A new parameter for conjugate gradient methods using Dai and Liu conjugate condition to solve unconstrained optimization functions.

In this work, a novel nonlinear conjugate gradient approach that was designed to address unconstrained optimization problems is presented. The new parameter of the conjugate gradient algorithm was produced by employing the Dai and Liao condition. Under certain presumptions, we provide proof that the proposed technique has the features of global convergence and descent. Through the use of numerical examples, we demonstrated that the newly created algorithm is superior than the approaches proposed by Hestenes-Stiefel (HS,1952) and Dai-Yuan (DY, 1999) when it comes to the successful resolution of issues involving unconstrained optimization. [ABSTRACT FROM AUTHOR]