Conjugate directions methods for quadratic problems -- Conjugate gradient methods for nonconvex problems -- Memoryless quasi-Newton methods -- Preconditioned conjugate gradient algorithms -- Limited memory quasi-Newton algorithms -- A method of shortest residuals and nondifferentiable optimization -- The method of shortest residuals for smooth problems -- The preconditioned shortest residuals algorithm -- Optimization on a polyhedron -- Problems with box constraints -- The preconditioned shortest residuals algorithm with box -- Conjugate gradient reduced-Hessian method -- Elements of topology and analysis -- Elements of linear algebra
Summary
Explains algorithms for large-scale unconstrained and bound constrained optimization. This book shows optimization techniques from a conjugate gradient algorithm perspective. It is devoted to preconditioned conjugate gradient algorithms. It focuses on the methods of shortest residuals developed by the author
