一个关于二次规划问题的分段线性同伦算法

本文发展了一个关于二次规划问题的分段线性同伦算法。该算法可看作是外点罚函数法的一个变体。凡是符合外点罚函数法收敛条件的二次规划问题用该算法均可经有限次轮回运算得到稳定解。大量的关于随机的凸二次规划问题的数值实验结果表明它的计算效率是高的，在某些条件下可能是多项式时间算法。     

用Eaves－Saigal不动点算法求解不可微优化

本文通过修改向量标号改造Ｅａｖｅｓ－Ｓａｉｇａｌ单纯同伦算法为上半连续集值映射零点的同伦算法，并给出了这一算法收敛的条件．最后，应用该方法到不可做优化问题的求解，得到一些收敛性结果．数值结果表明计算效果良好．     

同伦方法求解无界域上非凸规划问题的收敛性定理

利用同伦方法求解非凸规划时,一般只能得到问题的K-K-T点.本文得到无界域上同伦方法求解非凸规划的几个收敛性定理,证明在一定条件下,通过构造合适的同伦方程,同伦算法收敛到问题的局部最优解.     

用Eaves—Saigal不动点算法求解不可微优化

本文通过修改向量标号改造Ｅａｖｅｓ－Ｓａｉｇａｌ单纯用伦算法为上半连续集值映射零点的同伦算法，并给出了这一算法收敛的条件，最后，应用该方法到不可微优化问题的求解，得到一些收敛性结果，数值结果表明计算效果良好。     

解非对称矩阵特征值问题的一种并行分治算法

１引言考虑矩阵特征值问题其中Ａ是非对称矩阵．通过正交变换（如Ｈｏｕｓｅｈｏｌｄｅｒ变换或Ｇｉｖｅｎｓ变换）,Ａ可化为上Ｈｅｓｓｅｎｂｅｒｇ形．因而,本文假设Ａ为上Ｈｅｓｓｅｎｂｅｒｇ矩阵,表示如下：不失一般性,进一步假设所有的（ｊ＝２,…,ｎ）,即认为Ａ是不可约的关于如何求解上述问题,人们进行了不懈的努力,提出了许多行之有效的算法［１－８］．其中分治算法因具有良好的并行性而引人注目．分治算法的典型代表是基于同伦连续的分治算法［２,３,４］和基于Ｎｅｗｔｏｎ迭代的分治算法［１］．本文提出一种新的分…     

一类非凸区域的拟法锥构造方法及其在非凸规划求解中的应用

本文给出基于球形的一类满足拟法锥条件区域的拟法锥构造方法,基于该可行域的拟法锥,建立求解在该类非凸区域上的规划问题的K-K-T点的部分凝聚同伦组合方程,并证明了该同伦内点法的整体收敛性,给出实现同伦内点法的具体数值跟踪算法步骤,并通过数值例子证明算法是可行的和有效的．     

解非光滑方程组的广义数值延拓算法(I)---基本理论

本文研究了求解B-可微方程组的广义数值延拓算法的基本理论.其基本出发点是利用同伦延拓思想,建立相应的非光滑同伦方程组,论证其跟踪路径的存在唯一性及连续性.据此,在另文中进一步获得了广义数值延拓算法的适定性、收敛性,进而将新算法应用于几类重要的规划问题.     

关于非线性规划的同伦算法与罚函数法

本文揭示了关于非线性规划问题的同伦算法与外点罚函数法的关系，并讨论了有关同伦算法的收敛条件，给出了一些典型的检验问题的计算结果以表明利用结构的分段线性同伦算法的有效性。     

无界域上不定二次规划的一个算法

本给出了无界域上不定二次规划一个算法，该算法将不定二次规划转化为一系列凸二次规划，并证明了算法的收敛性。     

作为T－空间T－伦型不变量的特异指数

对Ｔ-空间之间引进了Ｔ-映射，Ｔ-同胚，Ｔ-映射的Ｔ-同伦，Ｔ-空间的Ｔ-同伦等价等概念．对Ｔ-紧致连通Ｈａｕｓｄｏｒｆｆ空间应用Cｅｃｈ-ｓｍｉｔｈ特异上同调理论定义了特异指数的概念，并在此基础上证明了Ｔ-空间的特异指数是Ｔ-空间的Ｔ-伦型不变量，从而也证明了它是Ｔ-空间的Ｔ-同胚不变量．     

A spline smoothing homotopy method for nonconvex nonlinear programming

Homotopy methods are globally convergent under weak conditions and robust; however, the efficiency of a homotopy method is closely related with the construction of the homotopy map and the path tracing algorithm. Different homotopies may behave very different in performance even though they are all theoretically convergent. In this paper, a spline smoothing homotopy method for nonconvex nonlinear programming is developed using cubic spline to smooth the max function of the constraints of nonlinear programming. Some properties of spline smoothing function are discussed and the global convergence of spline smoothing homotopy under the weak normal cone condition is proven. The spline smoothing technique uses a smooth constraint instead of m constraints and acts also as an active set technique. So the spline smoothing homotopy method is more efficient than previous homotopy methods like combined homotopy interior point method, aggregate constraint homotopy method and other probability one homotopy methods. Numerical tests with the comparisons to some other methods show that the new method is very efficient for nonlinear programming with large number of complicated constraints.     

A low-rank bilinear programming approach for sub-optimal solution of the quadratic assignment problem

This paper is concerned with a new approach for solving quadratic assignment problems (QAP). We first reformulate QAP as a concave quadratic programming problem and apply an outer approximation algorithm. In addition, an improvement routine is incorporated in the final stage of the algorithm. Computational experiments on a set of standard data demonstrate that this algorithm can yield favorable results with a relatively low computational effort.     

凸规划的新算法

对一般凸目标函数和一般凸集约束的凸规划问题新解法进行探讨,它是线性规划一种新算法的扩展和改进,此算法的基本思想是在规划问题的可行域中由所建－的一个切割面到另一个切割面的不断推进来求取最优的。文章对目标函数是二次的且约束是一般凸集和二次目标函数且约束是线性的情形,给出了更简单的算法。     

无界域上不定二次规划的一个算法

本文给出了无界域上不定二次规划一个算法 ,该算法将不定二次规划转化为一系列凸二次规划 ,并证明了算法的收敛性 .     

Branch and bound algorithm for multidimensional scaling with city-block metric

A two level global optimization algorithm for multidimensional scaling (MDS) with city-block metric is proposed. The piecewise quadratic structure of the objective function is employed. At the upper level a combinatorial global optimization problem is solved by means of branch and bound method, where an objective function is defined as the minimum of a quadratic programming problem. The later is solved at the lower level by a standard quadratic programming algorithm. The proposed algorithm has been applied for auxiliary and practical problems whose global optimization counterpart was of dimensionality up to 24.     

一类大规模二次规划问题的可行下降分解算法

本文对一类大规模二次规划问题，提出了矩阵剖分的概念和方法，并将问题转化为求解一系列容易求解的小规模二次规划子问题．另外，通过施加某些约束机制，使子问题所产生的迭代点均为可行下降点．在通常的假定下，证明算法具有全局收敛性，大量数值实验表明，本文所提出的新算法是有效的。     

弱拟法锥条件下非凸优化问题的同伦算法

本文给出弱拟法锥条件的定义,并针对非线性组合同伦方程,得到在弱拟法锥条件下求解约束非凸优化问题的同伦内点算法.证明了该算法对于可行域的某个子集中几乎所有的点,同伦路径存在,并且同伦路径收敛于问题的K-K-T点,通过数值例子验证了该算法是有效的.     

An Extended Sequential Quadratically Constrained Quadratic Programming Algorithm for Nonlinear, Semidefinite, and Second-Order Cone Programming

This paper is concerned with nonlinear, semidefinite, and second-order cone programs. A general algorithm, which includes sequential quadratic programming and sequential quadratically constrained quadratic programming methods, is presented for solving these problems. In the particular case of standard nonlinear programs, the algorithm can be interpreted as a prox-regularization of the Solodov sequential quadratically constrained quadratic programming method presented in Mathematics of Operations Research (2004). For such type of methods, the main cost of computation amounts to solve a linear cone program for which efficient solvers are available. Usually, “global convergence results” for these methods require, as for the Solodov method, the boundedness of the primal sequence generated by the algorithm. The other purpose of this paper is to establish global convergence results without boundedness assumptions on any of the iterative sequences built by the algorithm.