Strong predictor–corrector Euler–Maruyama methods for stochastic differential equations with Markovian switching

In this paper numerical methods for solving stochastic differential equations with Markovian switching (SDEwMSs) are developed by pathwise approximation. The proposed family of strong predictor–corrector Euler–Maruyama methods is designed to overcome the propagation of errors during the simulation of an approximate path. This paper not only shows the strong convergence of the numerical solution to the exact solution but also reveals the order of the error under some conditions on the coefficient functions. A natural analogue of the p$p$-stability criterion is studied. Numerical examples are given to illustrate the computational efficiency of the new predictor–corrector Euler–Maruyama approximation.     

Adaptive use of iterative methods in predictor–corrector interior point methods for linear programming

In this work we devise efficient algorithms for finding the search directions for interior point methods applied to linear programming problems. There are two innovations. The first is the use of updating of preconditioners computed for previous barrier parameters. The second is an adaptive automated procedure for determining whether to use a direct or iterative solver, whether to reinitialize or update the preconditioner, and how many updates to apply. These decisions are based on predictions of the cost of using the different solvers to determine the next search direction, given costs in determining earlier directions. We summarize earlier results using a modified version of the OB1-R code of Lustig, Marsten, and Shanno, and we present results from a predictor–corrector code PCx modified to use adaptive iteration. If a direct method is appropriate for the problem, then our procedure chooses it, but when an iterative procedure is helpful, substantial gains in efficiency can be obtained.     

An efficient time-step-based self-adaptive algorithm for predictor–corrector methods of Runge–Kutta type

Finding an efficient implementation variant for the numerical solution of problems from computational science and engineering involves many implementation decisions that are strongly influenced by the specific hardware architecture. The complexity of these architectures makes it difficult to find the best implementation variant by manual tuning. For numerical solution methods from linear algebra, auto-tuning techniques based on a global search engine as they are used for ATLAS or FFTW can be used successfully. These techniques generate different implementation variants at installation time and select one of these implementation variants either at installation time or at runtime, before the computation starts. For some numerical methods, auto-tuning at installation time cannot be applied directly, since the best implementation variant may strongly depend on the specific numerical problem to be solved. An example is solution methods for initial value problems (IVPs) of ordinary differential equations (ODEs), where the coupling structure of the ODE system to be solved has a large influence on the efficient use of the memory hierarchy of the hardware architecture. In this context, it is important to use auto-tuning techniques at runtime, which is possible because of the time-stepping nature of ODE solvers.In this article, we present a sequential self-adaptive ODE solver that selects the best implementation variant from a candidate pool at runtime during the first time steps, i.e., the auto-tuning phase already contributes to the progress of the computation. The implementation variants differ in the loop structure and the data structures used to realize the numerical algorithm, a predictor–corrector (PC) iteration scheme with Runge–Kutta (RK) corrector considered here as an example. For those implementation variants in the candidate pool that use loop tiling to exploit the memory hierarchy of a given hardware platform we investigate the selection of tile sizes. The self-adaptive ODE solver combines empirical search with a model-based approach in order to reduce the search space of possible tile sizes. Runtime experiments demonstrate the efficiency of the self-adaptive solver for different IVPs across a range of problem sizes and on different hardware architectures.     

Optimized Runge–Kutta pairs for problems with oscillating solutions

Three types of methods for integrating periodic initial value problems are presented. These methods are (i) phase-fitted, (ii) zero dissipation (iii) both zero dissipative and phase fitted. Some particular modifications of well-known explicit Runge–Kutta pairs of orders five and four are constructed. Numerical experiments show the efficiency of the new pairs in a wide range of oscillatory problems.     

Runge–Kutta–Nyström‐type parallel block predictor–corrector methods

This paper describes the construction of block predictor–corrector methods based on Runge–Kutta–Nyström correctors. Our approach is to apply the predictor–corrector method not only with stepsize h, but, in addition (and simultaneously) with stepsizes a _i h, i = 1 ...,r. In this way, at each step, a whole block of approximations to the exact solution at off‐step points is computed. In the next step, these approximations are used to obtain a high‐order predictor formula using Lagrange or Hermite interpolation. Since the block approximations at the off‐step points can be computed in parallel, the sequential costs of these block predictor–corrector methods are comparable with those of a conventional predictor–corrector method. Furthermore, by using Runge–Kutta–Nyström corrector methods, the computation of the approximation at each off‐step point is also highly parallel. Numerical comparisons on a shared memory computer show the efficiency of the methods for problems with expensive function evaluations.     

Implicit–explicit predictor–corrector schemes for nonlinear parabolic differential equations

In the present paper, a family of predictor–corrector (PC) schemes are developed for the numerical solution of nonlinear parabolic differential equations. Iterative processes are avoided by use of the implicit–explicit (IMEX) methods. Moreover, compared to the predictor schemes, the proposed methods usually have superior accuracy and stability properties. Some confirmation of these are illustrated by using the schemes on the well-known Fisher’s equation.     

On accelerating PL continuation algorithms by predictor—corrector methods

We consider path following methods designed to trace the zeroes of a continuous or differentiable mapF:R ⁿ⁺¹ R ⁿ . These methods are applicable e.g. in the numerical study of nonlinear eigenvalue and bifurcation problems. Traditionally a simplicial algorithm is based on a fixed triangulationT ofR ⁿ⁺¹ and a corresponding piecewise linear approximationF _T :R ⁿ⁺¹ R ⁿ .4 A fixed triangulation algorithm then traces the zeroes ofF _T via a complementary pivoting procedure. We present two kinds of hybrid algorithms that have the structure of a predictor—corrector method using simplicial methods to carry out the corrector steps. Numerical experience is reported showing the improvement in efficiency as compared to the fixed triangulation algorithm.     

A new predictor–corrector method for solving unconstrained minimization problems

This paper presents a new predictor–corrector method for finding a local minimum of a twice continuously differentiable function. The method successively constructs an approximation to the solution curve and determines a predictor on it using a technique similar to that used in trust region methods for unconstrained optimization. The proposed predictor is expected to be more effective than Euler's predictor in the sense that the former is usually much closer to the solution curve than the latter for the same step size. Results of numerical experiments are reported to demonstrate the effectiveness of the proposed method.     

Pseudo almost periodic solutions for a Lasota–Wazewska model with an oscillating death rate

This paper is concerned with a Lasota–Wazewska model with an oscillating death rate. Under proper conditions, we employ a novel argument to establish a criterion on the existence and stability of positive pseudo almost periodic solutions. The obtained result complements with some existing ones.     

A new family of three-stage two-step P-stable multiderivative methods with vanished phase-lag and some of its derivatives for the numerical solution of radial Schrödinger equation and IVPs with oscillating solutions

A new family of three-stage two-step methods are presented in this paper. These methods are of algebraic order 12 and have an important P-stability property. To make these methods, vanishing phase-lag and some of its derivatives have been used. The main structure of these methods are multiderivative, and the combined phases have been applied for expanding stability interval and for achieving P-stability. The advantage of the new methods in comparison with similar methods, in terms of efficiency, accuracy, and stability, has been showed by the implementation of them in some important problems, including the radial time-independent Schrödinger equation during the resonance problems with the use of the Woods-Saxon potential, undamped Duffing equation, etc.

     

A family of predictor–corrector schemes for a class of variational inequalities

This work is concerned with an abstract problem in the form of a variational inequality, or equivalently a minimization problem involving a non-differential functional. The problem is inspired by a formulation of the initial–boundary value problem of elastoplasticity. The objective of this work is to revisit the predictor–corrector algorithms that are commonly used in computational applications, and to establish conditions under which these are convergent or, at least, under which they lead to decreasing sequences of the functional for the problem. The focus is on the predictor step, given that the corrector step by definition leads to a decrease in the functional. The predictor step may be formulated as a minimization problem. Attention is given to the tangent predictor, a line search approach, the method of steepest descent, and a Newton-like method. These are all shown to lead to decreasing sequences.     

A non–interior predictor–corrector path following algorithm for the monotone linear complementarity problem

We present a predictor–corrector non–interior path following algorithm for the monotone linear complementarity problem based on Chen–Harker–Kanzow–Smale smoothing techniques. Although the method is modeled on the interior point predictor–corrector strategies, it is the first instance of a non–interior point predictor–corrector algorithm. The algorithm is shown to be both globally linearly convergent and locally quadratically convergent under standard hypotheses. The approach to global linear convergence follows the authors’ previous work on this problem for the case of (P ₀+R ₀) LCPs. However, in this paper we use monotonicity to refine our notion of neighborhood of the central path. The refined neighborhood allows us to establish the uniform boundedness of certain slices of the neighborhood of the central path under the standard hypothesis that a strictly positive feasible point exists. Received September 1997 / Revised version received May 1999?Published online December 15, 1999     

Exponentially-fitted Runge-Kutta-Nyström method for the numerical solution of initial-value problems with oscillating solutions

A new approach for constructing efficient Runge-Kutta-Nyström methods is introduced in this paper. Based on this new approach a new exponentially-fitted Runge-Kutta-Nyström fourth-algebraic-order method is obtained for the numerical solution of initial-value problems with oscillating solutions. The new method has an extended interval of periodicity. Numerical illustrations on well-known initial-value problems with oscillating solutions indicate that the new method is more efficient than other ones.     

An embedded pair of exponentially fitted explicit Runge–Kutta methods

An embedded pair of exponentially fitted explicit Runge–Kutta (RK) methods for the numerical integration of IVPs with oscillatory solutions is derived. This pair is based on the exponentially fitted explicit RK method constructed in Vanden Berghe et al., and we confirm that the methods which constitute the pair have algebraic order 4 and 3. Some numerical experiments show the efficiency of our pair when it is compared with the variable step code proposed by Vanden Berghe et al. (J. Comput. Appl. Math. 125 (2000) 107).     

Numerical solution of hybrid fuzzy differential equations using improved predictor–corrector method

The hybrid fuzzy differential equations have a wide range of applications in science and engineering. This paper considers numerical solution for hybrid fuzzy differential equations. The improved predictor–corrector method is adapted and modified for solving the hybrid fuzzy differential equations. The proposed algorithm is illustrated by numerical examples and the results obtained using the scheme presented here agree well with the analytical solutions. The computer symbolic systems such as Maple and Mathematica allow us to perform complicated calculations of algorithm.     

Rapidly oscillating solutions of a generalized Korteweg–de Vries equation

For a generalized Korteweg–de Vries equation, the existence of families of rapidly oscillating periodic solutions is proved and their asymptotic representation is found. The asymptotics of tori of different dimensions are examined. Formulas for solutions depending on all parameters of the problem are derived.     

On using explicit Runge–Kutta–Nyström methods for the treatment of retarded differential equations with periodic solutions

In this work we dial with the treatment of second order retarded differential equations with periodic solutions by explicit Runge–Kutta–Nyström methods. In the past such methods have not been studied for this class of problems. We refer to the underline theory and study the behavior of various methods proposed in the literature when coupled with Hermite interpolants. Among them we consider methods having the characteristic of phase–lag order. Then we consider continuous extensions of the methods to treat the retarded part of the problem. Finally we construct scaled extensions and high order interpolants for RKN pairs which have better characteristics compared to analogous methods proposed in the literature. In all cases numerical tests and comparisons are done over various test problems.