Three interior point methods are proposed for sufficient horizontal linear complementarity problems (HLCP): a large update path following algorithm, a first order corrector-predictor method, and a second order corrector-predictor method. All algorithms produce sequences of iterates in the wide neighborhood of the central path introduced by Ai and Zhang. The algorithms do not depend on the handi...

In this paper, an improved predictor-corrector methods (IPC) to solve fuzzy differential equation under generalized differentiability are discussed. The methods proposed here are based on generalized characterization theorem. Using the Generalized Characterization we can translate a fuzzy differential equation into two ODE systems. Also, the convergence and stability of the proposed methods are...

Three interior point methods are proposed for sufficient horizontal linear complementarity problems (HLCP): a large update path following algorithm, a first order corrector-predictor method, and a second order corrector-predictor method. All algorithms produce sequences of iterates in the wide neighborhood of the central path introduced by Ai and Zhang. The algorithms do not depend on the handi...

The TAGE predictor [12] is considered as one of the most storage effective global branch/path history predictors. It has been shown that associated with small adjunct predictors like a statistical corrector (SC for short) and/or a loop predictor (L for short) [11, 10], TAGE can even be more effective. In this study, we explore the performance limits of these TAGE-SC-L predictors for respectivel...

We develop a new constraint-reduced infeasible predictor-corrector interior point method for semidefinite programming, and we prove that it has polynomial global convergence and superlinear local convergence. While the new algorithm uses HKM direction in predictor step, it adopts AHO direction in corrector step to achieve a faster approach to the central path. In contrast to the previous constr...