Several multi-criteria programming methods for classification

In this paper, we propose a general optimization-based model for classification. Then we show that some well-known optimization-based methods for classification, which were developed by Shi et al. [Data mining in credit card portfolio management: a multiple criteria decision making approac. In: Koksalan M, Zionts S, editors. Multiple criteria decision making in the new millennium. Berlin: Springer; 2001. p. 427–36] and Freed and Glover [A linear programming approach to the discriminant problem. Decision Sciences 1981; 12: 68–79; Simple but powerful goal programming models for discriminant problems. European Journal of Operational Research 1981; 7: 44–60], are special cases of our model. Moreover, three new models, MCQP (multi-criteria indefinite quadratic programming), MCCQP (multi-criteria concave quadratic programming) and MCVQP (multi-criteria convex programming), are developed based on the general model. We also propose algorithms for MCQP and MCCQP, respectively. Then we apply these models to three real-life problems: credit card accounts, VIP mail-box and social endowment insurance classification. Extensive experiments are done to compare the efficiency of these methods.     

使用Qt/C++编程操作Microsoft Office软件的应用

Microsoft office系列软件在日常工作中应用广泛。我单位在工程项目中大量使用Office软件进行数据处理及交换,对这些原始数据采取适当的方法分析挖掘,可以极大地缩短设计与试验周期、降低成本。由于项目产生的临时数据常以不同格式存放在各种办公软件中,且数量巨大,所以需要一个可以控制Office系列办公软件的程序来完成原始信息的收集及输出。给出了通过使用基于C++的Qt框架并结合COM、ODBC技术获取、处理数据,并输出至数据库或XML文档的实现方法。     

Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains

In the real-world manufacturing/distribution planning decision (MDPD) integration problems in supply chains, the environmental coefficients and parameters are normally imprecise due to incomplete and/or unavailable information. This work presents a fuzzy linear programming approach based on the possibility theory. It applies this approach to solve multi-product and multi-time period MDPD problems with imprecise goals and forecast demand by considering the time value of money of related operating cost categories. The proposed approach attempts to minimize the total manufacturing and distribution costs by considering the levels of inventory, subcontracting and backordering, the available machine capacity and labor levels at each source, forecast demand and available warehouse space at each destination. This study utilizes an industrial case study to demonstrate the feasibility of applying the proposed approach to practical MDPD problems. The primary contribution of this paper is a fuzzy mathematical programming methodology for solving the MDPD integration problems in uncertain environments.     

传感器输出特性的线性化回归程序设计

介绍了用面向对象程序设计方法编制的线性回归数据处理程序 ,该程序用于传感器实验数据的回归处理和特性曲线的绘制     

Guaranteed Dynamic-System State Estimation by the Method of Bidirectional Dynamic Programming

The problem of guaranteed estimation (smoothing, filtration, prediction) of a dynamic process observed on a finite discrete time interval is solved, based on generalization of the dynamic programming procedure for the case with sequential optmization in direct and inverse time.     

Evolving Teams of Predictors with Linear Genetic Programming

This paper applies the evolution of GP teams to different classification and regression problems and compares different methods for combining the outputs of the team programs. These include hybrid approaches where (1) a neural network is used to optimize the weights of programs in a team for a common decision and (2) a realnumbered vector (the representation of evolution strategies) of weights is evolved with each term in parallel. The cooperative team approach results in an improved training and generalization performance compared to the standard GP method. The higher computational overhead of team evolution is counteracted by using a fast variant of linear GP.     

Solving multiple objective quasi-convex goal programming problems by linear programming

This study presents a novel means of resolving multiple objective goal programming (GP) problems with quasi-convex linear penalty functions. The proposed method initially expresses a quasi-convex function by the maximum operator of two convex functions, then solves it via a linear programming technique. The proposed method does not contain any zero–one variables; nor does it require dividing the multi-objective quasi-convex GP problem into large sub-problems as in conventional methods. Some illustrative examples are provided.     

ArcVieW应用开发中动态连接库方法研究

Ａｖｅｎｕｅ是地理信息系统软件平台ＡｒｅＶｉｅｗ的二次开发工具,该文重点介绍了在Ａｖｅｎｕｅ开发蝇使用动态连接库的实现方法。     

Robot Motion Planning: A Game-Theoretic Foundation

Analysis techniques and algorithms for basic path planning have become quite valuable in a variety of applications such as robotics, virtual prototyping, computer graphics, and computational biology. Yet, basic path planning represents a very restricted version of general motion planning problems often encountered in robotics. Many problems can involve complications such as sensing and model uncertainties, nonholonomy, dynamics, multiple robots and goals, optimality criteria, unpredictability, and nonstationarity, in addition to standard geometric workspace constraints. This paper proposes a unified, game-theoretic mathematical foundation upon which analysis and algorithms can be developed for this broader class of problems, and is inspired by the similar benefits that were obtained by using unified configuration-space concepts for basic path planning. By taking this approach, a general algorithm has been obtained for computing approximate optimal solutions to a broad class of motion planning problems, including those involving uncertainty in sensing and control, environment uncertainties, and the coordination of multiple robots. Received November 11, 1996; revised March 13, 1998.     

案例教学法在网络程序设计ASP课程中的应用

分析研究了网络程序设计ASP课程教学的特点,结合留言板系统的具体教学实践,讨论了如何有效地把案例教学法运用于网络程序设计教学中的方法、步骤。实践证明,案例教学法有利于培养学生分析问题和解决问题的实践能力。