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.     

Some fundamental problems of the theory of thermoviscoelasticity

Methods of solving quasistatic problems of the linear theory of thermoviscoelasticity are discussed. Special attention is given to the method of approximations. Modern methods of solving contact problems with a variable boundary and problems with a time-dependent boundary are briefly reviewed. Methods of solving problems with a nonuniform temperature field are outlined. The basic relations of the nonlinear theory of thermoviscoelasticity are given. Its various modifications and simplifications associated with the introduction of fairly general assumptions are examined. Methods of solving problems in certain nonlinear theories are noted. Nonisothermal (coupled) problems of thermoviscoelasticity and questions relating to the general theory with physical and geometric nonlinearity are discussed.Lomonosov Moscow State University. Translated from Mekhanika Polimerov, No. 1, pp. 41–58, January–February, 1971.     

基于服装舒适性的纺织材料设计反问题

纺织材料设计反问题是数学物理反问题的一个新领域,也被称为应用数学与计算数学的一个分支.综述纺织材料设计反问题的来源、数学归结,并基于服装的热湿舒适性、压力舒适性提出了设计反问题,给出了反问题解的定义,综述了求解纺织材料设计反问题的数值算法,列举了若干具有挑战的研究课题.     

Apply a novel evolutionary algorithm to the solution of parameter selection problems

In this study, a modified line-up competition algorithm (LCA) is used to solve parameter selection problems. The so-called parameter selection problems contain parameter identification problems and optimal control problems. Once the later problems are transformed by control parametrization, the parameters embedded in both problems are selected by the proposed method under the framework of integration approach. Two parameter identification problems and one optimal control problem are given to demonstrate the use of LCA. The results show that in addition to being insensitive to the initial conditions, LCA is very efficient in solving highly nonlinear parameter selection problems.     

A class of linear evasion problems

A special class of linear evasion problems is discussed. It turns out that the evasion problems are more difficult than pursuit problems in that evader has to prevent capture on an infinite interval of time. Some of the basic facts and difficulties inherent to evasion problems are pointed out.     

一类非线性演化方程初值问题的幂级数解

研究了一类非线性演化方程初值问题.通过不变子空间方法,这类初值问题被约化为常微分方程组的初值问题.这类初值问题是适定的.本文给出了这类初值问题关于时间变量t的幂级数解.     

Analysis of unbonded contact problems by means of quadratic programming

Two-body, elastic, unbonded contact problems are formulated as quadratic programming problems. Uniqueness theorems of quadratic programming theory are applied to show that the solution of a contact problem, if one exists, is unique and can be readily found by the modified simplex method of quadratic programming. A solution technique that is compatible with finite-element methods is developed, so that contact problems with complex boundary configurations can be routinely solved. A number of classical and nonclassical problems are solved. Good agreement is found for problems with previously known solutions.     

An asymptotic initial value method for second order singular perturbation problems of convection-diffusion type with a discontinuous source term

In this paper a numerical method is presented to solve singularly perturbed two points boundary value problems for second order ordinary differential equations consisting a discontinuous source term. First, in this method, an asymptotic expansion approximation of the solution of the boundary value problem is constructed using the basic ideas of a well known perturbation method WKB. Then some initial value problems and terminal value problems are constructed such that their solutions are the terms of this asymptotic expansion. These initial value problems are happened to be singularly perturbed problems and therefore fitted mesh method (Shishkin mesh) are used to solve these problems. Necessary error estimates are derived and examples provided to illustrate the method.     

空间轴对称问题边界元法的程序处理

弹性力学的空间轴对称问题可以化为两个变量(r,z)的二维问题求解,但又比平面问题略复杂些.在轴对称问题边界元的程序处理上也会相应带来些麻烦.文章具体介绍了作者在调试轴对称问题边界元程序中遇到的一些问题及处理方法,并给出数值结果加以验证.     

组合拓扑方法在组合学和图论中的应用

本文介绍组合拓扑方法在图论和组合学中的应用，探索一些新的离散问题和连续问题的关系，介绍目前有关这方面的新结果及发展动向。本文主要介绍同调理论在图论中的应用，与图有关的复形及性质，不动点定理在离散问题中的应用等。文中提出了一些新结果及可供研究的新问题。     

Identification of distributed systems and the theory of the regularization

The identification problems, i.e., the problems of finding unknown parameters in distributed systems from the observations are very important in modern control theory. The solutions of these identification problems can be obtained by solving the equations of the first kind. However, the solutions are often unstable. In other words, they are not continuously dependent on the data. The regularization or Tihonov's regularization is known as one of the stabilizing algorithms to solve these non well-posed problems. In this paper is studied the regularization method for identification of distributed systems. Several approximation theorems are proved to solve the equations of the first kind. Then, identification problems are reduced to the minimization of quadratic cost functionals by virtue of these theorems. On the other hand, it is known that the statistical methods for identification such as the maximum likelihood lead to the minimization problems of certain quadratic functionals. Comparing these quadratic cost functionals, the relations between the regularization and the statistical methods are discussed. Further, numerical examples are given to show the effectiveness of this method.     

On the complexity of some data analysis problems

NP-completeness of certain discrete optimization problems is proved. These are the problems to which one can reduce some important problems arising in data analysis when certain subsets of vectors are sought.     

Reducibility of bilevel programming problems to vector optimization problems

Reductions are studied of the bilevel programming problems to vector (multicriteria) optimization problems. A general framework is proposed for constructing these reductions. Some particular cases of bilevel problems are considered.     

Solution Sets of Quadratic Complementarity Problems

In this paper, we study quadratic complementarity problems, which form a subclass of nonlinear complementarity problems with the nonlinear functions being quadratic polynomial mappings. Quadratic complementarity problems serve as an important bridge linking linear complementarity problems and nonlinear complementarity problems. Various properties on the solution set for a quadratic complementarity problem, including existence, compactness and uniqueness, are studied. Several results are established from assumptions given in terms of the comprising matrices of the underlying tensor, henceforth easily checkable. Examples are given to demonstrate that the results improve or generalize the corresponding quadratic complementarity problem counterparts of the well-known nonlinear complementarity problem theory and broaden the boundary knowledge of nonlinear complementarity problems as well.     

A critical review of discrete filled function methods in solving nonlinear discrete optimization problems

Many real life problems can be modeled as nonlinear discrete optimization problems. Such problems often have multiple local minima and thus require global optimization methods. Due to high complexity of these problems, heuristic based global optimization techniques are usually required when solving large scale discrete optimization or mixed discrete optimization problems. One of the more recent global optimization tools is known as the discrete filled function method. Nine variations of the discrete filled function method in literature are identified and a review on theoretical properties of each method is given. Some of the most promising filled functions are tested on various benchmark problems. Numerical results are given for comparison.     

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.     

Perspectives on practical aspects of truck routing and scheduling

Truck routing and scheduling problems are differentiated from other vehicle routing and scheduling problems and a classification scheme for the former ones is outlined. Many characteristics of practical truck routing and scheduling problems are listed and several aspects are discussed, among them are: soft constraints, demand variability, multiple objectives, complex cost functions, and alternate solution approaches with their potential for solving practical problems. It is suggested that cost-based interactive heuristics coupled with graphical presentation of solutions may be the right method to deal with the more complex practical problems. Some basic generic heuristics are suggested and important software design and acquisition considerations are presented.     

Dependence of Eigenvalues of Certain Closely Discrete Sturm-Liouville Problems

This paper is concerned with dependence of eigenvalues of certain closely discrete Sturm-Liouville problems. Topologies and geometric structures on various spaces of such problems are firstly introduced. Then, relationships between the analytic and geometric multiplicities of an eigenvalue are discussed. It is shown that all problems sufficiently close to a given problem have eigenvalues near each eigenvalue of the given problem. So, all the simple eigenvalues live in so-called continuous simple eigenvalue branches over the space of problems, and all the eigenvalues live in continuous eigenvalue branches over the space of self-adjoint problems. The analyticity, differentiability and monotonicity of continuous eigenvalue branches are further studied.     

Carleman estimates for the regularization of ill-posed Cauchy problems

This work is a survey of results for ill-posed Cauchy problems for PDEs of the author with co-authors starting from 1991. A universal method of the regularization of these problems is presented here. Even though the idea of this method was previously discussed for specific problems, a universal approach of this paper was not discussed, at least in detail. This approach consists in constructing of such Tikhonov functionals which are generated by unbounded linear operators of those PDEs. The approach is quite general one, since it is applicable to all PDE operators for which Carleman estimates are valid. Three main types of operators of the second order are among them: elliptic, parabolic and hyperbolic ones. The key idea is that convergence rates of minimizers are established using Carleman estimates. Generalizations to nonlinear inverse problems, such as problems of reconstructions of obstacles and coefficient inverse problems are also feasible.     

Some Methods of Producing Approximate Solutions to Travelling Salesman Problems with Hundreds or Thousands of Cities

Many large practical combinatorial problems await methods of solution, especially those involving the scheduling of hundreds or thousands of activities. The travelling salesman problem is archetypal and has attracted much attention, yet published rigorous methods can only be applied to problems encompassing tens of cities and approximate methods appear only to have been applied to problems of up to 105 cities. None of these methods offers scope for extension to much larger problems because of rapidly increasing computing requirements.Some approximate, sequential methods and the results of applying them to thirty problems of between 20 and 500 cities are described. In addition, the results of applying one method to ten 2500 city problems are reported; the solutions produced were, on average, 1·28 times the corresponding lower bound. It appears that satisfactory solutions to some large practical problems may be obtained by developing suitable sequential methods.