ACTA MATHEMATICAE APPLIC ATAE SINICA(English Series)2007年第23卷第3期摘要(英文)

Parametric Duality Models for Semi-infinite Discrete Minmax Fractional Programming Problems Involving Generalized(η,ρ)-Invex Functions—G.J.Zalmai,Qing-hong Zhang A semi-infinite programming problem is a mathematical programming problem with a finite number of variables and infinitely many constraints.Duality theories and generalized     

Optimal value functions of generalized semi-infinite min-max programming on a noncompact set

In this paper, we study optimal value functions of generalized semi-infinite min-max programming problems on a noncompact set. Directional derivatives and subd-ifferential characterizations of optimal value functions are given. Using these properties, we establish first order optimality conditions for unconstrained generalized semi-infinite programming problems.     

ASYMPTOTIC APPROXIMATION METHOD AND ITS CONVERGENCE ON SEMI-INFINITE PROGRAMMING

The aim of this article is to discuss an asymptotic approximation model and its convergence for the minimax semi-infinite programming problem. An asymptotic surrogate constraints method for the minimax semi-infinite programming problem is presented by making use of two general discrete approximation methods. Simultaneously, the consistence and the epi-convergence of the asymptotic approximation problem are discussed.     

Some studies on mathematical models for general elastic multi-structures

The aim of this paper is to study the static problem about a general elastic multi-structure composed of an arbitrary number of elastic bodies, plates and rods. The mathematical model is derived by the variational principle and the principle of virtual work in a vector way. The unique solvability of the resulting problem is proved by the Lax-Milgram lemma after the presentation of a generalized Korn's inequality on general elastic multi-structures. The equilibrium equations are obtained rigorously by only assuming some reasonable regularity of the solution. An important identity is also given which is essential in the finite element analysis for the problem.     

ON THE DUALITY OF GENERALIZED GEOMETRIC PROGRAMMING

It is found that generalized geometric programming (GGP) is in fact a special case of generalized convex programming. By selecting a suitable bifunetion and calculating its adjoint function, the dual form of the standard GGP problem is derived. Some duality theorems are also obtained with this point of view. The method used is simpler and more general than what appeared in the literature.     

A Dynamic Programming Algorithm for the κ-Haplotyping Problem

The Minimum Fragments Removal （MFR） problem is one of the haplotyping problems： given a set of fragments, remove the minimum number of fragments so that the resulting fragments can be partitioned into k classes of non-conflicting subsets. In this paper, we formulate the κ-MFR problem as an integer linear programming problem, and develop a dynamic programming approach to solve the κ-MFR problem for both the gapless and gap eases.     

A kind of fuzzy linear programming problems based on interval-valued fuzzy sets

Abstract. The objective of this paper is to deal with a kind of fuzzy linear programming problem based on interval-valued fuzzy sets (IVFLP) through the medium of procedure that turns IVFLP into parametric linear programming via the mathematical programming. Some useful results for the benefit of solving IVFLP are expounded and proved,developed and discussed. Furthermore,that the proposed techniques in this paper allow the decision-maker to assign a different degree of importance can provide a useful way to efficiently help the decision-maker make their decisions.     

Spectral Element Viscosity Methods for Nonlinear Conservation Laws onthe Semi-Infinite Interval

In this paper we propose a spectral element: vanishing viscosity (SEW) method for the conservation laws on the semi-infinite interval. By using a suitable mapping, the problem is first transformed into a modified conservation law in a bounded interval, then the well-known spectral vanishing viscosity technique is generalized to the multi-domain case in order to approximate this trarsformed equation more efficiently. The construction details and convergence analysis are presented. Under a usual assumption of boundedness of the approximation solutions, it is proven that the solution of the SEW approximation converges to the uniciue entropy solution of the conservation laws. A number of numerical tests is carried out to confirm the theoretical results.     

NEW ALGORITHMS FOR LINEAR PROGRAMMING

The problem of solving a linear programming is converted into that of solving an uncon-strained maximization problem in which the objective function is concave. Two algorithms areproposed. These two algorithms have very simple structure and can be implemented easily. Forany given precision, the algorithms will terminate in a finite number of steps.     

广义几何规划的压缩共轭梯度路径非单调信赖域算法(英文)

In this paper,on the basis of making full use of the characteristics of unconstrained generalized geometric programming（GGP）,we establish a nonmonotonic trust region algorithm via the conjugate path for solving unconstrained GGP problem.A new type of condensation problem is presented,then a particular conjugate path is constructed for the problem,along which we get the approximate solution of the problem by nonmonotonic trust region algorithm,and further prove that the algorithm has global convergence and quadratic convergence properties.     

A dual-relax penalty function approach for solving nonlinear bilevel programming with linear lower level problem

The penalty function method, presented many years ago, is an important numerical method for the mathematical programming problems. In this article, we propose a dual-relax penalty function approach, which is significantly different from penalty function approach existing for solving the bilevel programming, to solve the nonlinear bilevel programming with linear lower level problem. Our algorithm will redound to the error analysis for computing an approximate solution to the bilevel programming. The error estimate is obtained among the optimal objective function value of the dual-relax penalty problem and of the original bilevel programming problem. An example is illustrated to show the feasibility of the proposed approach.     

The Generalized Center-Weak Saddle of General Homogeneous System of Degree n

In this paper,a problem of center-weak focus of a homogeneous system of degree n is transformed into a problem of generalized center-weak saddle. It provides formulae for the saddle values of the first (4-(-1)n)m orders in such a system,where m=n-1 if n is an even number and m=(n-1)/2 if n is an odd number.     

Optimality Conditions for Minimax Optimization Problems with an Infinite Number of Constraints and Related Applications

This paper is concerned with the study of optimality conditions for minimax optimization problems with an infinite number of constraints,denoted by(MMOP).More precisely,we first establish necessary conditions for optimal solutions to the problem(MMOP)by means of employing some advanced tools of variational analysis and generalized differentiation.Then,sufficient conditions for the existence of such solutions to the problem(MMOP)are investigated with the help of generalized convexity functions defined in terms of the limiting subdifferential of locally Lipschitz functions.Finally,some of the obtained results are applied to formulating optimality conditions for weakly efficient solutions to a related multiobjective optimization problem with an infinite number of constraints,and a necessary optimality condition for a quasiε-solution to problem(MMOP).     

Generalized K-T conditions and penalty functions for quasidifferentiable programming

In this paper,a quasidifferentiable programming problem with inequality constraintsis considered. First,a general form of optimality conditions for this problem is glven,which contains the results of Luderer,Kuntz and Scholtes. Next,a new generalized K-T condition is derived. The new optimality condition doesn‘t use Luderer‘s regularity assumption and ita Lagrangian multipliers don‘t depend on the particular elements in the superdifferentials of the object function and constraint functions, Finally,a penalty function for the prohlem is studied. Sufficient conditions of the penalty function attaining a global minimum are obtained.     

二阶($F, \alpha,\rho, d,p$) 一致凸性与极小极大分式规划的对偶

In this paper,we introduce a class of generalized second order(F,α,ρ,d,p)-univex functions.Two types of second order dual models are considered for a minimax fractional programming problem and the duality results are established by using the assumptions on the functions involved.     

An entropy based central cutting plane algorithm for convex min-max semi-infinite programming problems

In this paper,we present a central cutting plane algorithm for solving convex min-max semi-infinite programming problems.Because the objective function here is non-differentiable,we apply a smoothing technique to the considered problem and develop an algorithm based on the entropy function.It is shown that the global convergence of the proposed algorithm can be obtained under weaker conditions.Some numerical results are presented to show the potential of the proposed algorithm.     

具有V-不变凸的多目标规划的另一种方法

In this paper, optimality conditions for multiobjective programming problems having V-invex objective and constraint functions are considered. An equivalent multiobjective programming problem is constructed by a modification of the objective function.Furthermore, a (α, η)-Lagrange function is introduced for a constructed multiobjective programming problem, and a new type of saddle point is introduced. Some results for the new type of saddle point are given.     

ON KARUSH-KUHN-TUCKER POINTS FOR A SMOOTHING METHOD IN SEMI-INFINITE OPTIMIZATION

We study the smoothing method for the solution of generalized semi-infinite optimiza-tion problems from(O.Stein,G.Still:Solving semi-infinite optimization problems withinterior point techniques,SIAM J.Control Optim.,42(2003),pp.769-788).It is shownthat Karush-Kuhn-Tucker points of the smoothed problems do not necessarily converge toa Karush-Kuhn-Tucker point of the original problem,as could be expected from resultsin(F.Facchinei,H.Jiang,L.Qi:A smoothing method for mathematical programs withequilibrium constraints,Math.Program.,85(1999),pp.107-134).Instead, they mightmerely converge to a Fritz John point.We give,however,different additional assumptionswhich guarantee convergence to Karush-Kuhn-Tucker points.     

SUBSPACE SEARCH METHOD FOR A CLASS OF LEAST SQUARES PROBLEM

1. IntroductionNow the least squares problem is considered as follows:1Mid r(x,y) ~ SllAx By ~ bll' s.t. x 2 0 (1.1)where A E Rm",, B E R"q, and b E Re are given constant matrices and vectors,respectively.These problems arise in many areas of applications, such as scientific and engineering computing, physics, statistics, flited curve, economic, mathematical programming,social science, and as a component part of some large computation problem, as anexample, a nonlinear least squares pr…     

ON CRACK PROBLEMS IN AN INFINITE PLANE CONSISTING OF THREE DIFFERENT MEDIA

The mathematical problem of an infinite elastic plane consisting of three different media with an arbitrary number of cracks is considered. It is reduced to singular integral equations along the interfaces and the cracks by a constructive method. Those along the interfaces are further reduced to Fredholm ones.