培养兴趣,引导创新——《信息光学》理论教学改革实践

重点研究了针对《信息光学》理论性强的课程和学生在学习过程中兴趣下降以及一知半解等问题,着重从提高学生理论学习兴趣,引导学生创新为出发点,通过改进PPT课件,吸引学生注意,采用深入浅出、举一反三、师生互动、启发式教学方法、理论与实际相结合、教学科研相结合等多种方法和手段,帮助学生建立正确的物理概念,促进学生对数学公式所代表的物理意义的理解,达到改善理论教学效果的目的。同时结合创新性实验建设,培养创新型和复合型人才。     

多值测试诊断策略优化设计

针对电子系统中多值测试条件下的测试排序问题,提出了一种诊断策略优化方法。首先,以相关性矩阵模型为基础,将已有的二值测试的优化算法同多值测试问题相结合,提出了适用于多值测试的基于霍夫曼编码的启发式函数;其次,将平均测试代价最小和平均测试步骤最少作为优化目标,采用与或树启发式搜索算法生成诊断树,得到多值测试的诊断策略,并给出了诊断策略优化方法的具体实现步骤;最后,将其应用到航空设备的实例中。结果表明提出的基于霍夫曼编码的与或树启发式搜索算法是可行的,其生成的诊断树是最优的,比基于信息熵的与或树启发式搜索算法具有更小的平均测试代价和更少的平均测试步骤。     

“学习提示”模块在新版有机化学教材中的应用

一本好的有机化学教材应该对教师教学和学生自学有很好的辅助和引导作用。如何使学生从浩如烟海的内容中发现重点、难点,并做到有效掌握和融会贯通,是教材编写者需要重点考虑的问题。笔者将教学经验融入到有机化学教材改革实践,在新版教材中加入了原创的“学习提示”板块,用简练、更通俗易懂的语言对一些重要、较难理解的或是容易混淆的知识点进行辅助讲解、串联总结。笔者认为该板块可以起到协助学生理解知识难点、厘清易混淆概念、将关联知识融会贯通以及激发学生科研兴趣等作用。本文用一些实例对这一模块的编写构思、内容和预期成效进行了介绍。     

“仓店一体化”模式下订单拣选与配送集成调度优化

针对“仓店一体化”模式下提供限时送达服务的新零售仓店,研究多拣货员、多客户、配送方式为带限时送达约束的路径优化分批配送情形下的订单拣选与配送集成调度问题。以最小化订单最大履行时间和配送成本为目标,构建了混合整数非线性规划模型,并设计两阶段启发式算法(H-2)进行求解,最后通过数值实验对算法进行验证与分析。数值实验结果表明,H-2具有较高的求解质量;相较于传统调度算法(TS)在效率提升、资源节约以及客户满意度提高方面具有更优的表现,进而为新零售仓店管理者提供决策支持。     

Centered -discrepancy of random sampling and Latin hypercube design, and construction of uniform designs

In this paper properties and construction of designs under a centered version of the -discrepancy are analyzed. The theoretic expectation and variance of this discrepancy are derived for random designs and Latin hypercube designs. The expectation and variance of Latin hypercube designs are significantly lower than that of random designs. While in dimension one the unique uniform design is also a set of equidistant points, low-discrepancy designs in higher dimension have to be generated by explicit optimization. Optimization is performed using the threshold accepting heuristic which produces low discrepancy designs compared to theoretic expectation and variance.

     

Completeness and Admissibility for General Heuristic Search Algorithms—A Theoretical Study: Basic Concepts and Proofs

We propose a formal generalization for various works dealing with Heuristic Search in State Graphs. This generalization focuses on the properties of the evaluation functions, on the characteristics of the state graphs, on the notion of path length, on the procedures that control the node expansions, on the rules that govern the update operations. Consequently, we present the algorithm family and the sub-family Ã, which include Nilsson's A or A_* and many of their successors such as HPA, B, A ^* , A, C, BF^*, B, IDA^*, D, A^**, SDW. We prove general theorems about the completeness and the sub-admissibility that widely extend the previous results and provide a theoretical support for using diverse kinds of Heuristic Search algorithms in enlarged contexts, specially when the state graphs and the evaluation functions are less constrained than ordinarily.     

The ?-positive center figure

Based on Gage's notion of a “positive center” of a planar convex set, an ε-positive center figure is defined, constructed, and illustrated through example. The existence of an ε-positive center point, and the convexity of the ε-positive center figure, is conjectured.     

Clustering for routing in densely populated areas

This paper introduces a new approach for generating school bus routes in a dense urban area. First, a districting algorithm is used to determine clusters including appropriate numbers of students. Then, for each cluster, a route and the stops along this route are determined. Numerical results are reported and compared with those obtained previously. Although the algorithm has been developped and tested in a specific context, it could easily be extended to more general vehicle routing problems.     

Non-classical preference models in combinatorial problems: Models and algorithms for graphs

This is a summary of the most important results presented in the authors PhD thesis (Spanjaard 2003). This thesis, written in French, was defended on 16 December 2003 and supervised by Patrice Perny. A copy is available from the author upon request. This thesis deals with the search for preferred solutions in combinatorial optimization problems (and more particularly graph problems). It aims at conciliating preference modelling and algorithmic concerns for decision aiding.Received: March 2004, MSC classification: 91B06, 90C27, 90B40, 16Y60     

A MIP approach for some practical packing problems: Balancing constraints and tetris-like items

This paper considers packing problems with balancing conditions and items consisting of clusters of parallelepipeds (mutually orthogonal, i.e. tetris-like items). This issue is quite frequent in space engineering and a real-world application deals with the Automated Transfer Vehicle project (funded by the European Space Agency), at present under development. A Mixed Integer Programming (MIP) approach is proposed. The three-dimensional single bin packing problem is considered. It consists of orthogonally placing, with possibility of rotation, the maximum number of parallelepipeds into a given parallelepiped. A MIP formulation of the problem is reported together with a MIP-based heuristic approach. Balancing conditions are furthermore examined, as well as the orthogonal placement (with rotation) of tetris-like items into a rectangular domain.Received: September 2003, Revised: February 2004, AMS classification: 90B99, 05B40, 90C90, 90C59Thanks are due to T. A. Ciriani for the important suggestions given for the whole paper and to S. Gliozzi (IBM, Business Consulting Services) for the significant support offered, in particular in discussing the topics presented in Sect. 2.1.