A conjugate gradient method with descent direction for unconstrained optimization
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The conjugate gradient method (CGM) stands out as one of the most rapidly growing and effective approaches for addressing unconstrained optimization problems. In recent years, significant efforts have been dedicated to adapting the CGM for tackling nonlinear optimization challeng
The conjugate gradient technique is a numerical solution strategy for finding minimization in mathematics. We present simple, straightforward, efficient, and resilient this study. To address the convergence difficulty descent property, new built on quadratic model. Under some ass