A Hybrid Conjugate Gradient Method for Unconstrained Optimization With Application

This article considers a hybrid minimization algorithm from optimal choice of the modulatingnon-negative parameter of Dai-Liao conjugacy condition. The new hybrid parameter is selected in suchaway that a convex combination of Hestenes-Stiefel and Dai-Yuan Conjugate Gradient (CG) algorithmsis fulfilled. The numerical implementation adopts inexact line search which reveals that the scheme isrobust when compared with some known efficient algorithms in literature. Furthermore, the theoreticalanalysis shows that the proposed hybrid method converges globally. The method is also applicable tosolve three degree of freedom motion control robotic model.