A Variant of Self-Adjusting Spectral Hybrid Dai-Liao Conjugate Gradient Method

A DL -like Hybrid of DY Conjugate Gradient Algorithm for Unconstrained Optimization Problems with Application in Mode Function

Conjugate gradient methods have come a long way in solving system of equations and large scaled optimization problems. In this paper, a hybrid conjugate gradient method which incorporates the DY update parameter and herein constructed conjugate gradient solver that uses Dai-Liao conjugacy conditions is proposed for non...

Another hybrid conjugate gradient method as a convex combination of NVHS∗ and CD methods

Conjugate gradient methods play a fundamental role in solving unconstrained optimization problems. We propose a new hybrid conjugate gradient algorithm that forms a convex combination of βNVHS∗k and βCDk. The parameter θk is determined so as to satisfy the conjugacy condition. Under the strong Wolfe line search conditi...

Hybridization of two conjugate gradient methods for multiobjective optimization beyond convexity and Lipschitz continuity

A new hybrid conjugate gradient method as a convex combination of HZ and FR and PRP methods

In this paper, we propose a new conjugate gradient method for solving unconstrained optimization problem, whom is convex combination of the Hager-Zhan, Fletcher-Reeves and Polak-Ribére-Polyak algorithms. The search direction satisfies the sufficient descent condition and guarantees global convergence under the strong W...

Nonmonotone Coderivative-Based Newton Methods for Nonsmooth Optimization with Machine Learning Applications

Newton-type algorithms are among the most effective methods for solving optimization problems because of their rapid local convergence. However, extending these methods to nonsmooth optimization is challenging due to the difficulty of incorporating second-order information. To address this issue, we propose a coderivat...

A convex combination conjugate gradient algorithm with application in mode function

Conjugate gradient methods are a popular class of iterative methods for solving linear systems of equations and nonlinear optimization problems. In this paper, we suggest a new hybrid nonlinear conjugate gradient method, in which the conjugate gradient coefficient $\beta _{k}$ is a convex combination of $\beta _{k}^{NV...