LARGE－TIME BEHMIOR OF SOLUTIONS FOR THE SYSTEM OF COMPRESSIBLE ADIABATIC FLOW THROUGHPOROUS MEDIA

ＬＡＲＧＥ－ＴＩＭＥＢＥＨＭＩＯＲＯＦＳＯＬＵＴＩＯＮＳＦＯＲＴＨＥＳＹＳＴＥＭＯＦＣＯＭＰＲＥＳＳＩＢＬＥＡＤＩＡＢＡＴＩＣＦＬＯＷＴＨＲＯＵＧＨＰＯＲＯＵＳＭＥＤＩＡ￥ＸＩＡＯＬＩＮＧ（Ｌ．ＨＳＩＡＯ）Ｄ．ＳＥＲＲＥ（ＩｎｓｔｉｔｕｔｅｏｆＭａｔ...     

关于代数特征值反问题有解的充分条件

关于代数特征值反问题有解的充分条件张玉诲，朱本仁（山东大学数学系）ＯＮＴＨＥＳＵＦＦＩＣＩＥＮＴＣＯＮＤＩＴＩＯＮＳＦＯＲＴＨＥＳＯＬＶＡＢＩＬＩＴＹＯＦＧＥＮＥＲＡＬＡＬＧＥＢＲＡＩＣＩＮＶＥＲＳＥＥＩＧＥＮＶＡＬＵＥＰＲＯＢＬＥＭＳ￥ＺｈａｎｇＹ...     

STRONGLY ALGEBRAIC LATTICES AND CONDITIONS OF MINIMAL MAPPING PRESERVING INFS

ＳＴＲＯＮＧＬＹ ＡＬＧＥＢＲＡＩＣ ＬＡＴＴＩＣＥＳ ＡＮＤ ＣＯＮＤＩＴＩＯＮＳ ＯＦ ＭＩＮＩＭＡＬ ＭＡＰＰＩＮＧ ＰＲＥＳＥＲＶＩＮＧ ＩＮＦＳ ￥ＸＵＸＩＡＯＱＵＡＮＡｂｓｔｒａｃｔ：Ｔｈｅｔａｂｏｒｇｉｖｅｓｓｏｍｅｃｈａｒａｃｔｅｒｉ...     

MAJOR－EFFICIENT SOLUTIONS AND WEAKLY MAJOR－EFFICIENT SOLUTIONS OF MULTIOBJECTIVE PROGRAMMING

ＭＡＪＯＲ－ＥＦＦＩＣＩＥＮＴＳＯＬＵＴＩＯＮＳＡＮＤＷＥＡＫＬＹＭＡＪＯＲ－ＥＦＦＩＣＩＥＮＴＳＯＬＵＴＩＯＮＳＯＦＭＵＬＴＩＯＢＪＥＣＴＩＶＥＰＲＯＧＲＡＭＭＩＮＧ￥ＨＵＹＵＤＡ（Ｄｅｐｔ．ｏｆＡｐｐｌ．Ｍａｔｈ．，ＳｈａｎｇｈａｉＪｉａｏＴｏｎ...     

二维非线性椭圆型奇异摄动边值问题差分格式

二维非线性椭圆型奇异摄动边值问题差分格式刘国庆（南京化工学院）ＤＩＦＦＥＲＥＮＣＥＳＣＨＥＭＥＦＯＲＴＷＯ－ＤＩＭＥＮＳＩＯＮＮＯＮＬＩＮＥＡＲＥＬＬＩＰＴＩＣＳＩＮＧＵＬＡＲＬＹＰＥＲＴＵＲＢＥＤＢＯＵＮＤＡＲＹＶＡＬＵＥＰＲＯＢＬＥＭ￥ＬｉｕＧｕ...     

SOME GEOMETRIC PROPERLIES OFBROWNIAN MOTION ON SIERPINSKI GASKET

ＳＯＭＥ　ＧＥＯＭＥＴＲＩＣ　ＰＲＯＰＥＲＬＩＥＳ　ＯＦ　ＢＲＯＷＮＩＡＮ　ＭＯＴＩＯＮ　ＯＮ　ＳＩＥＲＰＩＮＳＫＩ　ＧＡＳＫＥＴＳＯＭＥＧＥＯＭＥＴＲＩＣＰＲＯＰＥＲＬＩＥＳＯＦＢＲＯＷＮＩＡＮＭＯＴＩＯＮＯＮＳＩＥＲＰＩＮＳＫＩＧＡＳＫＥＴ￥ＷＵ...     

SOME TOPOLOGICAL PROPERTIES ABOUT ALMOST PERIODIC DIFFERENTIAL EQUATIONS AND ALMOST PERIODIC SOLUTIONS

ＳＯＭＥ　ＴＯＰＯＬＯＧＩＣＡＬ　ＰＲＯＰＥＲＴＩＥＳ　ＡＢＯＵＴ　ＡＬＭＯＳＴ　ＰＥＲＩＯＤＩＣ　ＤＩＦＦＥＲＥＮＴＩＡＬ　ＥＱＵＡＴＩＯＮＳ　ＡＮＤ　ＡＬＭＯＳＴ　ＰＥＲＩＯＤＩＣ　ＳＯＬＵＴＩＯＮＳＺｈａｎｇＪｉａｎｆｅｎｇ（张剑峰）（Ｆｕｚｈ...     

TOPOLOGICAL STRUCTURE OF EFFICIENT SET OF OPTIMIZATION PROBLEM OF SET－VALUED MAPPING

ＴＯＰＯＬＯＧＩＣＡＬ ＳＴＲＵＣＴＵＲＥ ＯＦ ＥＦＦＩＣＩＥＮＴ ＳＥＴ ＯＦ ＯＰＴＩＭＩＺＡＴＩＯＮ ＰＲＯＢＬＥＭ ＯＦ ＳＥＴ－ＶＡＬＵＥＤ ＭＡＰＰＩＮＧ ￥ＬＩＹＵＡＮＸＩＡｂｓｔｒａｃｔ：Ｔｈｉｓｐａｐｅｒｉｓｃｏｎｃｅｒｎｅｄｗｉ...     

扩散系数反问题正则化数值方法的收敛性分析

扩散系数反问题正则化数值方法的收敛性分析朝红阳（中山大学计算机科学系）ＣＯＮＶＥＲＧＥＮＣＥＡＮＡＬＹＳＩＳＯＦＡＲＥＧＵＬＡＲＩＺＥＤＮＵＭＥＲＩＣＡＬＭＥＴＨＯＤＦＯＲＳＯＬＶＩＮＧＴＨＥＤＩＦＦＵＳＩＶＥＣＯＥＦＦＩＣＩＥＮＴＩＮＶＥＲＳＥＰＲ...     

UNIFORMLY VALID ASYMPTOTIC APPROXIMATIONS FOR NONLINEAR SINGULARLY－PERTURBED VECTOR BOUNDARY VALUE PROBLEMS

ＵＮＩＦＯＲＭＬＹＶＡＬＩＤＡＳＹＭＰＴＯＴＩＣＡＰＰＲＯＸＩＭＡＴＩＯＮＳＦＯＲＮＯＮＬＩＮＥＡＲＳＩＮＧＵＬＡＲＬＹ－ＰＥＲＴＵＲＢＥＤＶＥＣＴＯＲＢＯＵＮＤＡＲＹＶＡＬＵＥＰＲＯＢＬＥＭＳ￥ＳｈｉＹｕｍｉｎｇ（ＱｕｆｕＮｏｒｍａｌＵｎｉｖｅｒｓ...     

混合约束下广义几何规划的一种SQP算法

针对带等式和不等式约束的广义几何规划问题，构造了一种ＳＱＰ算法并证明了该算法的全局收敛性和局部二阶收敛性。     

混合约束下广义几何规划的一种全局收敛算法

In this paper, we develop a rapidly convergent algorithm for mixed constrained signomial geometric programming. The algorithm makes use of the characteristics of signomial geometric programming, and establishes a new active-set strategy on the basis of trust region method. The global convergence is proved, and some numerical tests are given to illustrate the effectiveness.     

Global optimization of signomial geometric programming problems

This paper presents a global optimization approach for solving signomial geometric programming problems. In most cases nonconvex optimization problems with signomial parts are difficult, NP-hard problems to solve for global optimality. But some transformation and convexification strategies can be used to convert the original signomial geometric programming problem into a series of standard geometric programming problems that can be solved to reach a global solution. The tractability and effectiveness of the proposed successive convexification framework is demonstrated by seven numerical experiments. Some considerations are also presented to investigate the convergence properties of the algorithm and to give a performance comparison of our proposed approach and the current methods in terms of both computational efficiency and solution quality.     

On a Lagrangian penalty function method for nonlinear programming problems

We modify a Lagrangian penalty function method proposed in [4] for constrained convex mathematical programming problems in order to obtain a geometric rate of convergence. For nonconvex problems we show that a special case of the algorithm in the above paper is still convergent without coercivity and convexity assumptions.On leave from the Institute of Mathematics, Hanoi, by a grant from Alexander-von-Humboldt-Stiftung.     

一个正定几何规划的对偶算法及收敛性

由于正定几何规划的对偶规划只含线性等式约束和非负约束,处理起来似乎要方便得多.然而,实际上许多对偶算法实施起来却往往失败(见[2,8,9]),这是由于对偶规划所特有的“块性质”以及目标函数在某些点的不可微性质引起的.因此,近年来主要的努力集中在克服这二个困难上。主要的工作有:1975年Beck和Ecker的修正凹单纯形     

A new type of condensation curvilinear path algorithm for unconstrained generalized geometric programming

A new type of condensation curvilinear path algorithm is proposed for unconstrained generalized geometric programming (GGP). First, a new type of condensation problem is presented based on the special structure of GGP. Then a particular curvilinear path for the problem is constructed, along which we get the approximate solution of the problem within a trust region. It is proved that the method is globally convergent and that the convergence rate is quadratic. Numerical experiments are given to show the effectiveness and feasibility of the algorithm.     

New method to posynomial geometric programming of trapezoidal fuzzy numbers

This paper presents a method for solving posynomial geometric programming with fuzzy coefficients. By utilizing comparison of fuzzy numbers with a method, the programming with fuzzy coefficients is reduced to the programming with constant coefficients. Then the programming with fuzzy coefficients can be solved by using a method for posynomial geometric programming. Finally, one comparative example is used to illustrate advantage of the new method.     

求解正定式几何规划的同论内点算法

求解正定式几何规划的同论内点算法张希，张可村（西安交通大学科学计算与应用软件系）ＡＨＯＭＯＴＯＰＹＩＮＴＥＲＩＯＲＡＬＧＯＲＩＴＨＭＦＯＲＰＯＳＹＮＯＭＩＡＬＧＥＯＭＥＴＲＩＣＰＲＯＧＲＡＭＭＩＮＧ￥ＺｈａｎｇＸｉ；ＺｈａｎｇＫｅ－ｃｕｎ（Ｄｅｐｔ．...     

Generic Algorithm for Generalized Fractional Programming

We propose a unified framework to study various versions of Dinkelbach-type algorithms for solving the generalized fractional programming problem. Classical algorithms used carefully selected iterate points and incorporated subtle convergence proofs. Our generic algorithm, however, is natural and simple. Moreover, the convergence analysis can be carried out through geometric observations and fundamental properties of convex functions. Consequently, the classical results are either refined or strengthened with new insights.     

Method of orthogonal simplexes and its applications to convex programming

Numerical methods for solving a convex programming problem are considered whose guaranteed convergence rate depends only on the space dimension. On average, the ratio of the corresponding geometric progression is better than that in the basis model of ellipsoids or simplexes. Results of numerical experiments are presented.