Preface Chapter 1: Introduction Part I: Preliminaries Chapter 2: Basic Concepts Chapter 3: Basic Analysis and Optimality Conditions Chapter 4: Basic Linear Algebra Chapter 5 Krylov Subspace Methods Part II: Trust-Region Methods For Unconstrained Optimization Chapter 6: Global Convergence of the Basic Algorithm Chapter 7: The Trust-Region Subproblem Chapter 8: Further Convergence Theory Issues Chapter 9: Conditional Models Chapter 10: Algorithmic Extensions Chapter 11: Nonsmooth Problems Part III: Trust-Region Methods For Constrained Optimization With Convex Constraints Chapter 12: Projection Methods for Convex Constraints Chapter 13: Barrier Methods for Inequality Constraints Part IV: Trust-Region Methods For General Constrained Optimization and Systems of Nonlinear Equations Chapter 14: Penalty-Function Methods Chapter 15: Sequential Quadratic Programming Methods Chapter 16: Nonlinear Equations and Nonlinear Fitting Part V: Final Considerations Chapter 17: Practicalities Afterword Appendix: A Summary of Assumptions Annotated Bibliography Subject and Notation Index Author Index.

