The method of mechanical quadratures for integral equations with fixed singularity

We investigate the method of mechanical quadratures for integral equations with fixed singularity. We establish estimates of the error of this method based on a quadrature process, which is the best in the class of differentiable functions. We prove the convergence of the method in finite-dimensional and uniform metrics. We find that the investigated quadrature method is optimal by order on the Hölder class of functions.     

A domain decomposition method based on the iterative operator splitting method

In this article a new approach is proposed for constructing a domain decomposition method based on the iterative operator splitting method. The convergence properties of such a method are studied. The main feature of the proposed idea is the decoupling of space and time. We present a multi-iterative operator splitting method that combines iteratively the space and time splitting. We confirm with numerical applications the effectiveness of the proposed iterative operator splitting method in comparison with the classical Schwarz waveform relaxation method as a standard method for domain decomposition. We provide improved results and convergence rates.     

On the limited memory BFGS method for large scale optimization

We study the numerical performance of a limited memory quasi-Newton method for large scale optimization, which we call the L-BFGS method. We compare its performance with that of the method developed by Buckley and LeNir (1985), which combines cycles of BFGS steps and conjugate direction steps. Our numerical tests indicate that the L-BFGS method is faster than the method of Buckley and LeNir, and is better able to use additional storage to accelerate convergence. We show that the L-BFGS method can be greatly accelerated by means of a simple scaling. We then compare the L-BFGS method with the partitioned quasi-Newton method of Griewank and Toint (1982a). The results show that, for some problems, the partitioned quasi-Newton method is clearly superior to the L-BFGS method. However we find that for other problems the L-BFGS method is very competitive due to its low iteration cost. We also study the convergence properties of the L-BFGS method, and prove global convergence on uniformly convex problems.This work was supported by the Applied Mathematical Sciences subprogram of the Office of Energy Research, U.S. Department of Energy, under contract DE-FG02-87ER25047, and by National Science Foundation Grant No. DCR-86-02071.     

On a numerical solution of the Cauchy problem for the Laplace equation by the fundamental solutions method

We discuss a numerical method to solve a Cauchy problem for the Laplace equation in the two-dimensional annular domain. We consider the case that the Cauchy data is given on an arc. We develop an approximation method based of the fundamental solutions method using the least squares method with Tikhonov regularization. The effectiveness of our method is examined by a numerical experiment. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Missing boundary data recovery using Nash games: the Stokes system

We consider the Cauchy-Stokes problem. We use a new method based on Nash game theory to recover the missing velocity and normal stress on some inaccessible part of the boundary. This method is used with two different approaches. The first one is compared to a control type one. The numerical study attests that both approaches give accurate results. We compare these results with those of the energy-like minimization method.     

A nonstandard difference-integral method for the viscous Burgers’ equation

We develop a nonstandard difference-integral method based on a nonstandard finite difference method coupled with a CE–SE scheme. We use the viscous Burgers’ equation with preestablished conditions as a benchmark for testing our method. Numerical results obtained show that this new method is more robust and efficient than the associated standard difference-integral method.     

On possibility of obtaining linear accuracy evaluation of approximate solutions to inverse problems

We consider a concept of linear a priori estimate of the accuracy for approximate solutions to inverse problems with perturbed data. We establish that if the linear estimate is valid for a method of solving the inverse problem, then the inverse problem is well-posed according to Tikhonov. We also find conditions, which ensure the converse for the method of solving the inverse problem independent on the error levels of data. This method is well-known method of quasi-solutions by V. K. Ivanov. It provides for well-posed (according to Tikhonov) inverse problems the existence of linear estimates. If the error levels of data are known, a method of solving well-posed according to Tikhonov inverse problems is proposed. This method called the residual method on the correctness set (RMCS) ensures linear estimates for approximate solutions. We give an algorithm for finding linear estimates in the RMCS.     

B-spline solution of a singularly perturbed boundary value problem arising in biology

We use B-spline functions to develop a numerical method for solving a singularly perturbed boundary value problem associated with biology science. We use B-spline collocation method, which leads to a tridiagonal linear system. The accuracy of the proposed method is demonstrated by test problems. The numerical result is found in good agreement with exact solution.     

Sufficient descent directions in unconstrained optimization

Descent property is very important for an iterative method to be globally convergent. In this paper, we propose a way to construct sufficient descent directions for unconstrained optimization. We then apply the technique to derive a PSB (Powell-Symmetric-Broyden) based method. The PSB based method locally reduces to the standard PSB method with unit steplength. Under appropriate conditions, we show that the PSB based method with Armijo line search or Wolfe line search is globally and superlinearly convergent for uniformly convex problems. We also do some numerical experiments. The results show that the PSB based method is competitive with the standard BFGS method.     

Hybrid Newton-Type Method for a Class of Semismooth Equations

In this paper, we present a hybrid method for the solution of a class of composite semismooth equations encountered frequently in applications. The method is obtained by combining a generalized finite-difference Newton method to an inexpensive direct search method. We prove that, under standard assumptions, the method is globally convergent with a local rate of convergence which is superlinear or quadratic. We report also several numerical results obtained applying the method to suitable reformulations of well-known nonlinear complementarity problems.     

A Simple Structural Analysis Method for DAEs

We describe a straightforward method for analysing the structure of a differential-algebraic system. It generalizes the method of Pantelides, but is more directly informative and applies to DAEs with derivatives of any order. It naturally leads to a numerical method for the initial value problem that combines projection and index reduction. We illustrate the method by examples, and justify it with proofs. We prove that it succeeds on a fairly wide class of systems encountered in practice, and show its relation to the Pantelides method and to the Campbell-Gear derivative-array equations.This revised version was published online in October 2005 with corrections to the Cover Date.     

Adaptive discontinuous Galerkin methods in multiwavelets bases

We use a multiwavelet basis with the Discontinuous Galerkin (DG) method to produce a multi-scale DG method. We apply this Multiwavelet DG method to convection and convection-diffusion problems in multiple dimensions. Merging the DG method with multiwavelets allows the adaptivity in the DG method to be resolved through manipulation of multiwavelet coefficients rather than grid manipulation. Additionally, the Multiwavelet DG method is tested on non-linear equations in one dimension and on the cubed sphere.     

A convergence criterion for Secant method with approximate zeros

We estimate the speed of convergence of Secant method in one variable and multivariable case with a constant from the coefficients of Taylor series. We present a criterion to confirm thatz is close enough to a zero for Secant method and compare with that of Newton method.     

Three methods for two‐sided bounds of eigenvalues—A comparison

We compare three finite element‐based methods designed for two‐sided bounds of eigenvalues of symmetric elliptic second order operators. The first method is known as the Lehmann–Goerisch method. The second method is based on Crouzeix–Raviart nonconforming finite element method. The third one is a combination of generalized Weinstein and Kato bounds with complementarity‐based estimators. We concisely describe these methods and use them to solve three numerical examples. We compare their accuracy, computational performance, and generality in both the lowest and higher order case.     

Clustering Categorical Data via Ensembling Dissimilarity Matrices

We present a technique for clustering categorical data by generating many dissimilarity matrices and combining them. We begin by demonstrating our technique on low-dimensional categorical data and comparing it to several other techniques that have been proposed. We show through simulations and examples that our method is both more accurate and more stable. Then we give conditions under which our method should yield good results in general. Our method extends to high-dimensional categorical data of equal lengths by ensembling over many choices of explanatory variables. In this context, we compare our method with two other methods. Finally, we extend our method to high-dimensional categorical data vectors of unequal length by using alignment techniques to equalize the lengths. We give an example to show that our method continues to provide useful results, in particular, providing a comparison with phylogenetic trees. Supplementary material for this article is available online.     

Numerical conformal mapping of multiply connected domains to regions with circular boundaries

We propose a method to map a multiply connected bounded planar region conformally to a bounded region with circular boundaries. The norm of the derivative of such a conformal map satisfies the Laplace equation with a nonlinear Neumann type boundary condition. We analyze the singular behavior at corners of the boundary and separate the major singular part. The remaining smooth part solves a variational problem which is easy to discretize. We use a finite element method and a gradient descent method to find an approximate solution. The conformal map is then constructed from this norm function. We tested our algorithm on a polygonal region and a curvilinear smooth region.     

A heuristic method for RCPSP with fuzzy activity times

In this paper, we propose a heuristic method for resource constrained project scheduling problem with fuzzy activity times. This method is based on priority rule for parallel schedule generation scheme. Calculation of critical path in this case requires comparison of fuzzy numbers. Distance based ranking of fuzzy number is used for finding the critical path length and concept of shifting criticality is proposed for some of the special cases. We also propose a measure for finding the non-integer power of a fuzzy number. We discuss some properties of the proposed method. We use an example to illustrate the method.     

On a Newton-Moser type method

We prove that a variant of Moser's iterative method for solving nonlinear equations is quadratically convergent and give error bounds. We estimate the amount of arithmetic for the method and compare it to Newton's method. Finally we use the method to solve a problem with small divisors.     

Convergence properties of the cross-entropy method for discrete optimization

We present new theoretical convergence results on the cross-entropy (CE) method for discrete optimization. We show that a popular implementation of the method converges, and finds an optimal solution with probability arbitrarily close to 1. We also give conditions under which an optimal solution is generated eventually with probability 1.     

Recurrence Method for Solving Singularly Perturbed Boundary Value Problems

We base on Taylor series expansions to construct the numerical method for solving singularly perturbed boundary value problems. We use the trapezoid method to approximate the integrals and obtain three‐term recurrence relationship. The efficiency of the proposed method is demonstrated by test problems. The numerical result is found in a good agreement with exact solution.