非线性延迟积分微分方程线性多步法的渐近稳定性

本文研究求解非线性延迟积分微分方程的线性多步法的渐近稳定性,其中积分部分采用复化梯形公式计算,结果表明:在问题真解渐近稳定的条件下,A-稳定的线性多步法也是渐近稳定的.     

一类stiff稳定的线性多步法

§1.引言 在常微分方程初值问题的数值方法中,线性多步法是最简单、使用最广泛的方法之一.但由于现存的线性多步方法的绝对稳定区域较小,以致在解刚性(Stiff)微分方程中受到很大限制.本文在BDF方法及[2]的基础上增加二个修正项,构造一类修正BDF的线性多步法,具有较大的绝对稳定区域.其结果如下:此类修正方法的阶与同步数的BDF方法的阶一致,其绝对稳定区域与低二阶的BDF方法大致相同,甚至更好,并给出了参数的取值范围.     

用加权平均方法构造新的隐式线性多步法公式

在已知的线性多步法公式中,用两个较适合的线性多步法进行加权平均就能构造出一系列新的隐式线性多步法公式,而且其中有些公式可能具有较好的性质,如稳定域增大.从而使得解刚性方程时,可以根据对稳定域与截断误差不同的需求来选择公式,以达到在适合的稳定域下,截断误差最小.经过数值试验验证,本文举出的实例中用加权平均方法构造出的有些新公式的稳定域大于原来两个公式任一个的稳定域,可应用于求解常微分方程初值问题的刚性问题.     

线性随机微分方程多步法的稳定性

研究了多步法用于求解线性随机微分方程的稳定性,利用维纳过程的增量服从正态分布的性质,得到了在乘性噪声情况下,多步法用于线性随机微分方程的均方稳定性的条件,并用MATLAB对实际算例进行了数值模拟.     

中立型微分方程组连续线性多步法

我们曾对中立型微分方程组给出了任意阶的单步解法.但是,就计算量来说,多步法比较优越.本文将给出连续线性多步法,它类似于常微分方程组Adams线性多步法.当方程是常微且取离散解时,它就是Adams法;当方程不含导数时,它是某类Volterra泛函微分方程组的线性多步法(Volterra微分积分方程与迟延方程为其特例).本文的算法在     

求解非线性刚性初值问题的隐显线性多步方法的误差分析

隐显线性多步方法由隐式线性多步方法和显式线性多步法组合而成.本文主要讨论求解满足单边Lipschitz条件的非线性刚性初值问题和一类奇异摄动初值问题的隐显线性多步方法的误差分析.最后,由数值例子验证了所获的理论结果的正确性及方法处理这两类问题的有效性.     

求解非线性中立型延迟微分方程一类线性多步方法的收敛性

本文致力于带有Lagrang插值的一类线性多步法求解非线性中立型延迟微分方程的误差分析.证明了一个p′阶的线性多步方法配上一个q阶的Lagrang插值导致一个minf[p′,q 1]阶的E-(或EB-)收敛的非线性中立型延迟微分方程数值方法.     

线性多步法中的分枝现象

1 引言 在文献[1],[2]中,Yamaguti和Ushiki发现了用中心差商求解微分方程得到的数值解不是真解的逼近解,而是与真解相差很远的解,这种解被称为“鬼解”,在[2]中指出,用中心差商求解微分方程,当原初值点是方程的稳定点时,在差分化方程中,初值点是双曲鞍点,因此不论时间步长△t取得多么小,甚至取极限△t→0,得到的解与原方程的解完全不同,文献[3]中将上面结论推广到R~n中的情形,并且导出中心化后的极限方程,本文讨论线性多步法中的分枝现象,比较用线性多步法求得解与原方程解之间的差别,并且探索线性多步法出现“鬼解”的可能性。     

多时滞微分方程数值稳定性

考虑了时滞微分方程的初值问题,分析了用线性多步法求解一类滞后型微分系统数值解的稳定性,在一定的Lagrange插值条件下,给出并证明了求解滞后型微分系统的线性多步法数值稳定的充分必要条件.     

非线性中立型延迟积分微分方程线性多步法的散逸性

考虑非线性中立型延迟积分微分方程数值方法的散逸性,把一类线性多步法应用到以上问题中,当积分项用复合求积公式逼近时,证明该数值方法在满足一定条件下具有散逸性.     

An Optimal Control Problem of a Coupled Nonlinear Parabolic Population System

An optimal control problem for a coupled nonlinear parabolic population system is considered. The existence and uniqueness of the positive solution for the system is shown by the method of upper and lower solutions. An explicit prior bound of solutions to the system is given by considering an auxiliary coupled linear system. The existence of the optimal control is proved and the characterization of the optimal control is established.     

On visco - plasticity with hardening

A stability theory is developed for finite difference approximations on nonuniform grids for m-th order linear integrodifferential equations under linear side conditions. The stability inequalities are obtained in l^ρ-spaces, pε[1,∞]. The eigenvalue problem is included.     

Nonlinear Riemann - Hilbert Problems without Transversality

Nonlinear Riemann - Hilbert problems (RHP) generalize two fundamental classical problems for complex analytic functions, namely: 1. the conformal mapping problem, and 2. the linear Riemann - Hilbert problem. This paper presents new results on global existence for the nonlinear (RHP) in doubly connected domains with nonclosed restriction curves for the boundary data. More precisely, our nonlinear (RHP) is required to become ?at infinity”?, i.e., for solutions having large moduli, a linear (RHP) with variable coefficients. Global existence for q-connected domains was already obtained in [9] for the special case that the restriction curves for the boundary data ?at infinity”? coincide with straight lines corresponding to linear (RHP)-s with special so-called constant - coefficient transversality boundary conditions. In this paper, the boundary conditions are much more general including highly nonlinear conditions for bounded solutions in the context of nontransversality. In order to prove global existence, we reduce the problem to nonlinear singular integral equations which can be treated by a degree theory of Fredholm - quasiruled mappings specifically constructed for mappings defined by nonlinar pseudodifferential operators.     

Copositive optimization - Recent developments and applications

Due to its versatility, copositive optimization receives increasing interest in the Operational Research community, and is a rapidly expanding and fertile field of research. It is a special case of conic optimization, which consists of minimizing a linear function over a cone subject to linear constraints. The diversity of copositive formulations in different domains of optimization is impressive, since problem classes both in the continuous and discrete world, as well as both deterministic and stochastic models are covered. Copositivity appears in local and global optimality conditions for quadratic optimization, but can also yield tighter bounds for NP-hard combinatorial optimization problems. Here some of the recent success stories are told, along with principles, algorithms and applications.     

Cuts for mixed 0-1 conic programming

In this we paper we study techniques for generating valid convex constraints for mixed 0-1 conic programs. We show that many of the techniques developed for generating linear cuts for mixed 0-1 linear programs, such as the Gomory cuts, the lift-and-project cuts, and cuts from other hierarchies of tighter relaxations, extend in a straightforward manner to mixed 0-1 conic programs. We also show that simple extensions of these techniques lead to methods for generating convex quadratic cuts. Gomory cuts for mixed 0-1 conic programs have interesting implications for comparing the semidefinite programming and the linear programming relaxations of combinatorial optimization problems, e.g. we show that all the subtour elimination inequalities for the traveling salesman problem are rank-1 Gomory cuts with respect to a single semidefinite constraint. We also include results from our preliminary computational experiments with these cuts.Research partially supported by NSF grants CCR-00-09972, DMS-01-04282 and ONR grant N000140310514.     

FLIM - A Variant of FEM based on Line Integration

A variant of the finite element method (FEM) for modelling and solving partial differential equations based on triangular and tetrahedral meshes is proposed. While FEM is based on integration over finite elements, the new approach - briefly denoted as FLIM hereafter - uses integration along edges (finite lines). The stiffness matrix, which - for linear triangles and tetrahedra - is identical with the one obtained with FEM, as well as the load vector can solely be obtained by summing up the edge contributions. This new variant requires much lower storage than FEM, especially for three-dimensional problems, but yields the same approximation error and convergence rate as the finite element method. It is shown that its performance, when applied to linear problems, is in close agreement with the performance of the finite element method. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

SEQUENTIAL SYSTEMS OF LINEAR EQUATIONS ALGORITHM FOR NONLINEAR OPTIMIZATION PROBLEMS-INEQUALITY CONSTRAINED PROBLEMS

AbstractIn this paper, a new superlinearly convergent algorithm of sequential systems of linear equations (SSLE) for nonlinear optimization problems with inequality constraints is proposed. Since the new algorithm only needs to solve several systems of linear equations having a same coefficient matrix per iteration, the computation amount of the algorithm is much less than that of the existing SQP algorithms per iteration. Moreover, for the SQP type algorithms, there exist so-called inconsistent problems, i.e., quadratic programming subproblems of the SQP algorithms may not have a solution at some iterations, but this phenomenon will not occur with the SSLE algorithms because the related systems of linear equations always have solutions. Some numerical results are reported.     

Book review of advances in gabor analysis,applied and numerical harmonic analysis,Hans G. Feichtinger and Thomas Strohmer (Eds.), Birkhäuser,Boston-Basel-Berlin, 2002, 356 pages. ISBN 0-8176-4239-0

In some recent publications it was shown that certain stationary stochastic dynamic programming problems with general state and action spaces can be solved by generalized linear programming. It Is the main aim of the present paper to demonstrate that a similar linear programming approach is feasible even in the non-stationary case. For this end, we formulate a programming problem (D^?) and show that (D^?) is equivalent to the problem of finding a p=optimal policy for the stochastic dynamic program, whereas a modification of (D^?) turns out to be the dual program of a pair of general linear programs.     

Tightening concise linear reformulations of 0-1 cubic programs

A common strategy for solving 0-1 cubic programs is to reformulate the non-linear problem into an equivalent linear representation, which can then be submitted directly to a standard mixed-integer programming solver. Both the size and the strength of the continuous relaxation of the reformulation determine the success of this method. One of the most compact linear representations of 0-1 cubic programs is based on a repeated application of the linearization technique for 0-1 quadratic programs introduced by Glover. In this paper, we develop a pre-processing step that serves to strengthen the linear programming bound provided by this concise linear form of a 0-1 cubic program. The proposed scheme involves using optimal dual multipliers of a partial level-2 RLT formulation to rewrite the objective function of the cubic program before applying the linearization. We perform extensive computational tests on the 0-1 cubic multidimensional knapsack problem to show the advantage of our approach.     

Nash equilibrium in a pay-as-bid electricity market Part 2 - best response of a producer

We consider a multi-leader-common-follower model of a pay-as-bid electricity market in which the producers provide the regulator with either linear or quadratic bids. We prove that for a given producer only linear bids can maximize his profit. Such linear bids are referred as the ‘best response’ of the given producer. They are obtained assuming the demand is known and some estimate of the bids of the other producers is available. Nevertheless we also show that whenever no best response exists, the optimal profit can be asymptotically attained by a sequence of quadratic bids converging to the so-called ‘limiting best response’. An explicit formula for such a sequence is provided.