An Approximation Scheme for Uncertain Minimax Optimal Control Problems

In this work, we address an uncertain minimax optimal control problem with linear dynamics where the objective functional is the expected value of the supremum of the running cost over a time interval. By taking an independently drawn random sample, the expected value function is approximated by the corresponding sample average function. We study the epi-convergence of the approximated objective functionals as well as the convergence of their global minimizers. Then we define an Euler discretization in time of the sample average problem and prove that the value of the discrete time problem converges to the value of the sample average approximation. In addition, we show that there exists a sequence of discrete problems such that the accumulation points of their minimizers are optimal solutions of the original problem. Finally, we propose a convergent descent method to solve the discrete time problem, and show some preliminary numerical results for two simple examples.     

An Asymptotic Expansion for Probabilities of Moderate Deviations for Multivariate Martingales

We derive formulae for probabilities of large deviations in a moderate range for multivariate martingales. Although we give an elementary proof for univariate martingales, there is no elementary extension to the multivariate case. The hard point is to produce a proper estimate for the norming factor. For this we develop a method of sequential projectors which allows us to obtain the desired natural extension of the result in the univariate case.     

A Multigrid Scheme for Elliptic Constrained Optimal Control Problems

A multigrid scheme for the solution of constrained optimal control problems discretized by finite differences is presented. This scheme is based on a new relaxation procedure that satisfies the given constraints pointwise on the computational grid. In applications, the cases of distributed and boundary control problems with box constraints are considered. The efficient and robust computational performance of the present multigrid scheme allows to investigate bang-bang control problems.AMS Subject Classification: 49J20, 65N06, 65N12, 65N55Supported in part by the SFB 03 “Optimization and Control”     

An Asymptotic Expansion of the Double Gamma Function

The Barnes double gamma function G(z) is considered for large argument z. A new integral representation is obtained for log G(z). An asymptotic expansion in decreasing powers of z and uniformly valid for |Arg z|<π is derived from this integral. The expansion is accompanied by an error bound at any order of the approximation. Numerical experiments show that this bound is very accurate for real z. The accuracy of the error bound decreases for increasing Arg z.     

Asymptotic Analysis of State Constrained Semilinear Optimal Control Problems

The asymptotic behavior of state-constrained semilinear optimal control problems for distributed-parameter systems with variable compact control zones is investigated. We derive conditions under which the limiting problems can be made explicit. We gratefully acknowledge the support of the DAAD. The paper was prepared during the visit of the first author at the Institute of Applied Mathematics II, University Erlangen-Nuremberg in 2003.     

A FEM-Multigrid Scheme for Elliptic Nash-Equilibrium Multiobjective Optimal Control Problems

A finite-element multigrid scheme for elliptic Nash-equilibrium multiobjective optimal control problems with control constraints is investigated. The multigrid computational framework implements a nonlinear multigrid strategy with collective smoothing for solving the multiobjective optimality system discretized with finite elements. Error estimates for the optimal solution and two-grid local Fourier analysis of the multigrid scheme are presented. Results of numerical experiments are presented to demonstrate the effectiveness of the proposed framework.     

An Asymptotic Expansion for the Distribution of Hotelling'sT-Statistic under Nonnormality

In this paper we obtain an asymptotic expansion for the distribution of Hotelling'sT²-statisticT²under nonnormality when the sample size is large. In the derivation we find an explicit Edgeworth expansion of the multivariatet-statistic. Our method is to use the Edgeworth expansion and to expand the characteristic function ofT².     

Asymptotic Expansion of Solutions to Singular Perturbation Problems in Critical Cases

This paper investigates the problem of singular perturbed integral initial values and Robin boundary values in the critical case. Based on the boundary layer function method, we not only construct the asymptotic approximation of the original equation, but also prove the uniform validity of the asymptotic solution by successive approximation. At the same time, we give an example to prove the validity of the theoretical results.     

An Infinite Asymptotic Expansion for the Extreme Zeros of the Pollaczek Polynomials

In this paper, we first establish an integral expression for the Pollaczek polynomials P_n ( x ; a , b ) from a generating function. By applying a canonical transformation to the integral and carrying out a detailed analysis of the integrand, we derive a uniform asymptotic expansion for P_n (cosθ; a , b ) in terms of the Airy function and its derivative, in descending powers of n . The uniformity is in an interval next to the turning point , with M being a constant. The coefficients of the expansion are analytic functions of a parameter that depends only on t where , and not on the large parameter n . From the expansion of the polynomials we obtain an asymptotic expansion in powers of n ^−1/3 for the largest zeros. As a special case, a four-term approximation is provided for comparison and illustration. The method used in this paper seems to be applicable to more general situations.     

均值-方差准则下的多期最优保险投资(英文)

近年来,最优保险投资问题吸引了越来越多的注意。一般这个问题是在连续时间框架下来研究的。本文针对这一问题建立离散时间的最优控制模型。应用动态规划原理求解模型对应的近似问题,得到了最优投资策略和投资有效边界的解析表达形式。本文得到的最优投资策略和投资有效边界均依赖于承保参数。通过数值例子分析了承保参数对最优投资策略和有效边界的影响。     

An Optimal Multisecret Threshold Scheme Construction

A multisecret threshold scheme is a system which protects a number of secret keys among a group of n participants. There is a secret s_K associated with every subset K of k participants such that any t participants in K can reconstruct the secret s_K, but a subset of w participants cannot get any information about a secret they are not associated with. This paper gives a construction for the parameters t = 2, k = 3 and for any n and w that is optimal in the sense that participants hold the minimal amount of information. Communicated by: P. Wild     

Complete Asymptotic Expansion for Generalized Favard Operators

In the present paper we consider a generalization _boxclose F_{n,\sigma_{n}} of the Favard operators and study the local rate of convergence for smooth functions. As a main result we derive the complete asymptotic expansion for the sequence ( F_n,snf)( x)( F_{n,\sigma _{n}}f)( x) as n tends to infinity. Furthermore, we consider a truncated version of these operators. Finally, all results were proved for simultaneous approximation.     

Capital Investment — An Optimal Control Perspective

Many managers appear to have a mental model of how investment decisions should be carried out. This paper attempts to identify some of the characteristics of such a mental model by constructing an optimal control model of the process of authorizing an investment project. The key activities in the model are design, support generation and authorization. It is assumed that the effort that can be expended on each is limited. The objective function is the net present value of the cash flows associated with the project. The solution to the model is readily interpreted qualitatively. For viable projects, four different patterns of decision-making are found, each of which is optimum under appropriate circumstances. It is argued that in many actual investment decisions it should be possible for managers to approximate reasonably closely the optimal behaviour, and that therefore the optimal control model may shed light on managers' mental model.     

An Optimal Congestion and Cost-sharing Pricing Scheme for Multiclass Services

We study in this paper a social welfare optimal congestion-pricing scheme for multiclass queuing services which can be applied to telecommunication networks. Most of the literature has focused on the marginal price. Unfortunately, it does not share the total cost among the different classes. We investigate here an optimal Aumann–Shapley congestion-price which verifies this property. We extend the work on the Aumann–Shapley price for priority services, based on the results on the marginal price: instead of just determining the cost repartition among classes for given rates, we obtain the rates and charges that optimize the social welfare.     

Asymptotic Expansion for the Derivative of Finite Elements

It is proved in this paper that there exists an expansion for the derivative of the linear finite element approximation to a model Dirichlet problem in a polygonal domain with a piecewise uniform triangulation.     

关于伽马函数的不等式与渐近展开式

给出伽马函数的一个渐近展开式.基于获得的结果,我们建立了伽马函数的不等式.     

关于Euler-Mascheroni常数的不等式与渐近展开式（英文）

给出一个递推关系式来确定调和数的渐近展开式的系数.我们建立了Euler-Mascheroni常数的不等式.     

图形的同调类中封闭图形数量的渐近估计

In this paper we give an asymptotic expansion including error terms for the number of cycles in homology classes for connected graphs.Mainly,we obtain formulae about the coefficients of error terms which depend on the homology classes and give two examples of how to calculate the coefficient of first error term.     

图形的同调类中封闭图形数量的渐近估计

我们将给出连通图形的同调类中封闭图形数量的渐近表达式并给出误差项的系数的表达式.两特例显示如何计算误差项的系数.