Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...

Abstract: Conjugate gradient techniques are widely used to solve unconstrained optimization issues. The accelerated conjugate gradient approach provides superior numerical effects for the ...

The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. In this paper, we present a new algorithm of ...

This is a preview. Log in through your library . Abstract In this paper, a family of three-term conjugate gradient methods is proposed to solve a large-scale unconstrained optimization problem. With ...

ABSTRACT: Whale Optimization Algorithm (WOA) is a meta-heuristic algorithm. It is a new algorithm, it simulates the behavior of Humpback Whales in their search for food and migration. In this paper, a ...

This is a PyTorch based machine learning project that focuses on implementing the Trust Region Newton Conjugate Gradient (TRNCG) optimization algorithm to train a neural network. Since TRNCG is not ...

Abstract: For the solutions of large and sparse linear systems of equations with unsymmetric coefficient matrices, we propose an improved version of the Conjugate Gradient Squared method (ICGS) method ...

This repository contains all homework assignments for the "Optimization of Mechanical Systems" course at the University of Tehran. The projects cover the modeling, analysis, and solution of complex, ...