The principles of correspondence between static boundary value problems of thermoviscoelasticity and thermoelasticity

Principles of correspondence between static boundary value problems of thermoviscoelasticity and thermoelasticity are proposed. This class of problems of the inhomogeneous non-linear anisotropic theory of thermoviscoelasticity is reduced by integral transformations to the corresponding class of thermoelasticity problems.     

NP-completeness of some problems of choosing a vector subset

The NP-completeness is proved of some problems of choosing a Euclidean vector subset. One of the data analysis problems is reduced to these problems. The required subset is assumed to have a fixed cardinality and include the vectors that are “close” to each other by the criterium of the minimum sum of squares of distances.     

Plane potential flow past a cylinder with porous surface

In the paper two models for the potential flow past a cylinder with porous or perforated surface are reduced to nonlinear Riemann-Hilbert problems for the complex velocity function and general existence and uniqueness theorems for the solution of the problems are derived. Further the problems are reduced to nonlinear singular integral equations of Hilbert type whose solvability is investigated by means of the Schauder and Banach fixed point theorem.     

Perturbation theory for mathematical programming problems

Mathematical programming (MP) problems depending on a small parameter are investigated. Attention is paid to the cases where the solutions to the reduced program and/or the solutions to the dual reduced program are not unique. Conditions are given for the convergence of perturbed solutions to a point of the reduced problem solution set, if the small parameter tends to zero. It is shown how to find this point and how to construct an approximate solution to the perturbed program. A singular situation may appear if the dual solution set is unbounded. In this case, a gap between perturbed and reduced solutions may arise. However, it is shown that the perturbed solutions are close to the solutions of some modified reduced problem. The practical usefulness of perturbation theory is demonstrated by considering the two LP problems. Decomposition and aggregation procedures are constructed on the base of general results to find suboptimal solutions of these problems.     

Initial-value technique for self-adjoint singular perturbation boundary value problems

We have developed an initial-value technique for self-adjoint singularly perturbed two-point boundary value problems. The original problem is reduced to its normal form, and the reduced problem is converted into first-order initial-value problems. These initial-value problems are solved by the cubic spline method. Numerical illustrations are given at the end to demonstrate the efficiency of our method. Graphs are also depicted in support of the results. An erratum to this article can be found at     

A reduced MFE formulation based on POD for the non-stationary conduction-convection problems

In this article, a reduced mixed finite element (MFE) formulation based on proper orthogonal decomposition (POD) for the non-stationary conduction-convection problems is presented. Also the error estimates between the reduced MFE solutions based on POD and usual MFE solutions are derived. It is shown by numerical examples that the results of numerical computation are consistent with theoretical conclusions. Moreover, it is shown that the reduced MFE formulation based on POD is feasible and efficient in finding numerical solutions for the non-stationary conduction-convection problems.     

Trigonometric Tension B-Spline Method for the Solution of Problems in Calculus of Variations

In this paper, the tension B-spline collocation method is used for finding the solution of boundary value problems which arise from the problems of calculus of variations. The problems are reduced to an explicit system of algebraic equations by this approximation. We apply some numerical examples to illustrate the accuracy and implementation of the method.     

A class of singularly perturbed,nonlinear, fixed-endpoint control problems

Singular perturbation techniques are applied to a class of nonlinear, fixed-endpoint control problems to decompose the full-order problem into three lower-order problems, namely, the reduced problem and the left and right boundary-layer problems. The boundary-layer problems are linear-quadratic and, contrary to previous singular perturbation works, the reduced problem has a simple formulation. The solutions of these lower-order problems are combined to yield an approximate solution to the full nonlinear problem. Based on the properties of the lower-order problems, the full problem is shown to possess an asymptotic series solution.This work was supported in part by the National Science Foundation under Grant No. ENG-47-20091 and in part by the US Air Force under Grant No. AFOSR-73-2570.The author acknowledges the helpful suggestions of Professor P. V. Kokotovic, University of Illinois, Urbana, Illinois.     

The Reduced Module of the Complex Sphere

The paper continues studies of reduced modules of open sets. A notion of reduced module of the complex sphere is introduced, a formula for this module is obtained, and a number of its properties are proved. Applications of the reduced module of the sphere to various problems in geometric function theory are given. Bibliography: 12 titles.     

Minimizing Quadratic Functions Subject to Bound Constraints with the Rate of Convergence and Finite Termination

A new active set based algorithm is proposed that uses the conjugate gradient method to explore the face of the feasible region defined by the current iterate and the reduced gradient projection with the fixed steplength to expand the active set. The precision of approximate solutions of the auxiliary unconstrained problems is controlled by the norm of violation of the Karush-Kuhn-Tucker conditions at active constraints and the scalar product of the reduced gradient with the reduced gradient projection. The modifications were exploited to find the rate of convergence in terms of the spectral condition number of the Hessian matrix, to prove its finite termination property even for problems whose solution does not satisfy the strict complementarity condition, and to avoid any backtracking at the cost of evaluation of an upper bound for the spectral radius of the Hessian matrix. The performance of the algorithm is illustrated on solution of the inner obstacle problems. The result is an important ingredient in development of scalable algorithms for numerical solution of elliptic variational inequalities.     

Singularly Perturbed Nonlinear Boundary-Value Problems Whose Reduced Equations Have Singular Points

Using results on implicit first-order differential equations, the existence and the asymptotic behavior of solutions of singularly perturbed second-order boundary-value problems whose reduced equations have singular points are studied. The variety of possible nonuniform behavior is investigated by means of a stability analysis of the reduced solutions and is illustrated with several model problems which are canonical in terms of the first-order singular-point theory.     

A new local reduced basis discontinuous Galerkin approach for heterogeneous multiscale problems

Inspired by the reduced basis approach and modern numerical multiscale methods, we present a new framework for an efficient treatment of heterogeneous multiscale problems. The new approach is based on the idea of considering heterogeneous multiscale problems as parametrized partial differential equations where the parameters are smooth functions. We then construct, in an offline phase, a suitable localized reduced basis that is used in an online phase to efficiently compute approximations of the multiscale problem by means of a discontinuous Galerkin method on a coarse grid. We present our approach for elliptic multiscale problems and discuss an a posteriori error estimate that can be used in the construction process of the localized reduced basis. Numerical experiments are given to demonstrate the efficiency of the new approach.     

Lagrangian bounds in multiextremal polynomial and discrete optimization problems

Many polynomial and discrete optimization problems can be reduced to multiextremal quadratic type models of nonlinear programming. For solving these problems one may use Lagrangian bounds in combination with branch and bound techniques. The Lagrangian bounds may be improved for some important examples by adding in a model the so-called superfluous quadratic constraints which modify Lagrangian bounds. Problems of finding Lagrangian bounds as a rule can be reduced to minimization of nonsmooth convex functions and may be successively solved by modern methods of nondifferentiable optimization. This approach is illustrated by examples of solving polynomial-type problems and some discrete optimization problems on graphs.     

A reduction technique for weighted grouping problems

Weighted grouping problems are shown to have an equivalent reduced form, which is often considerably smaller than the original problem. Although the reduction may be small for randomly generated problems, real-life problems often contain non-random properties that greatly increase the effect of reduction. We give an efficient algorithm to build the reduced problem instance, and analyse the expected amount of reduction for certain statistical distributions and real-life data. In addition, we briefly discuss the effect of reduction on traditional solving methods of the grouping problem. The results show clearly the usefulness of problem reduction: it is computationally cheap to apply and may make the reduced problem solvable in a practical time whilst the original one is not. The method is readily applicable to the job grouping problem of printed circuit board (PCB) printing industry.     

Augmented Lagrangian Homotopy Method for the Regularization of Total Variation Denoising Problems

This paper presents a homotopy procedure which improves the solvability of mathematical programming problems arising from total variational methods for image denoising. The homotopy on the regularization parameter involves solving a sequence of equality-constrained optimization problems where the positive regularization parameter in each optimization problem is initially large and is reduced to zero. Newton’s method is used to solve the optimization problems and numerical results are presented.     

一类非线性椭圆型方程奇摄动问题

A class of singularly perturbed problems for the nonlinear elliptic equations is considered. Under suitable conditions, using the theory of differential inequalities the asymptotic behavior of solution for the boundary value problems are studied, which reduced equations possess two intersecting solutions.     

On the Solution of Inverse Problems for Generalized Oxygen Consumption

We present the solution of some inverse problems for one-dimensional free boundary problems of oxygen consumption type, with a semilinear convection-diffusion-reaction parabolic equation. Using a fixed domain transformation (Landau's transformation) the direct problem is reduced to a system of ODEs. To minimize the objective functionals in the inverse problems, we approximate the data by a finite number of parameters with respect to which automatic differentiation is applied.     

Complexity of vector optimization problems on graphs

The paper is dedicated to the computation complexity of multi-objective optimization problems on graphs. The classes of multi-objective problems with polynomial complexity or being polynomially reduced to be NP-hard are marked out. The unsolvability of a series of combinatorial multi-objective problems has been set up by means of linear convolution algorithm. The sufficient conditions under which these algorithms are statistically efficient have also been obtained.     

On the solution of some max-min problems

A random search-type method for finding max-min of multivariable functions is suggested. The solution of such problems is reduced to the construction, on the basis of random tests, of certain regression curves and to the determination of their roots. One-stage and multistage max-min problems are considered. Various modifications of the method are given.