基于几何不变量的蛋白质三维分子结构比对

为了解决蛋白质三维结构比对需要处理大量的旋转、平移变换，直接用动态规划将变得十分繁琐这一问题，在保留蛋白质空间结构属性特征的基础上，对蛋白质三维数据进行了预先的处理．通过计算蛋白质结构在旋转和平移下的几何不变量，将蛋白质的三维结构坐标变换为具有旋转、平移不变性的一维序列．进一步给出了“距离”以及“相似得分”的定义．在此基础上采用动态规划方法给出了新的蛋白质结构比对算法．对专家分类的蛋白质结构数据库进行测试，结果显示准确、快速．     

A constructive characterization of the split closure of a mixed integer linear program

Two independent proofs of the polyhedrality of the split closure of mixed integer linear program have been previously presented. Unfortunately neither of these proofs is constructive. In this paper, we present a constructive version of this proof. We also show that split cuts dominate a family of inequalities introduced by Köppe and Weismantel.     

The uv-Decomposition on a Class of D.C. Functions and Optimality Conditions

In this paper,the UV-theory and P-differential calculus are employed to study second-order ex-pansion of a class of D.C.functions and minimization problems.Under certain conditions,some properties ofthe U-Lagrangian,the second-order expansion of this class of functions along some trajectories are formulated.Some first and second order optimality conditions for the class of D.C.optimization problems are given.     

A New Algorithm for the Elimination of Common Subexpressions in Hardware Implementation of Digital Filters by Using Genetic Programming

A new algorithm based on Genetic Programming (GP) for the problem of optimization of Multiple constant Multiplication (MCM) by Common Subexpression Elimination(CSE) is developed. This method is used for hardware optimization for DSP systems. A solution based on Genetic Programming is shown in this paper. The performance of the technique is demonstrated in one- and multi-dimensional digital filters with constant coefficients.     

SUN5500小型机MPI编程与蕴式并行计算的实现方法

基于SUN5500小型计算机并行开发环境，给出了消息传递模型和蕴式行模型的实现方法，通过实例分析了SUNMPI实际编程，并对选取不同模型有不同参数的运算时间进行了比较，结果表明，在SUN5500计算机上MPI模型和蕴式并行模型均能较大地提高运算速度，而且MPI在灵活性和并行程度方面更优。     

On the stability of some integer programming algorithms

In the present paper we develop our approach for studying the stability of integer programming problems. We prove that the L-class enumeration method is stable on integer linear programming problems in the case of bounded relaxation sets [9]. The stability of some cutting plane algorithms is discussed.     

A generic view of Dantzig-Wolfe decomposition in mixed integer programming

The Dantzig-Wolfe reformulation principle is presented based on the concept of generating sets. The use of generating sets allows for an easy extension to mixed integer programming. Moreover, it provides a unifying framework for viewing various column generation practices, such as relaxing or tightening the column generation subproblem and introducing stabilization techniques.     

Integration and propagation of a multi-criteria decision making model in constraint programming

In this paper we propose a general integration scheme for a Multi-Criteria Decision Making model of the Multi-Attribute Utility Theory in Constraint Programming. We introduce the Choquet integral as a general aggregation function for multi-criteria optimization problems and define the Choquet global constraint that propagates this function during the Branch-and-Bound search. Finally the benefits of the propagation of the Choquet constraint are evaluated on the examination timetabling problem.     

A Constraint Programming Approach to Extract the Maximum Number of Non-Overlapping Test Forms

This paper introduces a novel approach for extracting the maximum number of non-overlapping test forms from a large collection of overlapping test sections assembled from a given item bank. The approach involves solving maximum set packing problems (MSPs). A branch-and-bound MSP algorithm is developed along with techniques adapted from constraint programming to estimate lower and upper bounds on the optimal MSP solution. The algorithm is general and can be applied in other applications including combinatorial auctions. The results of computer simulations and experiments with an operational item bank are presented. An erratum to this article is available at .     

On a Modified Subgradient Algorithm for Dual Problems via Sharp Augmented Lagrangian*

We study convergence properties of a modified subgradient algorithm, applied to the dual problem defined by the sharp augmented Lagrangian. The primal problem we consider is nonconvex and nondifferentiable, with equality constraints. We obtain primal and dual convergence results, as well as a condition for existence of a dual solution. Using a practical selection of the step-size parameters, we demonstrate the algorithm and its advantages on test problems, including an integer programming and an optimal control problem. *Partially Supported by 2003 UniSA ITEE Small Research Grant Ero2. Supported by CAPES, Brazil, Grant No. 0664-02/2, during her visit to the School of Mathematics and Statistics, UniSA.