Metaheuristic downhill simplex method in combinatorial optimization

The concept of combinatorial objects is formalized. It allows strict definition of a combinatorial optimization problem (COP). An efficient metaheuristic method to solve COPs (H-method) is considered. It includes stochastic local search algorithms as a built-in procedure. A parallel implementation of the H-method is set forth and analyzed. The results from a numerical experiment and solution of some well-known COPs on personal computers and on the SKIT cluster supercomputer are presented. The study was supported by INTAS (Project 06-1000017-8909). __________ Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 70–79, November–December 2007.     

Robust control of polytopic systems by convex optimization

Robust control synthesis of linear time-invariant SISO polytopic systems is investigated using the polynomial approach. A convex set of all stabilizing controllers for a polytopic system is given over an infinite-dimensional space. A finite-dimensional approximation of this set is obtained using the orthonormal basis functions and represented by a set of LMIs thanks to the KYP lemma. Then, an LMI based convex optimization problem for robust pole placement with sensitivity function shaping in two- and infinity-norm is proposed. The simulation results show the effectiveness of the proposed method.     

Information cut for clustering using a gradient descent approach

We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between probability density functions. We propose to optimize the Information Cut using a gradient descent-based approach. Our algorithm has several advantages compared to many other graph-based methods in terms of determining an appropriate affinity measure, computational complexity, memory requirements and coping with different data scales. We show that our method may produce clustering and image segmentation results comparable or better than the state-of-the art graph-based methods.     

Search for the upper bound of Bayesian estimates of the parameter in an exponential failure model with two known quantiles of an a priori distribution function

A fast exact algorithm of searching for the upper bound of Bayesian estimates for the parameter of the exponential distribution under the condition that an a priori distribution belongs to the class of all distribution functions with two equal quantiles. This problem arises in analyzing the sensitivity of Bayesian estimates to the choice of an a priori distribution in an exponential failure model. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 90–102, January–February 2007.     

基于网格的电大网络教育资源整合模式

建设优质的电大网络教育资源及其服务是电大远程教育长远发展的一大重要课题，通过对电大网络教育资源及其服务现状的调查，文章提出利用网格技术实现电大网络教育资源的整合优化模式，分别从网格系统框架、基本原则、组织形式、整合模式等方面阐述电大网格系统的建设，各电大网格节点统一规划、分工协作，在网络教育理论指导下或进行资源开发，或着重开发网格服务．实现电大网络教育资源的全面共享。     

Increasing testing productivity and software quality: A comparison of software testing methodologies within NASA

Pressure to compress the development life cycle and reduce the duration and resources committed to testing lead to experimentation in testing at the NASA Goddard Space Flight Centerís Software Engineering Laboratory. This study investigates the trend to reduce developer testing and increasingly rely upon inspection techniques and independent functional testing to shorten the development life cycle, improve testing productivity, and improve software quality.An approach is developed to conduct this comparison. In particular, the problem faced by software researchers, having a comprehensive characterization of software projects so similar types may be identified for comparative studies, is addressed using expert opinion.     

轧制规程优化设计

介绍了板、带材压下规程及型材的孔型优化设计问题，并指出了设计特点与方法，给出了优化后的效果。为钢材及其它有色金属轧制规程的设计提供了设计方法。     

降低锅炉飞灰可燃物的途径

介绍在发电厂锅炉运行过程中降低燃烧低挥发分高热值燃料飞灰含碳量的途径     

Binary particle swarm optimization with multiple evolutionary strategies

This paper introduces a novel variation of binary particle swarm optimization(BPSO) algorithm and a further extension to improve its performance.Firstly,mimicking the behaviors of some creatures group,multiple evolutionary strategies BPSO(MBPSO) is introduced which takes different evolutionary strategies for various particles according to their performances.Then,on the basis of MBPSO,a new strategy is discussed to improve the performance of the MBPSO(M2BPSO) which adopts the concept of the mutation operator aiming to overcome the premature convergence and slow convergent speed during the later stages of the optimization.The proposed two algorithms are tested on seven benchmark functions and their results are compared with those obtained by other methods.Experimental results show that our methods outperform the other algorithms.     

Sparse synthetic aperture radar imaging with optimized azimuthal aperture

To counter the problem of acquiring and processing huge amounts of data for synthetic aperture radar(SAR)using traditional sampling techniques,a method for sparse SAR imaging with an optimized azimuthal aperture is presented.The equivalence of an azimuthal match filter and synthetic array beamforming is shown so that optimization of the azimuthal sparse aperture can be converted to optimization of synthetic array beamforming.The azimuthal sparse aperture,which is composed of a middle aperture and symmetrical bilateral apertures,can be obtained by optimization algorithms(density weighting and simulated annealing algorithms,respectively).Furthermore,sparse imaging of spectrum analysis SAR based on the optimized sparse aperture is achieved by padding zeros at null samplings and using a non-uniform Taylor window.Compared with traditional sampling,this method has the advantages of reducing the amount of sampling and alleviating the computational burden with acceptable image quality.Unlike periodic sparse sampling,the proposed method exhibits no image ghosts.The results obtained from airborne measurements demonstrate the effectiveness and superiority of the proposed method.