At the beginning of this century, which is characterized by huge flows of emerging data, Dai
and Liao proposed a pervasive conjugacy condition that triggered the interest of many …

Computer Science and Applied Mathematics: Constrained Optimization and Lagrange
Multiplier Methods focuses on the advancements in the applications of the Lagrange …

A generic optimization problem in any domain—science, engineering, medicine, or business—
involves finding the optimal value of an objective function that depends on a set of variables …

This book is on conjugate gradient methods for unconstrained optimization. The concept of
conjugacy was introduced by Magnus Hestenes and Garrett Birkhoff in 1936 in the context of …

Optimization Theory and Methods can be used as a textbook for an optimization course for
graduates and senior undergraduates. It is the result of the author's teaching and research …

Quasi-Newton methods were introduced by Charles Broyden [A class of methods for solving
nonlinear simultaneous equations, Math Comp. 19 (1965), pp. 577–593] as an alternative to …

An integrated molecular modeling system for designing and studying organic and
bioorganic molecules and their molecular complexes using molecular mechanics is …

This paper describes some numerical experiments with variable-storage quasi-Newton
methods for the optimization of some large-scale models (coming from fluid mechanics and …

Conjugate gradient methods are iterative methods for finding the minimizer of a scalar
function f (x) of a vector variable x which do not update an approximation to the inverse …

In this paper, we seek the conjugate gradient direction closest to the direction of the scaled
memoryless BFGS method and propose a family of conjugate gradient methods for …