Abstract
In this study, we introduce a novel hybrid conjugate gradient [CG] to solve an efficient and effective unconstrained optimization problem. The parameter θk is a convex combination of the conjugate gradient method and . Under strong Wolfe line search conditions (SWC), we have shown that this method is globally convergent, and the proposed hybrid CG method is able to generate a descending search direction at each iteration. The numerical results presented, in this paper demonstrate that the proposed strategy is both effective and promising.
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