Although quasi-Newton algorithms generally converge in fewer iterations than conjugate gradient algorithms, they have the disadvantage of requiring substantially more storage. An algorithm will be described which uses an intermediate (and variable) amount of storage and which demonstrates convergence which is also intermediate, that is, generally better than that observed for conjugate gradient...

We study a parallel Newton-Krylov-Schwarz (NKS) based algorithm for solving large sparse systems resulting from a fully implicit discretization of partial differential equations arising from petroleum reservoir simulations. Our NKS algorithm is designed by combining an inexact Newton method with a rank-2 updated quasi-Newton method. In order to improve the computational efficiency, both DDM and...

Several problems have been solved by nonlinear equation systems (NESs), including real-life issues in chemistry and neurophysiology. However, the accuracy of solutions is highly dependent on efficiency algorithm used. In this paper, a Modified Sperm Swarm Optimization Algorithm called MSSO introduced to solve NESs. combines Newton’s second-order iterative method with (SSO). Through combination,...

The diierential dynamic programming algorithm (DDP) and the stage-wise Newton procedure are two typical examples of eecient local procedures for discrete-time optimal control (DTOC) problems. It is desirable to generalize these local procedures to globally convergent methods. One successful globalization was recently proposed by Coleman and Liao 3] which combines the trust region idea with Pant...

Model Predictive Control (MPC) is increasing in popularity in industry as more e cient algorithms for solving the related optimization problem are developed. The main computational bottle-neck in on-line MPC is often the computation of the search step direction, i.e. the Newton step, which is often done using generic sparsity exploiting algorithms or Riccati recursions. However, as parallel har...

This article develops a new algorithm for computing a Nash equilibrium of an N-person game. The algorithm approximates the game by a sequence of polymatrix games. We provide su±cient conditions for local convergence to an equilibrium and report on our computational experience. The algorithm convergences rapidly but it is not failsafe. We show that if the algorithm does not converge then one can...

In lifetime analysis of electric transformers, the maximum likelihood estimation has been proposed with the EM algorithm. However, it is not clear whether the EM algorithm offers a better solution compared to the simpler Newton-Raphson algorithm. In this paper, the first objective is a systematic comparison of the EM algorithm with the Newton-Raphson algorithm in terms of convergence performanc...