附註:Includes bibliographical references (pages 611-623) and index.
Cover -- Preface -- Table of Contents -- 1. Introduction -- 2. Fundamentals of Unconstrained Optimization -- 3. Line Search Methods -- 4. Trust-Region Methods -- 5. Conjugate Gradient Methods -- 6. Practical Newton Methods -- 7. Calculating Derivatives -- 8. Quasi-Newton Methods -- 9. Large-Scale Quasi-Newton and Partially Separable Optimization -- 10. Nonlinear Least-Squares Problems -- 11. Nonlinear Equations -- 12. Theory of Constrained Optimization -- 13. Linear Programming: The Simplex Method -- 14. Linear Programming: Interior-Point Methods -- 15. Fundamentals of Algorithms for Nonlinear Constrained Optimization -- 16. Quadratic Programming -- 17. Penalty, Barrier, and Augmented Lagrangian Methods -- 18. Sequential Quadratic Programming -- Appendix A -- Background Material -- References.
摘要:This work covers numerical methods for finite-dimensional optimisation problems involving fairly smooth functions. It concentrates on methods for unconstrained optimisation, with attention given at the end to problems with constraints.
