Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.

Estes elementos decorativos encontram paralelo no con- junto orientalizante de Talavera la Vieja (Cáceres), onde se encontram peças semelhantes fabricadas em prata, com a

The integrated use of these two operational research (OR) methods should allow the problem at hand (i.e. the clas- sification of tenants in the residential rental market) to be

Abstract - Two multi-objective optimization based tuning methods for model predictive control are proposed.. Both methods consider the minimization of the error between the

In this article we present a new channel compensation technique based on the concurrent operation of two stochastic gradient time- domain algorithms, one which minimizes a

So it was not our goal in this paper to compare Conjugate Gradient with those methods, but to show that our approximation of GCV is applicable as a stopping rule to the

Although some conjugate gradient methods have good numerical performance in solving large scale minimization problems, they have no global convergence in some situations [6].. We

Based on the secant condition often satisfied by quasi-Newton methods, two new versions of the Hestenes-Stiefel (HS) nonlinear conjugate gradient method are proposed, which are

In this section, we do some numerical experiments to test Algorithm 2.1 with the modified strong Wolfe line search, and compare the performance with some existing conjugate