Includes bibliographical references (pages 813-934) and index.
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.
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This is the first comprehensive reference on trust-region methods, a class of numerical algorithms for the solution of nonlinear convex optimization methods. Its unified treatment covers both unconstrained and constrained problems and reviews a large part of the specialized literature on the subject. It also provides an up-to-date view of numerical optimization.