Heuristic Rejection in Interval Global Optimization

Based on the investigation carried out in Ref. 1, this paper incorporates new studies about the properties of inclusion functions on subintervals while a branch-and-bound algorithm is solving global optimization problems. It is found that the relative place of the global minimum value within the inclusion function value of the objective function at the current interval indicates mostly whether the given interval is close to a minimizer point. This information is used in a heuristic interval rejection rule that can save a considerable amount of computation. Illustrative examples are discussed and an extended numerical study shows the advantages of the new approach.     

关于组合最优化理论的多媒体教学实践

本文讨论和分析了开发组合最比化理论系列课程多媒体课件的基本认识、课件的主要特色和体会，并提出了使用多媒体课件中应注意的问题．     

一种全局优化的多面体凸分解匹配方法

提出了一种全局优化的多面体匹配方法，该方法对物体的拓扑关系和结构关系进行多级匹配,利用全局优化的松驰迭代方法减少匹配误差，并由匹配的一致性准则进行匹配结果的检测，根据物体的内在特征来进行匹配，从而解决非同构物体的匹配.可广泛应用于物体识别、三维物体重建、医学图象处理等领域，实验证明此方法质量好、自动化程度高，是一种有效的全局优化结构匹配方法．     

Rational Functions with Prescribed Global and Local Minimizers

A family of multivariate rational functions is constructed. It has strong local minimizers with prescribed function values at prescribed positions. While there might be additional local minima, such minima cannot be global. A second family of multivariate rational functions is given, having prescribed global minimizers and prescribed interpolating data.     

遗传算法的改进及其在电力系统无功优化中的应用

针对无功优化的动态、多目标、多约束以及非线性特点,提出了基于简单遗传算法的改进算法,在简单遗传算法的基础上,添加了自适应控制和适应度排序思想,并对算法终止准则进行了改进。以IEEE14节点标准测试系统为例对该算法进行了有效性验证。仿真结果表明,该方法对电力系统的无功优化效果良好。     

Analysis and Optimization of the Energy Efficiency in the 802.11 DCF

This paper introduces an analytical model to investigate the energy efficiency of the IEEE 802.11 distributed coordinated function (DCF). This model not only accounts for the number of contending nodes, the contention window, but also the packet size, and the channel condition. Based on this model, we identify the tradeoff in choosing optimum parameters to optimize the energy efficiency of DCF in the error-prone environment. The effects of contention window and packet size on the energy efficiency are examined and compared for both DCF basic scheme and DCF with four-way handshaking. The maximum energy efficiency can be obtained by combining both the optimal packet size and optimal contention window. To validate our analysis, we have done extensive simulations in ns-2, and simulation results seem to match well with the presented analytical results. The Ohio Board of Regents Doctoral Enhancements Funds and the National Science Foundation under Grant CCR 0113361 have supported this work. Xiaodong Wang received his B.S. degree in communication engineering from Beijing Information Technical Institute of China in 1995, and his M.S. degree in electric engineering from Beijing University of Aeronautics and Astronautics of China in 1998. He joined China Telecom in 1998 where he worked on communication protocols for telecommunication. From June 2000 to July 2002, he worked on GSM base station software development at Bell-labs China, Beijing, China. Currently he is a Ph.D. student in Computer Engineering at University of Cincinnati. His research activities include wireless MAC protocols, energy saving for wireless sensor networks. He is a student member of the IEEE. Jun Yin received the BS degree in automatic control from Dalian Railway Institute of China in 1997, and the MS degree in flight control from Beijing University of Aeronautics and Astronautics of China in 2001. Since 2001 she has been a Ph.D. student in the OBR Research Center for Distributed and Mobile Computing at the University of Cincinnati. Her research interests include performance evaluation of 802.11 MAC protocol, wireless ad hoc networks and sensor networks. She is a student member of the IEEE. Dharma P.Agrawal IEEE Fellow, 1987; ACM Fellow, 1998; AAAS Fellow, 2003 Dr. Agrawal is the Ohio Board of Regents Distinguished Professor of Computer Science and Computer Engineering in the department of Electrical and Computer Engineering and Computer Science, University of Cincinnati, OH. He has been a faculty member at Wayne State University, (1977–1982) and North Carolina State University (1982–1998). He has been a consultant to the General Dynamics Land Systems Division, Battelle, Inc., and the U. S. Army. He has held visiting appointment at AIRMICS, Atlanta, GA, and the AT&T Advanced Communications Laboratory, Whippany, NJ. He has published a number of papers in the areas of Parallel System Architecture, Multi computer Networks, Routing Techniques, Parallelism Detection and Scheduling Techniques, Reliability of Real-Time Distributed Systems, Modeling of C-MOS Circuits, and Computer Arithmetic. His recent research interest includes energy efficient routing, information retrieval, and secured communication in ad hoc and sensor networks, effective handoff handling and multicasting in integrated wireless networks, interference analysis in piconets and routing in scatternet, use of smart directional antennas (multibeam) for enhanced QoS, Scheduling of periodic real-time applications and automatic load balancing in heterogeneous workstation environment. He has four approved patents and three patent filings in the area of wireless cellular networks.     

DB2数据库查询优化策略

数据库的查询优化是改善应用程序性能的重要手段。通过分析IBM DB2数据库系统的最优化处理器的工作原理,对查询性能影响较大的统计信息更新、索引建立、SQL查询语句构造3个方面提出具体优化建议。建立了一套完整的测试方案,对每一条优化建议都使用具体SQL语句进行严格的验证。开发者要注意分析查询语句的时间开销和空间开销,才能写出较优的查询语句。     

Structural optimization design for large mirror

The system design must be started from the concept with low cost and high performance. In this point, the topological shape of the structure is very important in the view of the structural rigidities and light-weight design.In this paper, the optimization methodology is presented in the design stage of the large optical mirror. We obtain the optimal layout through the topology optimization and then design the details through the size or shape optimization for structural rigidity.     

An experimental analysis of a population based approach for global optimization

In this paper we perform a computational analysis of a population based approach for global optimization, Population Basin Hopping (PBH), which was proven to be very efficient on very challenging global optimization problems by the authors (see ). The experimental analysis aims at understanding more deeply how the approach works and why it is successful on challenging problems.     

Discrete global descent method for discrete global optimization and nonlinear integer programming

A novel method, entitled the discrete global descent method, is developed in this paper to solve discrete global optimization problems and nonlinear integer programming problems. This method moves from one discrete minimizer of the objective function f to another better one at each iteration with the help of an auxiliary function, entitled the discrete global descent function. The discrete global descent function guarantees that its discrete minimizers coincide with the better discrete minimizers of f under some standard assumptions. This property also ensures that a better discrete minimizer of f can be found by some classical local search methods. Numerical experiments on several test problems with up to 100 integer variables and up to 1.38 × 10¹⁰⁴ feasible points have demonstrated the applicability and efficiency of the proposed method.