Shape Optimization and Fictitious Domain Approach for Solving Free Boundary Problems of Bernoulli Type

This contribution deals with an efficient method for the numerical realization of the exterior and interior Bernoulli free boundary problems. It is based on a shape optimization approach. The state problems are solved by a fictitious domain solver using boundary Lagrange multipliers.     

Shape Optimization for Semi-Linear Elliptic Equations Based on an Embedding Domain Method

We study a class of shape optimization problems for semi-linear elliptic equations with Dirichlet boundary conditions in smooth domains in ℝ². A part of the boundary of the domain is variable as the graph of a smooth function. The problem is equivalently reformulated on a fixed domain. Continuity of the solution to the state equation with respect to domain variations is shown. This is used to obtain differentiability in the general case, and moreover a useful formula for the gradient of the cost functional in the case where the principal part of the differential operator is the Laplacian. Online publication 23 January 2004.     

Global Solution of Optimization Problems with Parameter-Embedded Linear Dynamic Systems

This paper develops a theory for the global solution of nonconvex optimization problems with parameter-embedded linear dynamic systems. A quite general problem formulation is introduced and a solution is shown to exists. A convexity theory for integrals is then developed to construct convex relaxations for utilization in a branch-and-bound framework to calculate a global minimum. Interval analysis is employed to generate bounds on the state variables implied by the bounds on the embedded parameters. These bounds, along with basic integration theory, are used to prove convergence of the branch-and-bound algorithm to the global minimum of the optimization problem. The implementation of the algorithm is then considered and several numerical case studies are examined thoroughly     

GA optimization on multi-segments muffler under space constraints

Whilst the space volume of muffler in noise control system is often constrained for maintenance in practical engineering work, the maximization on muffler’s performance becomes important and essential. In this paper, a novel approach genetic algorithms (GAs) based on the principles of natural biological evolution will be used to tackle this optimization of muffler design [M. Mitchell, An Introduction to Genetic Algorithms, The MIT Press, Cambridge, MA, 1996]. Here, the shape optimization of multi-segments muffler coupled with the GA searching technique is presented. The techniques of binary genetic algorithms (BGA) together with the commercial MATLAB package [G. Lindfield, J. Penny, Numerical Method Using Matlab, second ed., Prentice Hall, Englewood Cliffs, NJ, 2000] are applied in GA searching. In addition, a numerical case of pure tone elimination with 2-5 segments on muffler is introduced and fully discussed. To achieve the best optimization in GA, several GA parameters are on trial in various values. Results show that the GA operators, including crossover mutation and elitism, are essential in accuracy. Consequently, results verify that the optimal sound transmission loss at the designed frequency of 500 Hz is exactly maximized. The GA optimization on multi-segments muffler proposed in this study surely provides a quick and correct approach.     

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.