Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method.
The purpose of this book is to develop a wide collection of nonlinear optimization applications from the real-world expressed in the GAMS (General Algebraic Modeling System) language.
The qualifier modern in the title refers to the unconstrained and constrained optimization algorithms that combine and integrate the latest and the most efficient optimization techniques and advanced computational linear algebra methods.