数学规划问题 的翻译结果

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mathematical programming problem

Duality-based regularization in a linear convex mathematical programming problem

Necessary conditions for an extremum in a mathematical programming problem

A semi-infinite programming problem is a mathematical programming problem with a finite number of variables and infinitely many constraints.

Initially, the technique solves the knapsack relaxation of the original mathematical programming problem using dynamic programming.

They are used as functions of a particular mathematical programming problem.

mathematical programming problems

Large-Dimensional Mathematical Programming Problems: A Solution Approach

An algorithm is designed for numerically solving large-dimensional mathematical programming problems, in which only the variables in linear constraints play a dominant role.

The method of feasible directions for mathematical programming problems with preconvex constraints

Generalization of the newton method for one class of nonconvex mathematical programming problems

Several mathematical programming problems, and static and dynamic response structural design problems are used to evaluate the method.

This paper deals with the problem of how, to determine the region of the initial value in a linear differential equation of high order when the u-pper and lower bounds of the Solutions have been given. This is u funda-mental problem in automatic control, which is usually solved by constru-cting лsinyHOB functions. Here, we try to solve it from another approach.Fir- , st it is changed into a mathematical programming problem, then the region is estimated by convex polyhedrons. It is easy to see that this appJoach...

This paper deals with the problem of how, to determine the region of the initial value in a linear differential equation of high order when the u-pper and lower bounds of the Solutions have been given. This is u funda-mental problem in automatic control, which is usually solved by constru-cting лsinyHOB functions. Here, we try to solve it from another approach.Fir- , st it is changed into a mathematical programming problem, then the region is estimated by convex polyhedrons. It is easy to see that this appJoach has greater flexibility and precision than the method of using лsinyHOB fu-nctions. In addition, we proved the convergence of the method. At the eud of the article, an example is provided.

本文研究的是,在一个高阶线性常微分方程中,当给定解的上、下界时,如何去确定其初值的变化范围。这是自动控制系统中的一个基本课题,一般是利用构造ЛЯпулов函数的方法来解决。本文从另一条思路予以考虑:先将问题化成数学规划问题,利用凸多面体来估计所求的范围。这样做与ЛЯпулов函数方法比较,有较大的灵活性和较高的精确度,计算上亦不困难。另外,我们对与之有关的一些理论问题作了些研究,给出了此方法收敛性的证明。本文最后还给出了一个计算例子。

vol. 22, no. 5, 2004.[21] juliang zhang, jian chen, xinjian zhuo, a constrained optimization approach for lcp, journal of computational mathematics, vol. 22, no. 4, 509-522, 2004. [22] juliang zhang, on the convergence properties of the levenberg--marquardt method, optimization, vol. 52, no. 6, 739-756, 2003.[23] juliang zhang, yong wang, a new trust region method for nonlinear equations, mathematical methods of operations research, vol. 58, no. 2, 283-298, 2003. [24] juliang zhang, xiangsun zhang, predictor-corrector smoothing methods for monotone lcp, acta mathematicae applicatae sinica。optimization: a j. of mathematical programming and operationsresearch。[11]guo h y, li z l. structural topology optimization of high-voltage transmission tower with discrete variables[j]. structural and multidisciplinary optimization, 2011, 43(6): 851-861.。

The mathematical formula in similarity of linear equality or linear inequality system with degeneration is finally obtained when many structural optimization problems are solved with optimality criterion method, as well as general mathematical programming. In this case, many algorithms fail to get solution or perform poorly. A unified method presented in this paper which is based on method presented in thispaper which is based on simplex method of linear propramming in used to overcome the difficulty mentioned previously. Optimality criterion method, constrained second order approximation method, Newton-Raphson method, the secone order algorithms of the Fleury's dual method and other method have been improved by using the basic idea of the method discussed in this paper, Numerical examples are given showing the validity of the method.

在结构优化准则法中,乃至一般的数学规划问题中,存在大量问题有相近的数学形式,通常是具有退化性质的线性等式或不等式系统,各种具体的解法往往失效,本文提出一个基于线性规划单纯形法之上的统一方法解决了这一困难。无论对于准则法,约束二阶近似的方法,Newton-Rap-hson方法,Fleury的对偶方法的二阶算法,本文提出的方法都是有效的,数值例子支持了该方法。

This paper is believed to be the first to present a new unified hardening

本文首次提出经典塑性力学中的一种统一强化模型。这一模型把理想塑性材料结构的结构强化和实际上广泛采用的等向强化、线性随动强化、混合强化、滑移强化等材料强化用统一的数学规律描述。这种统一性使通常仅适用于理想塑性材料的方法,诸如极限分析和安定分析中的上、下限定理以及本文作者提出的塑性应变模态法,原则上都可以直接推广用于强化材料。应用统一强化模型,弹塑性分析的增量法中基本的最小余能率原理可以表达为最小综合弹性余能率原理。这便于直接地归结为一个数学规划问题,并在弹塑性计算中推广了力法的应用、以补充习用的位移法。本文从最小余能率原理出发、又导出若干等价的原理,包括最小正则化综合残余应力幅率原理和在正则化空间中状态点的最陡爬升路线原理。

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