Table of Contents

Introducing Optimization.- One-variable Optimization.- Applications in n Variables.- n-Variable Unconstrained Optimization.- Direct Search Methods.- Computing Derivatives.- The Steepest Descent Method.- Weak Line Searches and Convergence.- Newton and Newton-like Methods.- Quasi-Newton Methods.- Conjugate Gradient Methods.- ASummary of Unconstrained Methods.- Optimization with Restrictions.- Larger-Scale Problems.- Global Unconstrained Optimization.- Equality Constrained Optimization.- Linear Equality Constraints.- Penalty Function Methods.- Sequential Quadratic Programming.- Inequality Constrained Optimization.- Extending Equality Constraint Methods.- Barrier Function Methods.- Interior Point Methods.- A Summary of Constrained Methods.- The OPTIMA Software.

Reviews

From the reviews: "This book gives on 280 pages a broad overview of nonlinear optimization. … The presented optimization approaches are compared with each other by means of several examples with up to 200 variables. … the introduction of the different techniques is written in a very comprehensible way. … each section contains exercises to verify and deepen the understanding of the material." (Andrea Walther, Zentralblatt MATH, Vol. 1167, 2009)