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 ...

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 ...

This course introduces high-performance computing (“HPC”) systems, software, and methods used to solve large-scale problems in science and engineering. It will focus on the intersection of two ...

Studies linear and nonlinear programming, the simplex method, duality, sensitivity, transportation and network flow problems, some constrained and unconstrained optimization theory, and the ...

In this paper, we propose an algorithm for solving inequality constrained mini-max optimization problem. In this algorithm, an active set strategy is used together with multiplier method to convert ...