Predictor-corrector Smoothing Methods for the Solution of Linear Programs1

The symmetric two-step P-stable nonlinear predictor-corrector‎ ‎methods for the numerical solution of second order‎ ‎initial value problems

In this paper‎, ‎we propose a modification of the second order method‎ ‎introduced in [‎‎Q. Li and ‎X‎. ‎Y. ‎Wu‎, A two-step explicit $P$-stable method for solving second order initial value problems‎, ‎textit{‎Appl‎. ‎Math‎. ‎Comput‎.}‎ {‎138}‎ (2003)‎, no. 2-3, ‎435--442‎] for the numerical solution of‎ ‎IVPs for second order ODEs‎. ‎The numerical results obtained by the‎ ‎new method for some...

Nordsieck representation of high order predictor-corrector Obreshkov methods and their implementation

Predictor-corrector (PC) methods for the numerical solution of stiff ODEs can be extended to include the second derivative of the solution. In this paper, we consider second derivative PC methods with the three-step second derivative Adams-Bashforth as predictor and two-step second derivative Adams-Moulton as corrector which both methods have order six. Implementation of the proposed PC method ...

Predictor-Corrector Smoothing Methods for Linear Programs with a More Flexible Update of the Smoothing Parameter

EXTENDED PREDICTOR-CORRECTOR METHODS FOR SOLVING FUZZY DIFFERENTIAL EQUATIONS UNDER GENERALIZED DIFFERENTIABILITY

In this paper, the (m+1)-step Adams-Bashforth, Adams-Moulton, and Predictor-Correctormethods are used to solve rst-order linear fuzzy ordinary dierential equations. The conceptsof fuzzy interpolation and generalised strongly dierentiability are used, to obtaingeneral algorithms. Each of these algorithms has advantages over current methods. Moreover,for each algorithm a convergence formula can b...

Corrector-predictor arc-search interior-point algorithm for $P_*(kappa)$-LCP acting in a wide neighborhood of the central path

In this paper, we propose an arc-search corrector-predictor interior-point method for solving $P_*(kappa)$-linear complementarity problems. The proposed algorithm searches the optimizers along an ellipse that is an approximation of the central path. The algorithm generates a sequence of iterates in the wide neighborhood of central path introduced by Ai and Zhang. The algorithm does not de...