行条件下外露天线2种不同形式对天线接插件温度的影响,计算结果表明:为保证天线正常工作的温度环境,避免高热流的冲击,在天线设计时需考虑防热措施.     

基于UML的作战系统描述方法

在仿真的具体实现过程中,系统描述是其中的关键步骤.分析了利用统一建模语言UML对系统进行描述的方法和步骤,并以炮兵群(团)作战系统为例,给出了UML中的用例图、类图、活动图以及协作图对系统进行描述的方法.结果表明利用UML进行系统描述,描述过程完整,易于理解和操作.     

C~4ISR系统军事需求模型并行开发与一致性检验

介绍了C4ISR系统军事需求模型的概念、特点及其开发的并行性,并根据我军联合作战指挥信息系统的需求开发实践需要,针对C4ISR系统军事需求模型的模块划分以及分组建模过程进行分析,在此基础上给出了一个C4ISR系统军事需求模型并行开发过程的参考模型,并探讨了并行开发过程在系统需求周期内的一致性检验问题,包括了需求模型的语法、语义和语用一致性检验的过程和方法.     

基于倾斜平台的舰炮武器系统零位修正方法

分析了舰炮基座平台倾斜误差较大时对系统零位一致性和精度造成的影响,提出了采用单炮基座倾斜修正和对系统瞄星数据补偿的改进修正方法进行系统零位一致性的精确调整,并给出修正公式的推导过程.以试验实测数据对修正精度进行了验证,结果表明该方法具有较好的实用价值.该方法已在某型舰炮武器系统的海试中得到了成功应用.