Banach空间中微分包含解的存在性*

本文在无穷维Banach空间中讨论微分包含解的存在性,先给出了几个普通微分包含的比较定理,讨论了近似解与解的关系,然后得到了Banach空间中微分包含解的存在性定理.     

跟踪微分系统解的研究

在已有的跟踪微分器理论的基础上,证明了跟踪微分器系统的解关于输入信号的连续性,并且为了便于考察跟踪微分器系统解的结构特点等性质,利用逼近函数设计了新型的跟踪微分器,进而证明了其解与具有不连续右端的跟踪微分器的解之间的等价关系.最后,给出了跟踪微分器应用于雷达跟踪目标运动状态的仿真计算结果,表明了由于其不依赖目标运动状态方程的特点,在实践应用中具有相当大的优势.     

微分代数方程去奇异化分析

利用去奇异化方法讨论了拟线性微分代数方程在奇点邻域内光滑解的性质.通过尺度参数的微分同胚变换,将拟线性微分代数方程转化为相应的常微分方程,从而构造出在孤立奇点邻域内的初始微分代数方程的光滑解,给出解存在的充分条件,并进一步讨论了解的性质.     

拟凸函数的近似次微分及其在多目标优化问题中的应用

针对拟凸函数提出一类新的近似次微分,研究其性质,并将近似次微分应用到拟凸多目标优化问题近似解的刻画中.首先,对已有的近似次微分进行改进,得到拟凸函数新的近似次微分,并给出其与已有次微分之间的关系及一系列性质.随后,利用新的近似次微分给出拟凸多目标优化问题近似有效解、近似真有效解的最优性条件.     

一类非线性微分-积分时滞反应扩散系统奇摄动问题的广义解

该文研究了一类非线性微分-积分时滞广义反应扩散系统奇摄动问题.在适当的条件下,利用奇摄动方法构造了初始-边值问题广义解的渐近展开式.建立了广义解的微分不等式理论,并证明了相应解的存在性及其解的渐近展开式的一致有效性.     

亚纯函数系数微分方程的解和小函数的关系

研究了一类亚纯函数为系数的二阶非齐次线性微分方程的解及其微分多项式和小函数的关系,并得到了这类微分方程解以及解的一阶,二阶导数与微分多项式的不动点性质.     

一类随机脉冲微分系统的稳定性

本文给出了随机脉冲微分系统零解的最终稳定性的定义,利用Liapunov函数,得到了非线性随机脉冲微分系统零解一致最终稳定性及一致最终渐进稳定性和最终不稳定的充分条件.     

微分、差分方程的机械化方法

介绍了微分与差分方程机械化方法研究若干最新进展.主要结果包括: 微分、差分方程的特征列理论与算法,微分、差分方程系统的分解算法以及微分、差分方程解析解求解算法.     

一类四阶微分方程的奇摄动边值问题

运用合成展开法和微分不等式理论研究了一类四阶方程的奇摄动边值问题.先运用合成展开法,构造了问题的形式渐近解,再运用微分不等式理论证明了原问题解的存在性及所得形式渐近解的一致有效性.最后用一个例子来说明所得结果的意义.     

拟凸多目标优化问题近似解的最优性条件

研究了拟凸多目标优化问题近似弱有效解、近似有效解的最优性条件.首先,在已有拟凸函数次微分的基础上引进4种近似次微分的概念,并给出它们之间的关系.然后,将4种近似次微分的概念应用到拟凸多目标优化问题中,给出了拟凸多目标优化问题近似弱有效解和近似有效解的充分条件和必要条件,并给出实例加以说明.     

非线性特征值问题的二次近似方法

本文研究求解非线性特征值问题的数值方法.基于矩阵值函数的二次近似,将非线性特征值问题转化为二次特征值问题,提出了求解非线性特征值问题的逐次二次近似方法,分析了该方法的收敛性.结合求解二次特征值问题的Arnoldi方法和Jacobi-Davidson方法,给出求解非线性特征值问题的一些二次近似方法.数值结果表明本文所给算法是有效的.     

Quasi-Newton Methods for Nonlinear Least Squares Focusing on Curvatures

A new quasi-Newton method for nonlinear least squares problems is proposed. Two advantages of the method are accomplished by utilizing special geometrical properties in the problem class. First, fast convergence is established for well-conditioned problems by interpolating both the current and the previous step in each iteration. Second, high accuracy is achieved for certain difficult problems, such as ill-conditioned problems and problems with large curvatures in the tangent space. Numerical results for artificial problems and standard test problems are presented and discussed.     

Differential sensitivity of solutions of convex constrained optimal control problems for discrete systems

A family of optimal control problems for discrete systems that depend on a real parameter is considered. The problems are strongly convex and subject to state and control constraints. Some regularity conditions are imposed on the constraints.The control problems are reformulated as mathematical programming problems. It is shown that both the primal and dual optimal variables for these problems are right-differentiable functions of a parameter. The right-derivatives are characterized as solutions to auxiliary quadratic control problems. Conditions of continuous differentiability are discussed, and some estimates of the rate of convergence of the difference quotients to the respective derivatives are given.     

Global and Local Search Algorithms for Concave Cost Transshipment Problems

Traditionally, the minimum cost transshipment problems have been simplified as linear cost problems, which are not practical in real applications. Recently, some advanced local search algorithms have been developed that can directly solve concave cost bipartite network problems. However, they are not applicable to general transshipment problems. Moreover, the effectiveness of these modified local search algorithms for solving general concave cost transshipment problems is doubtful. In this research, we propose a global search algorithm for solving concave cost transshipment problems. Effecient methods for encoding, generating initial populations, selection, crossover and mutation are proposed, according to the problem characteristics. To evaluate the effectiveness of the proposed global search algorithm, four advanced local search algorithms based on the threshold accepting algorithm, the great deluge algorithm, and the tabu search algorithm, are also developed and are used for comparison purpose. To assist with the comparison of the proposed algorithms, a randomized network generator is designed to produce test problems. All the tests are performed on a personal computer. The results indicate that the proposed global search algorithm is more effective than the four advanced local algorithms, for solving concave cost transshipment problems.     

The solution existence of general variational inclusion problems

We propose general variational inclusion problems which are slightly different from corresponding problems considered in several recent papers in the literature and show that they are advantageous. Sufficient conditions for the solution existence are established. As applications we derive consequences for several special cases of variational inclusion problems, quasioptimization problems, equilibrium problems and implicit variational inequalities and show that they improve the results of some recent existing papers.     

Estimates for Solutions to Model Problems Connected with Quasistationary Approximation for the Stefan Problem

Model problems for elliptic equations are considered. The time-derivative of a solution can be contained in the boundary condition or in the conjugation condition. Suich problems appear, for example, in the study of free boundary problems for elliptic equations that can be considered as quasistationary approximations to free boundary problems for parabolic equations. Estimates for solutions to the model problems are obtained. Bibliography: 11 titles.     

Towards global bilevel dynamic optimization

The global solution of bilevel dynamic optimization problems is discussed. An overview of a deterministic algorithm for bilevel programs with nonconvex functions participating is given, followed by a summary of deterministic algorithms for the global solution of optimization problems with nonlinear ordinary differential equations embedded. Improved formulations for scenario-integrated optimization are proposed as bilevel dynamic optimization problems. Solution procedures for some of the problems are given, while for others open challenges are discussed. Illustrative examples are given.     

Necessary optimality conditions for Stackelberg problems

First-order necessary optimality conditions are derived for a class of two-level Stackelberg problems in which the followers' lower-level problems are convex programs with unique solutions. To this purpose, generalized Jacobians of the marginal maps corresponding to followers' problems are estimated. As illustrative examples, two discretized optimum design problems with elliptic variational inequalities are investigated. The theoretical results may be used also for the numerical solution of the Stackelberg problems considered by nondifferentiable optimization methods.Communicated by M. Simaan     

Linear programming in tector criterion markov and semi-Markov decision processes

Optimality problems in infinite horizon, discrete time, vector criterion Markov and semi-Markov decision processes are expressed as standard problems of multiobjective linear programming. Processes with discounting, absorbing processes and completely ergodie processes without discounting are investigated. The common properties and special structure of derived multiobjective linear programming problems are overviewed. Computational simplicities associated with these problems in comparison with general multiobjective linear programming problems are discussed. Methods for solving these problems are overviewed and simple numerical examples are given.     

Sensitivity analysis for multivalued quasiequilibrium problems in metric spaces: Hölder continuity of solutions

Hölder continuity and uniqueness of the solutions of general multivalued vector quasiequilibrium problems in metric spaces are established. The results are shown to be extensions of recent ones for equilibrium problems with some improvements. Applications in quasivariational inequalities, vector quasioptimization and traffic network problems are provided as examples for others in various optimization—related problems.