In this paper, based on the efficient Conjugate Descent ({\tt CD}) method, two generalized {\tt CD}algorithms are proposed to solve unconstrained optimization problems.These methods three-term conjugate gradient which generateddirections by using parameters and independent of line searchsatisfy in sufficient descent condition. Furthermore, under strong Wolfe search,the global convergence proved...

In this paper the use of iterative methods for the solution of the carrier continuity equations in three-dimensional semiconductor device simulators is summarized. An overview of the derivation of the linear systems from the basic stationary semiconductor device equations is given and the algebraic properties of the nonsymmetric coefficient matrices are discussed. Results from the following cla...

Conjugate gradient methods are efficient for smooth optimization problems, while there are rare conjugate gradient based methods for solving a possibly nondifferentiable convex minimization problem. In this paper by making full use of inherent properties of Moreau-Yosida regularization and descent property of modified conjugate gradient method we propose a modified Fletcher-Reeves-type method f...

<span>Unconstrained optimization problems, such as energy minimization, can be solved using the conjugate gradient method. For its major characteristic, optimal formula encompasses all algorithms. In approaches, is typically focus point and it's playing a very important role for approaches. To offer essential descent criteria in this work, we devised novel based on second order Taylor whi...

Conjugate gradient methods are widely used for unconstrained optimization, especially large scale problems. Most of conjugate gradient methods don’t always generate a descent search direction, so the descent condition is usually assumed in the analyses and implementations. Dai and Yuan (1999) proposed the conjugate gradient method which generates a descent direction at every iteration. Yabe and...

in this paper, chebyshev acceleration technique is used to solve the fuzzy linear system (fls). this method is discussed in details and followed by summary of some other acceleration techniques. moreover, we show that in some situations that the methods such as jacobi, gauss-sidel, sor and conjugate gradient is divergent, our proposed method is applicable and the acquired results are illustrate...

In this paper, Chebyshev acceleration technique is used to solve the fuzzy linear system (FLS). This method is discussed in details and followed by summary of some other acceleration techniques. Moreover, we show that in some situations that the methods such as Jacobi, Gauss-Sidel, SOR and conjugate gradient is divergent, our proposed method is applicable and the acquired results are illustrate...

Conjugate gradient methods are a class of important methods for unconstrained optimization, especially when the dimension is large. This paper proposes a new conjugacy condition, which considers an inexact line search scheme but reduces to the old one if the line search is exact. Based on the new conjugacy condition, two nonlinear conjugate gradient methods are constructed. Convergence analysis...