This article introduces and analyzes a new adaptive algorithm for solving symmetric positive definite linear systems in cases where several preconditioners are available or the usual preconditioner is a sum of contributions. A new theoretical result allows to select, at each iteration, whether a classical preconditioned CG iteration is sufficient (i.e., the error decreases by a factor of at lea...

This paper presents a new algorithm for the parallel in time (PiT) numerical simulation of dependent partial/ordinary differential equations. We propose reliable alternative to well know parareal algorithm, by formulating problem algebraically and solve it using an adapted Bi-Conjugate gradient stabilized method. The proposed Parallel Stable (PiTSBiCG short) has great potential stabilizing reso...

We compare the performance of several robust large-scale minimization algorithms for the unconstrained minimization of an ill-posed inverse problem. The parabolized Navier-Stokes equations model was used for adjoint parameter estimation. The methods compared consist of two versions of the nonlinear conjugate gradient method (CG), Quasi-Newton (BFGS), the limited memory Quasi-Newton (L-BFGS) [15...

To improve the service quality of cloud computing, and aiming at characteristics resource scheduling optimization problems, this paper proposes a hybrid multi-objective bat algorithm. prevent algorithm from falling into local minimum, population is classified. The back-propagation based on mean square error conjugate gradient method used to increase loudness in search direction pulse emission r...