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A new algorithm for generating derangements based on a well known permutation generation method is presented and analysed. The algorithm is shown to be superior in storage and time requirements to the existing method.

In this paper, we propose a 2-step trust region indefinite dogleg path method for the solution of nonlinear equality constrained optimization problems. The method is a globally convergent modification of the locally convergent Fontecilla method and an indefinite dogleg path method is proposed to get approximate solutions of quadratic programming subproblems even if the Hessian in the model is indefinite. The dogleg paths lie in the null space of the Jacobian matrix of the constraints. An ℓ1 exact penalty function is used in the method to determine if a trial point is accepted. The global convergence and the local two-step superlinear convergence rate are proved. Some numerical results are presented.

For time dependent problems, the Schwarz waveform relaxation (SWR) algorithm can be analyzed both at the continuous and semi-discrete level. For consistent space discretizations, one would naturally expect that the semi-discrete algorithm performs as predicted by the continuous analysis. We show in this paper for the reaction diffusion equation that this is not always the case. We consider two space discretization methods—the 2nd-order central finite difference method and the 4th-order compact finite difference method, and for each method we show that the semi-discrete SWR algorithm with Dirichlet transmission condition performs as predicted by the continuous analysis. However, for Robin transmission condition the semi-discrete SWR algorithm performs worse than predicted by the continuous analysis. For each type of transmission conditions, we show that the convergence factors of the semi-discrete SWR algorithm using the two space discretization methods are (almost) equal. Numerical results are presented to validate our conclusions.

Systems of ordinary differential equations obtained by using splitting-up techniques in some air pollution models and a pseudospectral (Fourier) discretization of the first-order space derivatives are considered. The application of a fairly general class of predictor-corrector (PC) schemes in the time-discretization process is discussed. Several corrections with different corrector formulae are carried out in thesePC schemes. The classicalDahlquist theory valid for the case when the stepsize is constant is preserved (under very mild restrictions on the stepsize) when suchPC schemes are used as variable stepsize variable formula methods (VSVFM's). This fact is exploited by allowing the stepsize to follow the variation of a certain norm of the wind velocity vector in aVSVFM based on specially constructedPC schemes with large intervals of absolute stability on the imaginary axis. A device that attempts to check both the accuracy and the stability in the course of the integration process has been developed. The code based on the application of thisVSVFM in the time-integration part of the treatment of both 2-dimensional and 3-dimensional models has been tested by using meteorological data prepared at stations located in practically all European countries. The numerical results indicate thatPC schemes with several correctors can successfully be used for the class of problems under consideration. The main reason for this success is the special nature of the computational cost per time-step (due to the splitting approach used). Some short remarks on the possibility of extending the results for large systems ofODE's arising in the treatment of other classes of problems are made.

A convergence analysis is presented for the implicit Euler and Lie splitting schemes when applied to nonlinear parabolic equations with delay. More precisely, we consider a vector field which is the sum of an unbounded dissipative operator and a delay term, where both point delays and distributed delays fit into the framework. Such equations are frequently encountered, e.g. in population dynamics. The main theoretical result is that both schemes converge with an order (of at least) $$q=1/2$$ , without any artificial regularity assumptions. We discuss implementation details for the methods, and the convergence results are verified by numerical experiments demonstrating both the correct order, as well as the efficiency gain of Lie splitting as compared to the implicit Euler scheme.

An extrapolated form of the basic first order stationary iterative method for solving linear systems when the associated iteration matrix possesses complex eigenvalues, is investigated. Sufficient (and necessary) conditions are given such that convergence is assured. An analytic determination of good (and sometimes optimum) values of the involved real parameter is presented in terms of certain bounds on the eigenvalues of the iteration matrix. The usefulness of the developed theory is shown through a simple application to the conventional Jacobi method.