A line search filter secant method for nonlinear equality constrained optimization

<正> This paper formulates and analyzes a line search method for general nonlinear equalityconstrained optimization based on filter methods for step acceptance and secant methods for searchdirection.The feature of the new algorithm is that the secant algorithm is used to produce a searchdirection,a backtracking line search procedure is used to generate step size,some filtered rules areused to determine step acceptance,second order correction technique is used to reduce infeasibility andovercome the Maratos effect.Global convergence properties of this method are analyzed:under mildassumptions it is showed that every limit point of the sequence of iterates generated by the algorithmis feasible,and that there exists at least one limit point that is a stationary point for the problem.Moreover,it is also established that the Maratos effect can be overcome in our new approach by addingsecond order correction steps so that fast local superlinear convergence to a second order sufficient localsolution is achieved.Finally,the results of numerical experiments are reported to show the effectivenessof the line search filter secant method.     

一种基于随机进程代数的软件性能预测方法

性能是软件系统的内在属性之一,主要取决于体系结构选择和软件设计.基于模型的性能预测方法可以在软件开发完毕前得到性能需求满足情况的评价,也可帮助系统进行性能规划和调优.使用随机进程代数PEPA对J2EE应用交互过程进行了建模,该模型描绘了远程调用过程和容器处理过程的细节,能有效反映分布式应用中影响性能的主要因素.基于PEPA模型提出了一种面向COTS系统的性能预测方法,并可用于指导改进系统的响应性和可伸缩性.通过一个J2EE实例验证了方法的有效性.     

中国大额实时支付系统参与者的流动性管理

文章度量了中国主要商业银行在RTGS系统中流动性管理水平,通过与发达国家商业银行的流动性管理状况比较,发现我国商业银行在流动性管理方面存在很大差距,并深入分析了造成这种状况的主要原因.文章进一步讨论了提高流动性管理水平的方法,建立了单个商业银行流动性管理的理论模型,最后给出了流动性管理的最优水平.     

Volterra series based predistortion for broadband RF power amplifiers with memory effects

RF power amplifiers(PAs)are usually considered as memoryless devices in most existing predistortion techniques.However,in broadband communication systems,such as WCDMA,the PA memory effects are significant,and memoryless predistortion cannot linearize the PAs effectively.After analyzing the PA memory effects,a novel predistortion method based on the simplified Volterra series is proposed to linearize broadband RF PAs with memory effects.The indirect learning architecture is adopted to design the predistortion scheme and the recursive least squares algorithm with forgetting factor is applied to identify the parameters of the predistorter.Simulation results show that the proposed predistortion method can compensate the nonlinear distortion and memory effects of broadband RF PAs effectively.     

Optimal maintenance and replacement of extraction machinery

This paper considers a problem of optimal preventive maintenance and replacement schedule of equipment devoted to extracting resources from known deposits. Typical examples are oil drills, mine shovels, etc. At most one replacement of the existing machinery by a new one is allowed. The problem is formulated as an optimal control problem subject to the state constraint that the remaining deposit at any given time is nonnegative. We show that the optimal preventive maintenance, production rates, and the replacement and salvage times of the existing machinery and the new one, if required, can be obtained by solving sequentially a series of free-end-point optimal control problems. Moreover, an algorithm based on this result is developed and used to solve two illustrative examples.     

An improved branch-and-bound algorithm to minimize the weighted flowtime on identical parallel machines with family setup times

This article investigates identical parallel machines scheduling with family setup times. The objective function being the weighted sum of completion times, the problem is known to be strongly NP-hard. We propose a constructive heuristic algorithm and three complementary lower bounds. Two of these bounds proceed by elimination of setup times or by distributing each of them to jobs of the corresponding family, while the third one is based on a lagrangian relaxation. The bounds and the heuristic are incorporated into a branch-and-bound algorithm. Experimental results obtained outperform those of the methods presented in previous works, in term of size of solved problems.     

Interval Time Series Analysis with an Application to the Sterling-Dollar Exchange Rate

Traditional econometrics has long employed ＂points＂ to measure time series data. In real life situations, however, it suffers the loss of volatility information, since many variables are bounded by intervals in a given period. To address this issue, this paper provides a new methodology for interval time series analysis. The concept of ＂interval stochastic process＂ is formally defined as a counterpart of ＂stochastic process＂ in point-based econometrics. The authors introduce the concepts of interval stationarity, interval statistics （including interval mean, interval variance, etc.） and propose an interval linear model to investigate the dynamic relationships between interval processes. A new interval-based optimization approach for estimation is proposed, and corresponding evaluation criteria are derived. To demonstrate that the new interval method provides valid results, an empirical example on the sterling-dollar exchange rate is presented.     

PDE-Based Medial Axis Extraction and Shape Manipulation of Arbitrary Meshes

Shape skeletonization （i.e., medial axis extraction） is powerful in many visual computing applications, such as pattern recognition, object segmentation, registration, and animation. In this paper, the authors expand the use of diffusion equations combined with distance field information to approximate medial axes of arbitrary 3D differential properties. It offers an alternative solids represented by polygonal meshes based on their but natural way for medial axis extraction for commonly used 3D polygonal models. By solving the PDE along time axis, this system can not only quickly extract diffusion-based medial axes of input meshes, but also allow users to visualize the extraction process at each time step. In addition, the proposed model provides users a set of manipulation toolkits to sculpt extracted medial axes, then use diffusion-based techniques to recover corresponding deformed shapes according to the original input datasets. This skeleton-based shape manipulation offers a fast and easy way for animation and deformation of complicated mesh objects.     

Designing a Hybrid Intelligent Mining System for Credit Risk Evaluation

In this study, a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis. In the proposed hybrid intelligent system, support vector machines are used as a tool to extract typical features and filter its noise, which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines. Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets. Therefore, the proposed hybrid intelligent system overcomes the difficulty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches. In addition, the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.     

Systemic Intervention in a University Department: Reflections on Arrested Action Research

This paper reflects on my experience as an insider researcher attempting to use critical systems ideas and practices to promote quality improvement in a university engineering department. Reflection is a key part of learning. This paper is intended to contribute to critically, self-reflective learning for the community of systems practitioners. These reflections on my questions about participation, ethics, politics of process, and the choices and actions resulting from them may help others to formulate their own. The complexity of systems practice places substantial demands on the researcher, particularly in the case of insider, practitioner research. Nevertheless, the exploration of critical systems approaches to critique boundaries and structure ‘problems’ in the core aspects of higher education in locally meaningful ways should continue. While demanding, it still can work to promote learning about authentic quality.