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)

• 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.

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)

• 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.

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)

• 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.