Application of the finite integral transform method to solving a mixed problem with integro-differential conditions for a nonclassical equation

We consider a mixed problem with integro-differential boundary conditions for a nonclassical equation. Under certain conditions, we apply a finite integral transform to this problem and obtain a parametric problem. We introduce the notion of proper boundary conditions of the parametric problem, which is wider than the notion of regularity. By applying the inverse integral transform to the solution of the parametric problem, we obtain an analytic representation of the solution of the original mixed problem.     

Lipschitz Continuity Results for a Class of Variational Inequalities and Applications: A Geometric Approach

We consider a class of parametric variational inequalities which, under suitable assumptions, admit an equivalent integral formulation. We study the Lipschitz continuity of the solution and treat in detail the case in which the parametric constraint set is a polytope. Finally, the results obtained are applied to the time-dependent traffic equilibrium problem.     

Relations between stochastic and parametric programming for decision problems with a random objective function

In this paper we study the relation between the general concept for an optimal solution for stochastic programming problems with a random objective function-the concept of an £-efficient solution-and the associated parametric problem, We show that it is possible under certain assumptions to obtain some or even all £-efficient solutions of the stochastic problem by solving the parametric problem with respect to a certain parameter set.     

Lower semicontinuity of the solution map to a parametric elliptic optimal control problem with mixed pointwise constraints

This paper studies the solution stability of a parametric optimal control problem governed by single linear elliptic equations with mixed control-state constraints and convex cost functions. By reducing the problem to a parametric programming problem and a parametric variational inequality, we obtain sufficient conditions under which the solution map to an elliptic optimal control problem is lower semicontinuous.     

Mixed finite element methods for the approximation of time-dependent problems

A given elliptic boundary problem can, in general, be approximated by several different mixed finite element methods, depending on what physical unknowns are most desired. The use of certain mixed methods for time-dependent problems has been proposed by Johnson and Thomee [5]. We analyze here some additional mixed methods for the time-dependent case which can be used to obtain direct approximations to alternate physical quantities of interest.     

Parametric versus nonparametric tolerance regions in detection problems

A major problem in statistical quality control is to detect a change in the distribution of independent sequentially observed random vectors. The case of a Gaussian pre-change distribution has been extensively analyzed. Here we are concerned with the non-normal multivariate case. In this setup it is natural to use tolerance regions as detection tools. These regions are defined in terms of density level sets, which can be estimated in a plug-in fashion. Under a normal mixture model we compare, through a simulation study, the performance of such a detection scheme for two density estimators: a (parametric) normal mixture and a (nonparametric) kernel estimator. The problem of the bandwidth choice for the latter is addressed. We also obtain a result concerning the convergence rates of the error probabilities under a general parametric model. Finally, a real data example is discussed.     

Parametric network utility maximization problem

We show how to solve the parametric utility maximization problem with a continuous parameter in a finite number of steps in order to obtain a solution with given accuracy. Also, we propose a new approach for the discretization of time for the parametric utility maximization problem with Lipschitz utility function. Some numerical results are provided.     

State-dependent importance sampling schemes via minimum cross-entropy

We present a method to obtain state- and time-dependent importance sampling estimators by repeatedly solving a minimum cross-entropy (MCE) program as the simulation progresses. This MCE-based approach lends a foundation to the natural notion to stop changing the measure when it is no longer needed. We use this method to obtain a state- and time-dependent estimator for the one-tailed probability of a light-tailed i.i.d. sum that is logarithmically efficient in general and strongly efficient when the jumps are Gaussian. We go on to construct an estimator for the two-tailed problem which is shown to be similarly efficient. We consider minor variants of the algorithm obtained via MCE, and present some numerical comparisons between our algorithms and others from the literature.     

Optimal Design of the Time-Dependent Support of Bang–Bang Type Controls for the Approximate Controllability of the Heat Equation

We consider the nonlinear optimal shape design problem, which consists in minimizing the amplitude of bang–bang type controls for the approximate controllability of a linear heat equation with a bounded potential. The design variable is the time-dependent support of the control. Precisely, we look for the best space–time shape and location of the support of the control among those, which have the same Lebesgue measure. Since the admissibility set for the problem is not convex, we first obtain a well-posed relaxation of the original problem and then use it to derive a descent method for the numerical resolution of the problem. Numerical experiments in 2D suggest that, even for a regular initial datum, a true relaxation phenomenon occurs in this context. Also, we implement a simple algorithm for computing a quasi-optimal domain for the original problem from the optimal solution of its associated relaxed one.     

A Note on Rough Parametric Marcinkiewicz Functions

In this note, we obtain sharp L~p estimates of parametric Marcinkiewicz integral operators. Our result resolves a long standing open problem. Also, we present a class of parametric Marcinkiewicz integral operators that are bounded provided that their kernels belong to the sole space L~1(S~(n-1)).     

Algorithms for constructing controllers simultaneously stabilizing second-order linear plants

We consider the simultaneous stabilization problem for second-order linear scalar stationary plants and obtain an easy-to-verify necessary condition for simultaneous stabilization as well as a sufficient condition with a constructive algorithm for designing a stabilizing controller. The problem of extending a set of simultaneously stabilizable plants is considered as well. To solve these problems, we use an approach based on the consideration of parametric spaces of polynomials and transfer functions and on a method for finding the stability radii of the polynomials.     

The Douglas problem for parametric double integrals

 Let be a parametric variational double integral and γ ⊂ ℝ ⁿ be a system of several distinct Jordan curves. We prove the existence of multiply connected, conformally parametrized minimizers of spanned in γ by solving the Douglas problem for parametric functionals on multiply connected schlicht domains. As a by-product we obtain a simple isoperimetric inequality for multiply connected -minimizers, and we discuss regularity results up to the boundary which follow from corresponding results for the Plateau problem. Received: 19 April 2002 Mathematics Subject Classification (2000): 49J45, 49Q10, 53A07, 53A10     

An inexact proximal point method for solving generalized fractional programs

In this paper, we present several new implementable methods for solving a generalized fractional program with convex data. They are Dinkelbach-type methods where a prox-regularization term is added to avoid the numerical difficulties arising when the solution of the problem is not unique. In these methods, at each iteration a regularized parametric problem is solved inexactly to obtain an approximation of the optimal value of the problem. Since the parametric problem is nonsmooth and convex, we propose to solve it by using a classical bundle method where the parameter is updated after each ‘serious step’. We mainly study two kinds of such steps, and we prove the convergence and the rate of convergence of each of the corresponding methods. Finally, we present some numerical experience to illustrate the behavior of the proposed algorithms, and we discuss the practical efficiency of each one.      

A lie group structure on the space of time-dependent vector fields

In this note we use a banal relation between flows of vector fields, a sort of time-dependent Campbell—Baker—Hausdorff formula, to obtain a non-linear version of the variation of constants formula. We employ this formula to calculate the tangent to the mapping which assigns to each time-dependent vector fieldV with compact support the diffeomorphism _t (V), where _t (V) is the global flow ofV. Afterwards we use these results to give a non-commutative Lie group structure to the space of time-dependent vector fields with compact support. We also treat of the Lie algebra of this group and we calculate the adjoint action and the exponential mapping. The setting is the same of [1] and we refer the reader to this book for notations.     

A diophantine problem concerning cubes

This paper deals with the problem of finding n integers such that their pairwise sums are cubes. We obtain eight integers, expressed in parametric terms, such that all the six pairwise sums of four of these integers are cubes, 9 of the 10 pairwise sums of five of these integers are cubes, 12 pairwise sums of six of these integers are cubes, 15 pairwise sums of seven of these integers are cubes and 18 pairwise sums of all the eight integers are cubes. This leads to infinitely many examples of four positive integers such that all of their six pairwise sums are cubes. Further, for any arbitrary positive integer n, we obtain a set of 2(n+1) integers, in parametric terms, such that 5n+1 of the pairwise sums of these integers are cubes. With a choice of parameters, we can obtain examples with 5n+2 of the pairwise sums being cubes.     

A penalty method for the time-dependent Stokes problem with the slip boundary condition and its finite element approximation

We consider the finite element method for the time-dependent Stokes problem with the slip boundary condition in a smooth domain. To avoid a variational crime of numerical computation, a penalty method is introduced, which also facilitates the numerical implementation. For the continuous problem, the convergence of the penalty method is investigated. Then we study the fully discretized finite element approximations for the penalty method with the P1/P1-stabilization or P1b/P1 element. For the discretization of the penalty term, we propose reduced and non-reduced integration schemes, and obtain an error estimate for velocity and pressure. The theoretical results are verified by numerical experiments.     

Weak aggregating algorithm for the distribution-free perishable inventory problem

We formulate the multiperiod, distribution-free perishable inventory problem as a problem of prediction with expert advice and apply an online learning method (the Weak Aggregating Algorithm) to solve it. We show that the asymptotic average performance of this method is as good as that of any time-dependent stocking rule in a given parametric class.     

Overlapping grids for the diffusion equation

Yiqi Qiu ^{We examine the use of nonmatching, overlapping grids for theapproximate solution of time-dependent diffusion problems withNeumann boundary conditions. This problem arises as a modelof the so-called well test analysis of oil and gas reservoirs,which has geometry modelling requirements that make overlappinggrids particularly suitable. We describe the problem and theoverlapping grid approximation, and then carry out a stabilityand convergence analysis in one space dimension (1D). We showthat for suitable schemes, stability is relatively easy to establishin much more general situations. Convergence is less easy togeneralise, but we demonstrate that 2D approximations appearto have the same convergence behaviour as their 1D counterparts.}     

Using the parametric approach to solve the continuous-time linear fractional max–min problems

A numerical algorithm based on parametric approach is proposed in this paper to solve a class of continuous-time linear fractional max-min programming problems. We shall transform this original problem into a continuous-time non-fractional programming problem, which unfortunately happens to be a continuous-time nonlinear programming problem. In order to tackle this nonlinear problem, we propose the auxiliary problem that will be formulated as a parametric continuous-time linear programming problem. We also introduce a dual problem of this parametric continuous-time linear programming problem in which the weak duality theorem also holds true. We introduce the discrete approximation method to solve the primal and dual pair of parametric continuous-time linear programming problems by using the recurrence method. Finally, we provide two numerical examples to demonstrate the usefulness of this algorithm.     

Exactly solvable models and dynamic quantum systems

Complicated dynamic systems with several degrees of freedom are investigated with the inverse scattering method using an adiabatic approach based on a consistent statement of two adiabatic problems. An algebraic technique based on the parametric inverse problem in an adiabatic representation is developed for reconstructing two-dimensional (time-dependent and time-independent) potentials and the corresponding solutions. The calculated elements of the exchange interaction matrix determine the system of corresponding gauge equations. The main characteristics of the exchange interaction essentially depend on the statement of the parametric inverse problem. Namely, if the parametric problem is specified on the entire axis, then the constraint matrix elements are regular at degeneration points of two levels. The opposite occurs in the case of the radial parametric problem or the parametric problem specified on the semiaxis. The influence of the parametric spectral characteristics of the fast subsystem on the behavior of the slow subsystem is studied. In particular, it is shown that state transitions of a two-level system vanish for a special choice of the normalization functions. Translated from Teoreticheskaya i Matematicheskaya Fizika. Vol. 115, No. 1, pp. 106–131. April, 1998.